The validity of the air traffic selection and training (AT-SAT) test battery in operational use.

DOT National Transportation Integrated Search

2013-03-01

Applicants for the air traffic control specialist (ATCS) occupation from the general public and graduates from post-secondary institutions participating in the FAAs Air Traffic Collegiate Training Initiative (AT-CTI) must take and pass the Air Tra...

Systematic review of serious games for medical education and surgical skills training.

PubMed

Graafland, M; Schraagen, J M; Schijven, M P

2012-10-01

The application of digital games for training medical professionals is on the rise. So-called 'serious' games form training tools that provide a challenging simulated environment, ideal for future surgical training. Ultimately, serious games are directed at reducing medical error and subsequent healthcare costs. The aim was to review current serious games for training medical professionals and to evaluate the validity testing of such games. PubMed, Embase, the Cochrane Database of Systematic Reviews, PsychInfo and CINAHL were searched using predefined inclusion criteria for available studies up to April 2012. The primary endpoint was validation according to current criteria. A total of 25 articles were identified, describing a total of 30 serious games. The games were divided into two categories: those developed for specific educational purposes (17) and commercial games also useful for developing skills relevant to medical personnel (13). Pooling of data was not performed owing to the heterogeneity of study designs and serious games. Six serious games were identified that had a process of validation. Of these six, three games were developed for team training in critical care and triage, and three were commercially available games applied to train laparoscopic psychomotor skills. None of the serious games had completed a full validation process for the purpose of use. Blended and interactive learning by means of serious games may be applied to train both technical and non-technical skills relevant to the surgical field. Games developed or used for this purpose need validation before integration into surgical teaching curricula. Copyright © 2012 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.

49 CFR 380.301 - General requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

...-Training Program must be for the operation of CMVs representative of the subject matter that he/she will... instructor; (3) Possess a valid Class A CDL with all endorsements necessary to operate the CMVs applicable to...' CMV driving experience in a vehicle representative of the type of driver training to be provided (LCV...

49 CFR 380.301 - General requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

...-Training Program must be for the operation of CMVs representative of the subject matter that he/she will... instructor; (3) Possess a valid Class A CDL with all endorsements necessary to operate the CMVs applicable to...' CMV driving experience in a vehicle representative of the type of driver training to be provided (LCV...

49 CFR 380.301 - General requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

...-Training Program must be for the operation of CMVs representative of the subject matter that he/she will... instructor; (3) Possess a valid Class A CDL with all endorsements necessary to operate the CMVs applicable to...' CMV driving experience in a vehicle representative of the type of driver training to be provided (LCV...

49 CFR 380.301 - General requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

...-Training Program must be for the operation of CMVs representative of the subject matter that he/she will... instructor; (3) Possess a valid Class A CDL with all endorsements necessary to operate the CMVs applicable to...' CMV driving experience in a vehicle representative of the type of driver training to be provided (LCV...

Increasing self-regulatory energy using an Internet-based training application delivered by smartphone technology.

PubMed

Cranwell, Jo; Benford, Steve; Houghton, Robert J; Golembewski, Michael; Golembewksi, Michael; Fischer, Joel E; Hagger, Martin S

2014-03-01

Self-control resources can be defined in terms of "energy." Repeated attempts to override desires and impulses can result in a state of reduced self-control energy termed "ego depletion" leading to a reduced capacity to regulate future self-control behaviors effectively. Regular practice or "training" on self-control tasks may improve an individual's capacity to overcome ego depletion effectively. The current research tested the effectiveness of training using a novel Internet-based smartphone application to improve self-control and reduce ego depletion. In two experiments, participants were randomly assigned to either an experimental group, which received a daily program of self-control training using a modified Stroop-task Internet-based application delivered via smartphone to participants over a 4-week period, or a no-training control group. Participants assigned to the experimental group performed significantly better on post-training laboratory self-control tasks relative to participants in the control group. Findings support the hypothesized training effect on self-control and highlight the effectiveness of a novel Internet-based application delivered by smartphone as a practical means to administer and monitor a self-control training program. The smartphone training application has considerable advantages over other means to train self-control adopted in previous studies in that it has increased ecological validity and enables effective monitoring of compliance with the training program.

First CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

1990-01-01

The first Conference of C Language Production Systems (CLIPS) hosted by the NASA-Lyndon B. Johnson Space Center in August 1990 is presented. Articles included engineering applications, intelligent tutors and training, intelligent software engineering, automated knowledge acquisition, network applications, verification and validation, enhancements to CLIPS, space shuttle quality control/diagnosis applications, space shuttle and real-time applications, and medical, biological, and agricultural applications.

Novel Television-Based Cognitive Training Improves Working Memory and Executive Function

PubMed Central

Shatil, Evelyn; Mikulecká, Jaroslava; Bellotti, Francesco; Bureš, Vladimír

2014-01-01

The main study objective was to investigate the effect of interactive television-based cognitive training on cognitive performance of 119 healthy older adults, aged 60–87 years. Participants were randomly allocated to a cognitive training group or to an active control group in a single-blind controlled two-group design. Before and after training interactive television cognitive performance was assessed on well validated tests of fluid, higher-order ability, and system usability was evaluated. The participants in the cognitive training group completed a television-based cognitive training programme, while the participants in the active control group completed a TV-based programme of personally benefiting activities. Significant improvements were observed in well validated working memory and executive function tasks in the cognitive training but not in the control group. None of the groups showed statistically significant improvement in life satisfaction score. Participants' reports of “adequate” to “high” system usability testify to the successful development and implementation of the interactive television-based system and compliant cognitive training contents. The study demonstrates that cognitive training delivered by means of an interactive television system can generate genuine cognitive benefits in users and these are measurable using well-validated cognitive tests. Thus, older adults who cannot use or afford a computer can easily use digital interactive television to benefit from advanced software applications designed to train cognition. PMID:24992187

Increasing Self-Regulatory Energy Using an Internet-Based Training Application Delivered by Smartphone Technology

PubMed Central

Benford, Steve; Houghton, Robert J.; Golembewksi, Michael; Fischer, Joel E.; Hagger, Martin S.

2014-01-01

Abstract Self-control resources can be defined in terms of “energy.” Repeated attempts to override desires and impulses can result in a state of reduced self-control energy termed “ego depletion” leading to a reduced capacity to regulate future self-control behaviors effectively. Regular practice or “training” on self-control tasks may improve an individual's capacity to overcome ego depletion effectively. The current research tested the effectiveness of training using a novel Internet-based smartphone application to improve self-control and reduce ego depletion. In two experiments, participants were randomly assigned to either an experimental group, which received a daily program of self-control training using a modified Stroop-task Internet-based application delivered via smartphone to participants over a 4-week period, or a no-training control group. Participants assigned to the experimental group performed significantly better on post-training laboratory self-control tasks relative to participants in the control group. Findings support the hypothesized training effect on self-control and highlight the effectiveness of a novel Internet-based application delivered by smartphone as a practical means to administer and monitor a self-control training program. The smartphone training application has considerable advantages over other means to train self-control adopted in previous studies in that it has increased ecological validity and enables effective monitoring of compliance with the training program. PMID:24015984

Development of a proficiency-based virtual reality simulation training curriculum for laparoscopic appendicectomy.

PubMed

Sirimanna, Pramudith; Gladman, Marc A

2017-10-01

Proficiency-based virtual reality (VR) training curricula improve intraoperative performance, but have not been developed for laparoscopic appendicectomy (LA). This study aimed to develop an evidence-based training curriculum for LA. A total of 10 experienced (>50 LAs), eight intermediate (10-30 LAs) and 20 inexperienced (<10 LAs) operators performed guided and unguided LA tasks on a high-fidelity VR simulator using internationally relevant techniques. The ability to differentiate levels of experience (construct validity) was measured using simulator-derived metrics. Learning curves were analysed. Proficiency benchmarks were defined by the performance of the experienced group. Intermediate and experienced participants completed a questionnaire to evaluate the realism (face validity) and relevance (content validity). Of 18 surgeons, 16 (89%) considered the VR model to be visually realistic and 17 (95%) believed that it was representative of actual practice. All 'guided' modules demonstrated construct validity (P < 0.05), with learning curves that plateaued between sessions 6 and 9 (P < 0.01). When comparing inexperienced to intermediates to experienced, the 'unguided' LA module demonstrated construct validity for economy of motion (5.00 versus 7.17 versus 7.84, respectively; P < 0.01) and task time (864.5 s versus 477.2 s versus 352.1 s, respectively, P < 0.01). Construct validity was also confirmed for number of movements, path length and idle time. Validated modules were used for curriculum construction, with proficiency benchmarks used as performance goals. A VR LA model was realistic and representative of actual practice and was validated as a training and assessment tool. Consequently, the first evidence-based internationally applicable training curriculum for LA was constructed, which facilitates skill acquisition to proficiency. © 2017 Royal Australasian College of Surgeons.

Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments.

PubMed

Jones, B E; South, B R; Shao, Y; Lu, C C; Leng, J; Sauer, B C; Gundlapalli, A V; Samore, M H; Zeng, Q

2018-01-01

Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes. This article (1) develops a NLP tool that identifies the clinical assertion of pneumonia from physician emergency department (ED) notes, and (2) compares classification methods using diagnosis codes versus NLP against a gold standard of manual chart review to identify patients initially treated for pneumonia. Among a national population of ED visits occurring between 2006 and 2012 across the Veterans Affairs health system, we extracted 811 physician documents containing search terms for pneumonia for training, and 100 random documents for validation. Two reviewers annotated span- and document-level classifications of the clinical assertion of pneumonia. An NLP tool using a support vector machine was trained on the enriched documents. We extracted diagnosis codes assigned in the ED and upon hospital discharge and calculated performance characteristics for diagnosis codes, NLP, and NLP plus diagnosis codes against manual review in training and validation sets. Among the training documents, 51% contained clinical assertions of pneumonia; in the validation set, 9% were classified with pneumonia, of which 100% contained pneumonia search terms. After enriching with search terms, the NLP system alone demonstrated a recall/sensitivity of 0.72 (training) and 0.55 (validation), and a precision/positive predictive value (PPV) of 0.89 (training) and 0.71 (validation). ED-assigned diagnostic codes demonstrated lower recall/sensitivity (0.48 and 0.44) but higher precision/PPV (0.95 in training, 1.0 in validation); the NLP system identified more "possible-treated" cases than diagnostic coding. An approach combining NLP and ED-assigned diagnostic coding classification achieved the best performance (sensitivity 0.89 and PPV 0.80). System-wide application of NLP to clinical text can increase capture of initial diagnostic hypotheses, an important inclusion when studying diagnosis and clinical decision-making under uncertainty. Schattauer GmbH Stuttgart.

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies

PubMed Central

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-01-01

Background The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study Aim To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. Design and setting A three-part longitudinal predictive validity study of selection into training for UK general practice. Method In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Results Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. Conclusion In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered. PMID:24267856

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

PubMed

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-11-01

The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

Face validation of the Simbionix LAP Mentor virtual reality training module and its applicability in the surgical curriculum.

PubMed

Ayodeji, I D; Schijven, M; Jakimowicz, J; Greve, J W

2007-09-01

The goal of our study was to determine expert and referent face validity of the LAP Mentor, the first procedural virtual reality (VR) laparoscopy trainer. In The Netherlands 49 surgeons and surgical trainees were given a hands-on introduction to the Simbionix LAP Mentor training module. Subsequently, a standardized five-point Likert-scale questionnaire was administered. Respondents who had performed over 50 laparoscopic procedures were classified as "experts." The others constituted the "referent" group, representing nonexperts such as surgical trainees. Of the experts, 90.5% (n = 21) judge themselves to be average or above-average laparoscopic surgeons, while 88.5% of referents (n = 28) feel themselves to be less-than-average laparoscopic surgeons (p = 0.000). There is agreement between both groups on all items concerning the simulator's performance and application. Respondents feel strongly about the necessity for training on basic skills before operating on patients and unanimously agree on the importance of procedural training. A large number (87.8%) of respondents expect the LAP Mentor to enhance a trainee's laparoscopic capability, 83.7% expect a shorter laparoscopic learning curve, and 67.3% even predict reduced complication rates in laparoscopic cholecystectomies among novice surgeons. The preferred stage for implementing the VR training module is during the surgeon's residency, and 59.2% of respondents feel the surgical curriculum is incomplete without VR training. Both potential surgical trainees and trainers stress the need for VR training in the surgical curriculum. Both groups believe the LAP Mentor to be a realistic VR module, with a powerful potential for training and monitoring basic laparoscopic skills as well as full laparoscopic procedures. Simulator training is perceived to be both informative and entertaining, and enthusiasm among future trainers and trainees is to be expected. Further validation of the system is required to determine whether the performance results agree with these favorable expectations.

Validating a Culturally-sensitive Social Competence Training Programme for Adolescents with ASD in a Chinese Context: An Initial Investigation.

PubMed

Chan, Raymond Won Shing; Leung, Cecilia Nga Wing; Ng, Denise Ching Yiu; Yau, Sania Sau Wai

2018-02-01

Previous studies on social skills training on ASD were done almost exclusively in the West with children as the main subjects. Demonstrations of the applicability of social interventions in different cultures and age groups are warranted. The current study outlined the development and preliminary evaluation of a CBT-context-based social competence training for ASD (CBT-CSCA) developed in Hong Kong for Chinese adolescents with ASD. Twenty-five adolescents (aged 12-17 years, with a FSIQ above 80) were recruited. Significant improvements in social competence, autistic symptoms and general psychopathology at post-training and 3-month follow-up were reported by the parents. The study provided initial evidence support to the applicability of social competence training for adolescents with ASD in a different culture.

Evaluation of two selection tests for recruitment into radiology specialty training.

PubMed

Patterson, Fiona; Knight, Alec; McKnight, Liam; Booth, Thomas C

2016-07-11

This study evaluated whether two selection tests previously validated for primary care General Practice (GP) trainee selection could provide a valid shortlisting selection method for entry into specialty training for the secondary care specialty of radiology. We conducted a retrospective analysis of data from radiology applicants who also applied to UK GP specialty training or Core Medical Training. The psychometric properties of the two selection tests, a clinical problem solving (CPS) test and situational judgement test (SJT), were analysed to evaluate their reliability. Predictive validity of the tests was analysed by comparing them with the current radiology selection assessments, and the licensure examination results taken after the first stage of training (Fellowship of the Royal College of Radiologists (FRCR) Part 1). The internal reliability of the two selection tests in the radiology applicant sample was good (α ≥ 0.80). The average correlation with radiology shortlisting selection scores was r = 0.26 for the CPS (with p < 0.05 in 5 of 11 shortlisting centres), r = 0.15 for the SJT (with p < 0.05 in 2 of 11 shortlisting centres) and r = 0.25 (with p < 0.05 in 5 of 11 shortlisting centres) for the two tests combined. The CPS test scores significantly correlated with performance in both components of the FRCR Part 1 examinations (r = 0.5 anatomy; r = 0.4 physics; p < 0.05 for both). The SJT did not correlate with either component of the examination. The current CPS test may be an appropriate selection method for shortlisting in radiology but would benefit from further refinement for use in radiology to ensure that the test specification is relevant. The evidence on whether the SJT may be appropriate for shortlisting in radiology is limited. However, these results may be expected to some extent since the SJT is designed to measure non-academic attributes. Further validation work (e.g. with non-academic outcome variables) is required to evaluate whether an SJT will add value in recruitment for radiology specialty training and will further inform construct validity of SJTs as a selection methodology.

Identifying critical success factors for designing selection processes into postgraduate specialty training: the case of UK general practice.

PubMed

Plint, Simon; Patterson, Fiona

2010-06-01

The UK national recruitment process into general practice training has been developed over several years, with incremental introduction of stages which have been piloted and validated. Previously independent processes, which encouraged multiple applications and produced inconsistent outcomes, have been replaced by a robust national process which has high reliability and predictive validity, and is perceived to be fair by candidates and allocates applicants equitably across the country. Best selection practice involves a job analysis which identifies required competencies, then designs reliable assessment methods to measure them, and over the long term ensures that the process has predictive validity against future performance. The general practitioner recruitment process introduced machine markable short listing assessments for the first time in the UK postgraduate recruitment context, and also adopted selection centre workplace simulations. The key success factors have been identified as corporate commitment to the goal of a national process, with gradual convergence maintaining locus of control rather than the imposition of change without perceived legitimate authority.

The application of neural networks to the SSME startup transient

NASA Technical Reports Server (NTRS)

Meyer, Claudia M.; Maul, William A.

1991-01-01

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Validating a Culturally-Sensitive Social Competence Training Programme for Adolescents with ASD in a Chinese Context: An Initial Investigation

ERIC Educational Resources Information Center

Chan, Raymond Won Shing; Leung, Cecilia Nga Wing; Ng, Denise Ching Yiu; Yau, Sania Sau Wai

2018-01-01

Previous studies on social skills training on ASD were done almost exclusively in the West with children as the main subjects. Demonstrations of the applicability of social interventions in different cultures and age groups are warranted. The current study outlined the development and preliminary evaluation of a CBT-context-based social competence…

A frequency-domain approach to improve ANNs generalization quality via proper initialization.

PubMed

Chaari, Majdi; Fekih, Afef; Seibi, Abdennour C; Hmida, Jalel Ben

2018-08-01

The ability to train a network without memorizing the input/output data, thereby allowing a good predictive performance when applied to unseen data, is paramount in ANN applications. In this paper, we propose a frequency-domain approach to evaluate the network initialization in terms of quality of training, i.e., generalization capabilities. As an alternative to the conventional time-domain methods, the proposed approach eliminates the approximate nature of network validation using an excess of unseen data. The benefits of the proposed approach are demonstrated using two numerical examples, where two trained networks performed similarly on the training and the validation data sets, yet they revealed a significant difference in prediction accuracy when tested using a different data set. This observation is of utmost importance in modeling applications requiring a high degree of accuracy. The efficiency of the proposed approach is further demonstrated on a real-world problem, where unlike other initialization methods, a more conclusive assessment of generalization is achieved. On the practical front, subtle methodological and implementational facets are addressed to ensure reproducibility and pinpoint the limitations of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validity of the Medical College Admission Test for Predicting MD-PhD Student Outcomes

ERIC Educational Resources Information Center

Bills, James L.; VanHouten, Jacob; Grundy, Michelle M.; Chalkley, Roger; Dermody, Terence S.

2016-01-01

The Medical College Admission Test (MCAT) is a quantitative metric used by MD and MD-PhD programs to evaluate applicants for admission. This study assessed the validity of the MCAT in predicting training performance measures and career outcomes for MD-PhD students at a single institution. The study population consisted of 153 graduates of the…

PONS2train: tool for testing the MLP architecture and local traning methods for runoff forecast

NASA Astrophysics Data System (ADS)

Maca, P.; Pavlasek, J.; Pech, P.

2012-04-01

The purpose of presented poster is to introduce the PONS2train developed for runoff prediction via multilayer perceptron - MLP. The software application enables the implementation of 12 different MLP's transfer functions, comparison of 9 local training algorithms and finally the evaluation the MLP performance via 17 selected model evaluation metrics. The PONS2train software is written in C++ programing language. Its implementation consists of 4 classes. The NEURAL_NET and NEURON classes implement the MLP, the CRITERIA class estimates model evaluation metrics and for model performance evaluation via testing and validation datasets. The DATA_PATTERN class prepares the validation, testing and calibration datasets. The software application uses the LAPACK, BLAS and ARMADILLO C++ linear algebra libraries. The PONS2train implements the first order local optimization algorithms: standard on-line and batch back-propagation with learning rate combined with momentum and its variants with the regularization term, Rprop and standard batch back-propagation with variable momentum and learning rate. The second order local training algorithms represents: the Levenberg-Marquardt algorithm with and without regularization and four variants of scaled conjugate gradients. The other important PONS2train features are: the multi-run, the weight saturation control, early stopping of trainings, and the MLP weights analysis. The weights initialization is done via two different methods: random sampling from uniform distribution on open interval or Nguyen Widrow method. The data patterns can be transformed via linear and nonlinear transformation. The runoff forecast case study focuses on PONS2train implementation and shows the different aspects of the MLP training, the MLP architecture estimation, the neural network weights analysis and model uncertainty estimation.

Simulation-driven machine learning: Bearing fault classification

NASA Astrophysics Data System (ADS)

Sobie, Cameron; Freitas, Carina; Nicolai, Mike

2018-01-01

Increasing the accuracy of mechanical fault detection has the potential to improve system safety and economic performance by minimizing scheduled maintenance and the probability of unexpected system failure. Advances in computational performance have enabled the application of machine learning algorithms across numerous applications including condition monitoring and failure detection. Past applications of machine learning to physical failure have relied explicitly on historical data, which limits the feasibility of this approach to in-service components with extended service histories. Furthermore, recorded failure data is often only valid for the specific circumstances and components for which it was collected. This work directly addresses these challenges for roller bearings with race faults by generating training data using information gained from high resolution simulations of roller bearing dynamics, which is used to train machine learning algorithms that are then validated against four experimental datasets. Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping (DTW) to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

Process Improvements in Training Device Acceptance Testing: A Study in Total Quality Management

DTIC Science & Technology

1990-12-12

Quality Management , a small group of Government and industry specialists examined the existing training device acceptance test process for potential improvements. The agreed-to mission of the Air Force/Industry partnership was to continuously identify and promote implementable approaches to minimize the cost and time required for acceptance testing while ensuring that validated performance supports the user training requirements. Application of a Total Quality process improvement model focused on the customers and their requirements, analyzed how work was accomplished, and

Rank Order Entropy: why one metric is not enough

PubMed Central

McLellan, Margaret R.; Ryan, M. Dominic; Breneman, Curt M.

2011-01-01

The use of Quantitative Structure-Activity Relationship models to address problems in drug discovery has a mixed history, generally resulting from the mis-application of QSAR models that were either poorly constructed or used outside of their domains of applicability. This situation has motivated the development of a variety of model performance metrics (r2, PRESS r2, F-tests, etc) designed to increase user confidence in the validity of QSAR predictions. In a typical workflow scenario, QSAR models are created and validated on training sets of molecules using metrics such as Leave-One-Out or many-fold cross-validation methods that attempt to assess their internal consistency. However, few current validation methods are designed to directly address the stability of QSAR predictions in response to changes in the information content of the training set. Since the main purpose of QSAR is to quickly and accurately estimate a property of interest for an untested set of molecules, it makes sense to have a means at hand to correctly set user expectations of model performance. In fact, the numerical value of a molecular prediction is often less important to the end user than knowing the rank order of that set of molecules according to their predicted endpoint values. Consequently, a means for characterizing the stability of predicted rank order is an important component of predictive QSAR. Unfortunately, none of the many validation metrics currently available directly measure the stability of rank order prediction, making the development of an additional metric that can quantify model stability a high priority. To address this need, this work examines the stabilities of QSAR rank order models created from representative data sets, descriptor sets, and modeling methods that were then assessed using Kendall Tau as a rank order metric, upon which the Shannon Entropy was evaluated as a means of quantifying rank-order stability. Random removal of data from the training set, also known as Data Truncation Analysis (DTA), was used as a means for systematically reducing the information content of each training set while examining both rank order performance and rank order stability in the face of training set data loss. The premise for DTA ROE model evaluation is that the response of a model to incremental loss of training information will be indicative of the quality and sufficiency of its training set, learning method, and descriptor types to cover a particular domain of applicability. This process is termed a “rank order entropy” evaluation, or ROE. By analogy with information theory, an unstable rank order model displays a high level of implicit entropy, while a QSAR rank order model which remains nearly unchanged during training set reductions would show low entropy. In this work, the ROE metric was applied to 71 data sets of different sizes, and was found to reveal more information about the behavior of the models than traditional metrics alone. Stable, or consistently performing models, did not necessarily predict rank order well. Models that performed well in rank order did not necessarily perform well in traditional metrics. In the end, it was shown that ROE metrics suggested that some QSAR models that are typically used should be discarded. ROE evaluation helps to discern which combinations of data set, descriptor set, and modeling methods lead to usable models in prioritization schemes, and provides confidence in the use of a particular model within a specific domain of applicability. PMID:21875058

Using athletic training clinical education standards in radiography.

PubMed

Giordano, Shelley; Harris, Katherine

2012-01-01

The selection of clinical education sites for radiography students is based on availability, access to radiographic examinations, and appropriate student-to-technologist ratio. Radiography program directors are not required to evaluate sites based on their educational validity (eg, the clinical instructor's knowledge of basic teaching and learning principles, how well the site communicates with the program, or the clinical instructor's involvement in professional organizations). The purpose of this study was to determine if a set of 12 clinical education standards used in athletic training would be applicable and beneficial to radiography program directors when selecting clinical sites for students. A survey concerning the applicability of the athletic training standards to radiography site selection was completed by 270 directors of radiography programs accredited by the Joint Review Committee on Education in Radiologic Technology. The survey results indicated the athletic training clinical education standards were considered applicable to the selection of clinical sites for radiography students and would be beneficial to radiography program directors when selecting sites.

A neural networks application for the study of the influence of transport conditions on the working performance

NASA Astrophysics Data System (ADS)

Anghel, D.-C.; Ene, A.; Ştirbu, C.; Sicoe, G.

2017-10-01

This paper presents a study about the factors that influence the working performances of workers in the automotive industry. These factors regard mainly the transportations conditions, taking into account the fact that a large number of workers live in places that are far away of the enterprise. The quantitative data obtained from this study will be generalized by using a neural network, software simulated. The neural network is able to estimate the performance of workers even for the combinations of input factors that had been not recorded by the study. The experimental data obtained from the study will be divided in two classes. The first class that contains approximately 80% of data will be used by the Java software for the training of the neural network. The weights resulted from the training process will be saved in a text file. The other class that contains the rest of the 20% of experimental data will be used to validate the neural network. The training and the validation of the networks are performed in a Java software (TrainAndValidate java class). We designed another java class, Test.java that will be used with new input data, for new situations. The experimental data collected from the study. The software that simulated the neural network. The software that estimates the working performance, when new situations are met. This application is useful for human resources department of an enterprise. The output results are not quantitative. They are qualitative (from low performance to high performance, divided in five classes).

[Simulation training in surgical education - application of virtual reality laparoscopic simulators in a surgical skills course].

PubMed

Lehmann, K S; Gröne, J; Lauscher, J C; Ritz, J-P; Holmer, C; Pohlen, U; Buhr, H-J

2012-04-01

Training and simulation are gaining importance in surgical education. Today, virtual reality surgery simulators provide sophisticated laparoscopic training scenarios and offer detailed assessment methods. This also makes simulators interesting for the application in surgical skills courses. The aim of the current study was to assess the suitability of a virtual surgery simulator for training and assessment in an established surgical training course. The study was conducted during the annual "Practical Course for Visceral Surgery" (Warnemuende, Germany). 36 of 108 course participants were assigned at random for the study. Training was conducted in 15 sessions over 5 days with 4 identical virtual surgery simulators (LapSim) and 2 standardised training tasks. The simulator measured 16 individual parameters and calculated 2 scores. Questionnaires were used to assess the test persons' laparoscopic experience, their training situation and the acceptance of the simulator training. Data were analysed with non-parametric tests. A subgroup analysis for laparoscopic experience was conducted in order to assess the simulator's construct validity and assessment capabilities. Median age was 32 (27 - 41) years; median professional experience was 3 (1 - 11) years. Typical laparoscopic learning curves with initial significant improvements and a subsequent plateau phase were measured over 5 days. The individual training sessions exhibited a rhythmic variability in the training results. A shorter night's sleep led to a marked drop in performance. The participants' different experience levels could clearly be discriminated ( ≤ 20 vs. > 20 laparoscopic operations; p ≤ 0.001). The questionnaire showed that the majority of the participants had limited training opportunities in their hospitals. The simulator training was very well accepted. However, the participants severely misjudged the real costs of the simulators that were used. The learning curve on the simulator was successfully mastered during the course. Construct validity could be demonstrated within the course setting. The simulator's assessment system can be of value for the assessment of laparoscopic training performance within surgical skills courses. Acceptance of the simulator training is high. However, simulators are currently too expensive to be used within a large training course. © Georg Thieme Verlag KG Stuttgart · New York.

Development and validation of trauma surgical skills metrics: Preliminary assessment of performance after training.

PubMed

Shackelford, Stacy; Garofalo, Evan; Shalin, Valerie; Pugh, Kristy; Chen, Hegang; Pasley, Jason; Sarani, Babak; Henry, Sharon; Bowyer, Mark; Mackenzie, Colin F

2015-07-01

Maintaining trauma-specific surgical skills is an ongoing challenge for surgical training programs. An objective assessment of surgical skills is needed. We hypothesized that a validated surgical performance assessment tool could detect differences following a training intervention. We developed surgical performance assessment metrics based on discussion with expert trauma surgeons, video review of 10 experts and 10 novice surgeons performing three vascular exposure procedures and lower extremity fasciotomy on cadavers, and validated the metrics with interrater reliability testing by five reviewers blinded to level of expertise and a consensus conference. We tested these performance metrics in 12 surgical residents (Year 3-7) before and 2 weeks after vascular exposure skills training in the Advanced Surgical Skills for Exposure in Trauma (ASSET) course. Performance was assessed in three areas as follows: knowledge (anatomic, management), procedure steps, and technical skills. Time to completion of procedures was recorded, and these metrics were combined into a single performance score, the Trauma Readiness Index (TRI). Wilcoxon matched-pairs signed-ranks test compared pretraining/posttraining effects. Mean time to complete procedures decreased by 4.3 minutes (from 13.4 minutes to 9.1 minutes). The performance component most improved by the 1-day skills training was procedure steps, completion of which increased by 21%. Technical skill scores improved by 12%. Overall knowledge improved by 3%, with 18% improvement in anatomic knowledge. TRI increased significantly from 50% to 64% with ASSET training. Interrater reliability of the surgical performance assessment metrics was validated with single intraclass correlation coefficient of 0.7 to 0.98. A trauma-relevant surgical performance assessment detected improvements in specific procedure steps and anatomic knowledge taught during a 1-day course, quantified by the TRI. ASSET training reduced time to complete vascular control by one third. Future applications include assessing specific skills in a larger surgeon cohort, assessing military surgical readiness, and quantifying skill degradation with time since training.

Application of the Repetitions in Reserve-Based Rating of Perceived Exertion Scale for Resistance Training

PubMed Central

Cronin, John; Storey, Adam; Zourdos, Michael C.

2016-01-01

ABSTRACT RATINGS OF PERCEIVED EXERTION ARE A VALID METHOD OF ESTIMATING THE INTENSITY OF A RESISTANCE TRAINING EXERCISE OR SESSION. SCORES ARE GIVEN AFTER COMPLETION OF AN EXERCISE OR TRAINING SESSION FOR THE PURPOSES OF ATHLETE MONITORING. HOWEVER, A NEWLY DEVELOPED SCALE BASED ON HOW MANY REPETITIONS ARE REMAINING AT THE COMPLETION OF A SET MAY BE A MORE PRECISE TOOL. THIS APPROACH ADJUSTS LOADS AUTOMATICALLY TO MATCH ATHLETE CAPABILITIES ON A SET-TO-SET BASIS AND MAY MORE ACCURATELY GAUGE INTENSITY AT NEAR-LIMIT LOADS. THIS ARTICLE OUTLINES HOW TO INCORPORATE THIS NOVEL SCALE INTO A TRAINING PLAN. PMID:27531969

Can a virtual reality cognitive training application fulfill a dual role? Using the virtual supermarket cognitive training application as a screening tool for mild cognitive impairment.

PubMed

Zygouris, Stelios; Giakoumis, Dimitrios; Votis, Konstantinos; Doumpoulakis, Stefanos; Ntovas, Konstantinos; Segkouli, Sofia; Karagiannidis, Charalampos; Tzovaras, Dimitrios; Tsolaki, Magda

2015-01-01

Recent research advocates the potential of virtual reality (VR) applications in assessing cognitive functions highlighting the possibility of using a VR application for mild cognitive impairment (MCI) screening. The aim of this study is to investigate whether a VR cognitive training application, the virtual supermarket (VSM), can be used as a screening tool for MCI. Two groups, one of healthy older adults (n = 21) and one of MCI patients (n = 34), were recruited from day centers for cognitive disorders and administered the VSM and a neuropsychological test battery. The performance of the two groups in the VSM was compared and correlated with performance in established neuropsychological tests. At the same time, the effectiveness of a combination of traditional neuropsychological tests and the VSM was examined. VSM displayed a correct classification rate (CCR) of 87.30% when differentiating between MCI patients and healthy older adults, while it was unable to differentiate between MCI subtypes. At the same time, the VSM correlates with various established neuropsychological tests. A limited number of tests were able to improve the CCR of the VSM when combined with the VSM for screening purposes. VSM appears to be a valid method of screening for MCI in an older adult population though it cannot be used for MCI subtype assessment. VSM's concurrent validity is supported by the large number of correlations between the VSM and established tests. It is considered a robust test on its own as the inclusion of other tests failed to improve its CCR significantly.

49 CFR 1522.119 - Training.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., DEPARTMENT OF HOMELAND SECURITY SECURITY RULES FOR ALL MODES OF TRANSPORTATION TSA-APPROVED VALIDATION FIRMS AND VALIDATORS TSA-Approved Validation Firms and Validators for the Certified Cargo Screening Program § 1522.119 Training. (a) Initial training. The validation firm must ensure that its validators and...

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

NASA Technical Reports Server (NTRS)

Gupta, Pramod; Loparo, Kenneth; Mackall, Dale; Schumann, Johann; Soares, Fola

2004-01-01

Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.

Predictive validity of a selection centre testing non-technical skills for recruitment to training in anaesthesia.

PubMed

Gale, T C E; Roberts, M J; Sice, P J; Langton, J A; Patterson, F C; Carr, A S; Anderson, I R; Lam, W H; Davies, P R F

2010-11-01

Assessment centres are an accepted method of recruitment in industry and are gaining popularity within medicine. We describe the development and validation of a selection centre for recruitment to speciality training in anaesthesia based on an assessment centre model incorporating the rating of candidate's non-technical skills. Expert consensus identified non-technical skills suitable for assessment at the point of selection. Four stations-structured interview, portfolio review, presentation, and simulation-were developed, the latter two being realistic scenarios of work-related tasks. Evaluation of the selection centre focused on applicant and assessor feedback ratings, inter-rater agreement, and internal consistency reliability coefficients. Predictive validity was sought via correlations of selection centre scores with subsequent workplace-based ratings of appointed trainees. Two hundred and twenty-four candidates were assessed over two consecutive annual recruitment rounds; 68 were appointed and followed up during training. Candidates and assessors demonstrated strong approval of the selection centre with more than 70% of ratings 'good' or 'excellent'. Mean inter-rater agreement coefficients ranged from 0.62 to 0.77 and internal consistency reliability of the selection centre score was high (Cronbach's α=0.88-0.91). The overall selection centre score was a good predictor of workplace performance during the first year of appointment. An assessment centre model based on the rating of non-technical skills can produce a reliable and valid selection tool for recruitment to speciality training in anaesthesia. Early results on predictive validity are encouraging and justify further development and evaluation.

Development of a Deep Learning Algorithm for Automatic Diagnosis of Diabetic Retinopathy.

PubMed

Raju, Manoj; Pagidimarri, Venkatesh; Barreto, Ryan; Kadam, Amrit; Kasivajjala, Vamsichandra; Aswath, Arun

2017-01-01

This paper mainly focuses on the deep learning application in classifying the stage of diabetic retinopathy and detecting the laterality of the eye using funduscopic images. Diabetic retinopathy is a chronic, progressive, sight-threatening disease of the retinal blood vessels. Ophthalmologists diagnose diabetic retinopathy through early funduscopic screening. Normally, there is a time delay in reporting and intervention, apart from the financial cost and risk of blindness associated with it. Using a convolutional neural network based approach for automatic diagnosis of diabetic retinopathy, we trained the prediction network on the publicly available Kaggle dataset. Approximately 35,000 images were used to train the network, which observed a sensitivity of 80.28% and a specificity of 92.29% on the validation dataset of ~53,000 images. Using 8,810 images, the network was trained for detecting the laterality of the eye and observed an accuracy of 93.28% on the validation set of 8,816 images.

The Implementation and Validation of a Virtual Environment for Training Powered Wheelchair Manoeuvres.

PubMed

John, Nigel W; Pop, Serban R; Day, Thomas W; Ritsos, Panagiotis D; Headleand, Christopher J

2018-05-01

Navigating a powered wheelchair and avoiding collisions is often a daunting task for new wheelchair users. It takes time and practice to gain the coordination needed to become a competent driver and this can be even more of a challenge for someone with a disability. We present a cost-effective virtual reality (VR) application that takes advantage of consumer level VR hardware. The system can be easily deployed in an assessment centre or for home use, and does not depend on a specialized high-end virtual environment such as a Powerwall or CAVE. This paper reviews previous work that has used virtual environments technology for training tasks, particularly wheelchair simulation. We then describe the implementation of our own system and the first validation study carried out using thirty three able bodied volunteers. The study results indicate that at a significance level of 5 percent then there is an improvement in driving skills from the use of our VR system. We thus have the potential to develop the competency of a wheelchair user whilst avoiding the risks inherent to training in the real world. However, the occurrence of cybersickness is a particular problem in this application that will need to be addressed.

[Computerized system validation of clinical researches].

PubMed

Yan, Charles; Chen, Feng; Xia, Jia-lai; Zheng, Qing-shan; Liu, Daniel

2015-11-01

Validation is a documented process that provides a high degree of assurance. The computer system does exactly and consistently what it is designed to do in a controlled manner throughout the life. The validation process begins with the system proposal/requirements definition, and continues application and maintenance until system retirement and retention of the e-records based on regulatory rules. The objective to do so is to clearly specify that each application of information technology fulfills its purpose. The computer system validation (CSV) is essential in clinical studies according to the GCP standard, meeting product's pre-determined attributes of the specifications, quality, safety and traceability. This paper describes how to perform the validation process and determine relevant stakeholders within an organization in the light of validation SOPs. Although a specific accountability in the implementation of the validation process might be outsourced, the ultimate responsibility of the CSV remains on the shoulder of the business process owner-sponsor. In order to show that the compliance of the system validation has been properly attained, it is essential to set up comprehensive validation procedures and maintain adequate documentations as well as training records. Quality of the system validation should be controlled using both QC and QA means.

CASPer, an online pre-interview screen for personal/professional characteristics: prediction of national licensure scores.

PubMed

Dore, Kelly L; Reiter, Harold I; Kreuger, Sharyn; Norman, Geoffrey R

2017-05-01

Typically, only a minority of applicants to health professional training are invited to interview. However, pre-interview measures of cognitive skills predict for national licensure scores (Gauer et al. in Med Educ Online 21 2016) and subsequently licensure scores predict for performance in practice (Tamblyn et al. in JAMA 288(23): 3019-3026, 2002; Tamblyn et al. in JAMA 298(9):993-1001, 2007). Assessment of personal and professional characteristics, with the same psychometric rigour of measures of cognitive abilities, are needed upstream in the selection to health profession training programs. To fill that need, Computer-based Assessment for Sampling Personal characteristics (CASPer)-an on-line, video-based screening test-was created. In this paper, we examine the correlation between CASPer and Canadian national licensure examination outcomes in 109 doctors who took CASPer at the time of selection to medical school. Specifically, CASPer scores were correlated against performance on cognitive and 'non-cognitive' subsections of both the Medical Council of Canada Qualifying Examination (MCCQE) Parts I (end of medical school) and Part II (18 months into specialty training). Unlike most national licensure exams, MCCQE has specific subcomponents examining personal/professional qualities, providing a unique opportunity for comparison. The results demonstrated moderate predictive validity of CASPer to national licensure outcomes of personal/professional characteristics three to six years after admission to medical school. These types of disattenuated correlations (r = 0.3-0.5) are not otherwise predicted by traditional screening measures. These data support the ability of a computer-based strategy to screen applicants in a feasible, reliable test, which has now demonstrated predictive validity, lending evidence of its validation for medical school applicant selection.

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

2017-12-01

Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction.

PubMed

Cheng, Hao; Garrick, Dorian J; Fernando, Rohan L

2017-01-01

A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify the predictive ability of a statistical model. Naive application of Leave-one-out cross validation is computationally intensive because the training and validation analyses need to be repeated n times, once for each observation. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis. Efficient Leave-one-out cross validation strategies is 786 times faster than the naive application for a simulated dataset with 1,000 observations and 10,000 markers and 99 times faster with 1,000 observations and 100 markers. These efficiencies relative to the naive approach using the same model will increase with increases in the number of observations. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis.

Studying distributed cognition of simulation-based team training with DiCoT.

PubMed

Rybing, Jonas; Nilsson, Heléne; Jonson, Carl-Oscar; Bang, Magnus

2016-03-01

Health care organizations employ simulation-based team training (SBTT) to improve skill, communication and coordination in a broad range of critical care contexts. Quantitative approaches, such as team performance measurements, are predominantly used to measure SBTTs effectiveness. However, a practical evaluation method that examines how this approach supports cognition and teamwork is missing. We have applied Distributed Cognition for Teamwork (DiCoT), a method for analysing cognition and collaboration aspects of work settings, with the purpose of assessing the methodology's usefulness for evaluating SBTTs. In a case study, we observed and analysed four Emergo Train System® simulation exercises where medical professionals trained emergency response routines. The study suggests that DiCoT is an applicable and learnable tool for determining key distributed cognition attributes of SBTTs that are of importance for the simulation validity of training environments. Moreover, we discuss and exemplify how DiCoT supports design of SBTTs with a focus on transfer and validity characteristics. Practitioner Summary: In this study, we have evaluated a method to assess simulation-based team training environments from a cognitive ergonomics perspective. Using a case study, we analysed Distributed Cognition for Teamwork (DiCoT) by applying it to the Emergo Train System®. We conclude that DiCoT is useful for SBTT evaluation and simulator (re)design.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research.

PubMed

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-Etriby, Sherif

2016-03-11

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers-that we proposed earlier-improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research

PubMed Central

Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-etriby, Sherif

2016-01-01

Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction. PMID:26978368

Communication guidelines as a learning tool: an exploration of user preferences in general practice.

PubMed

Veldhuijzen, Wemke; Ram, Paul M; van der Weijden, Trudy; van der Vleuten, Cees P M

2013-02-01

To explore characteristics of written communication guidelines that enhance the success of training aimed at the application of the recommendations in the guidelines. Seven mixed focus groups were held consisting of communication skill teachers and communication skill learners and three groups with only learners. Analysis was done in line with principles of grounded theory. Five key attributes of guidelines for communication skill training were identified: complexity, level of detail, format and organization, type of information, and trustworthiness/validity. The desired use of these attributes is related to specific educational purposes and learners' expertise. The low complexity of current communication guidelines is appreciated, but seems ad odds with the wish for more valid communication guidelines. Which guideline characteristics are preferred by users depends on the expertise of the learners and the educational purpose of the guideline. Communication guidelines can be improved by modifying the key attributes in line with specific educational functions and learner expertise. For example: the communication guidelines used in GP training in the Netherlands, seem to offer an oversimplified model of doctor patient communication. This model may be suited for undergraduate learning, but does not meet the validity demands of physicians in training. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The validation of a swimming turn wall-contact-time measurement system: a touchpad application reliability study.

PubMed

Brackley, Victoria; Ball, Kevin; Tor, Elaine

2018-05-12

The effectiveness of the swimming turn is highly influential to overall performance in competitive swimming. The push-off or wall contact, within the turn phase, is directly involved in determining the speed the swimmer leaves the wall. Therefore, it is paramount to develop reliable methods to measure the wall-contact-time during the turn phase for training and research purposes. The aim of this study was to determine the concurrent validity and reliability of the Pool Pad App to measure wall-contact-time during the freestyle and backstroke tumble turn. The wall-contact-times of nine elite and sub-elite participants were recorded during their regular training sessions. Concurrent validity statistics included the standardised typical error estimate, linear analysis and effect sizes while the intraclass correlating coefficient (ICC) was used for the reliability statistics. The standardised typical error estimate resulted in a moderate Cohen's d effect size with an R 2 value of 0.80 and the ICC between the Pool Pad and 2D video footage was 0.89. Despite these measurement differences, the results from this concurrent validity and reliability analyses demonstrated that the Pool Pad is suitable for measuring wall-contact-time during the freestyle and backstroke tumble turn within a training environment.

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable

PubMed Central

Korjus, Kristjan; Hebart, Martin N.; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier’s generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term “Cross-validation and cross-testing” improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do. PMID:27564393

An Efficient Data Partitioning to Improve Classification Performance While Keeping Parameters Interpretable.

PubMed

Korjus, Kristjan; Hebart, Martin N; Vicente, Raul

2016-01-01

Supervised machine learning methods typically require splitting data into multiple chunks for training, validating, and finally testing classifiers. For finding the best parameters of a classifier, training and validation are usually carried out with cross-validation. This is followed by application of the classifier with optimized parameters to a separate test set for estimating the classifier's generalization performance. With limited data, this separation of test data creates a difficult trade-off between having more statistical power in estimating generalization performance versus choosing better parameters and fitting a better model. We propose a novel approach that we term "Cross-validation and cross-testing" improving this trade-off by re-using test data without biasing classifier performance. The novel approach is validated using simulated data and electrophysiological recordings in humans and rodents. The results demonstrate that the approach has a higher probability of discovering significant results than the standard approach of cross-validation and testing, while maintaining the nominal alpha level. In contrast to nested cross-validation, which is maximally efficient in re-using data, the proposed approach additionally maintains the interpretability of individual parameters. Taken together, we suggest an addition to currently used machine learning approaches which may be particularly useful in cases where model weights do not require interpretation, but parameters do.

Cost-effectiveness of electronic training in domestic violence risk assessment: ODARA 101.

PubMed

Hilton, N Zoe; Ham, Elke

2015-03-01

The need for domestic violence training has increased with the development of evidence-based risk assessment tools, which must be scored correctly for valid application. Emerging research indicates that training in domestic violence risk assessment can increase scoring accuracy, but despite the increasing popularity of electronic training, it is not yet known whether it can be an effective method of risk assessment training. In the present study, 87 assessors from various professions had training in the Ontario Domestic Assault Risk Assessment either face-to-face or using an electronic training program. The two conditions were equally effective, as measured by performance on a post-training skill acquisition test. Completion rates were 100% for face-to-face and 86% for electronic training, an improvement over a previously evaluated manual-only condition. The estimated per-trainee cost of electronic training was one third that of face-to-face training and expected to decrease. More rigorous evaluations of electronic training for risk assessment are recommended. © The Author(s) 2014.

Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

NASA Astrophysics Data System (ADS)

Wang, M.; Hu, N. Q.; Qin, G. J.

2011-07-01

In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

Application of the "see one, do one, teach one" concept in surgical training.

PubMed

Kotsis, Sandra V; Chung, Kevin C

2013-05-01

The traditional method of teaching in surgery is known as "see one, do one, teach one." However, many have argued that this method is no longer applicable, mainly because of concerns for patient safety. The purpose of this article is to show that the basis of the traditional teaching method is still valid in surgical training if it is combined with various adult learning principles. The authors reviewed literature regarding the history of the formation of the surgical residency program, adult learning principles, mentoring, and medical simulation. The authors provide examples for how these learning techniques can be incorporated into a surgical resident training program. The surgical residency program created by Dr. William Halsted remained virtually unchanged until recently with reductions in resident work hours and changes to a competency-based training system. Such changes have reduced the teaching time between attending physicians and residents. Learning principles such as experience, observation, thinking, and action and deliberate practice can be used to train residents. Mentoring is also an important aspect in teaching surgical technique. The authors review the different types of simulators-standardized patients, virtual reality applications, and high-fidelity mannequin simulators-and the advantages and disadvantages of using them. The traditional teaching method of "see one, do one, teach one" in surgical residency programs is simple but still applicable. It needs to evolve with current changes in the medical system to adequately train surgical residents and also provide patients with safe, evidence-based care.

Simulation validation of the XV-15 tilt-rotor research aircraft

NASA Technical Reports Server (NTRS)

Ferguson, S. W.; Hanson, G. D.; Churchill, G. B.

1984-01-01

The results of a simulation validation program of the XV-15 tilt-rotor research aircraft are detailed, covering such simulation aspects as the mathematical model, visual system, motion system, cab aural system, cab control loader system, pilot perceptual fidelity, and generic tilt rotor applications. Simulation validation was performed for the hover, low-speed, and sideward flight modes, with consideration of the in-ground rotor effect. Several deficiencies of the mathematical model and the simulation systems were identified in the course of the simulation validation project, and some were corrected. It is noted that NASA's Vertical Motion Simulator used in the program is an excellent tool for tilt-rotor and rotorcraft design, development, and pilot training.

Business Administration Scale for Family Child Care, BAS

ERIC Educational Resources Information Center

Talan, Teri N.; Bloom, Paula Jorde

2009-01-01

The "BAS for Family Child Care" is the first valid and reliable tool for measuring and improving the overall quality of business and professional practices in family child care settings. It is applicable for multiple uses, including program self-improvement, technical assistance and monitoring, training, research and evaluation, and public…

Business Administration Scale for Family Child Care (BAS). Second Edition

ERIC Educational Resources Information Center

Talan, Teri N.; Bloom, Paula Jorde

2018-01-01

The "Business Administration Scale for Family Child Care" (BAS) is the first valid and reliable tool for measuring and improving the overall quality of business and professional practices in family child care settings. It is applicable for multiple uses, including program self-improvement, technical assistance and monitoring, training,…

Putting Writing Research into Practice: Applications for Teacher Professional Development

ERIC Educational Resources Information Center

Troia, Gary A., Ed.; Shankland, Rebecca K., Ed.; Heintz, Anne, Ed.

2010-01-01

What are the most effective methods for teaching writing across grade levels and student populations? What kind of training do teachers need to put research-validated methods into practice? This unique volume combines the latest writing research with clear-cut recommendations for designing high-quality professional development efforts. Prominent…

The predictive validity of a situational judgement test, a clinical problem solving test and the core medical training selection methods for performance in specialty training .

PubMed

Patterson, Fiona; Lopes, Safiatu; Harding, Stephen; Vaux, Emma; Berkin, Liz; Black, David

2017-02-01

The aim of this study was to follow up a sample of physicians who began core medical training (CMT) in 2009. This paper examines the long-term validity of CMT and GP selection methods in predicting performance in the Membership of Royal College of Physicians (MRCP(UK)) examinations. We performed a longitudinal study, examining the extent to which the GP and CMT selection methods (T1) predict performance in the MRCP(UK) examinations (T2). A total of 2,569 applicants from 2008-09 who completed CMT and GP selection methods were included in the study. Looking at MRCP(UK) part 1, part 2 written and PACES scores, both CMT and GP selection methods show evidence of predictive validity for the outcome variables, and hierarchical regressions show the GP methods add significant value to the CMT selection process. CMT selection methods predict performance in important outcomes and have good evidence of validity; the GP methods may have an additional role alongside the CMT selection methods. © Royal College of Physicians 2017. All rights reserved.

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

Robust feature extraction for rapid classification of damage in composites

NASA Astrophysics Data System (ADS)

Coelho, Clyde K.; Reynolds, Whitney; Chattopadhyay, Aditi

2009-03-01

The ability to detect anomalies in signals from sensors is imperative for structural health monitoring (SHM) applications. Many of the candidate algorithms for these applications either require a lot of training examples or are very computationally inefficient for large sample sizes. The damage detection framework presented in this paper uses a combination of Linear Discriminant Analysis (LDA) along with Support Vector Machines (SVM) to obtain a computationally efficient classification scheme for rapid damage state determination. LDA was used for feature extraction of damage signals from piezoelectric sensors on a composite plate and these features were used to train the SVM algorithm in parts, reducing the computational intensity associated with the quadratic optimization problem that needs to be solved during training. SVM classifiers were organized into a binary tree structure to speed up classification, which also reduces the total training time required. This framework was validated on composite plates that were impacted at various locations. The results show that the algorithm was able to correctly predict the different impact damage cases in composite laminates using less than 21 percent of the total available training data after data reduction.

Face, content, and construct validity of human placenta as a haptic training tool in neurointerventional surgery.

PubMed

Ribeiro de Oliveira, Marcelo Magaldi; Nicolato, Arthur; Santos, Marcilea; Godinho, Joao Victor; Brito, Rafael; Alvarenga, Alexandre; Martins, Ana Luiza Valle; Prosdocimi, André; Trivelato, Felipe Padovani; Sabbagh, Abdulrahman J; Reis, Augusto Barbosa; Maestro, Rolando Del

2016-05-01

OBJECT The development of neurointerventional treatments of central nervous system disorders has resulted in the need for adequate training environments for novice interventionalists. Virtual simulators offer anatomical definition but lack adequate tactile feedback. Animal models, which provide more lifelike training, require an appropriate infrastructure base. The authors describe a training model for neurointerventional procedures using the human placenta (HP), which affords haptic training with significantly fewer resource requirements, and discuss its validation. METHODS Twelve HPs were prepared for simulated endovascular procedures. Training exercises performed by interventional neuroradiologists and novice fellows were placental angiography, stent placement, aneurysm coiling, and intravascular liquid embolic agent injection. RESULTS The endovascular training exercises proposed can be easily reproduced in the HP. Face, content, and construct validity were assessed by 6 neurointerventional radiologists and 6 novice fellows in interventional radiology. CONCLUSIONS The use of HP provides an inexpensive training model for the training of neurointerventionalists. Preliminary validation results show that this simulation model has face and content validity and has demonstrated construct validity for the interventions assessed in this study.

Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging.

PubMed

Handsfield, Geoffrey G; Bolsterlee, Bart; Inouye, Joshua M; Herbert, Robert D; Besier, Thor F; Fernandez, Justin W

2017-12-01

Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference [Formula: see text] or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.

System diagnostic builder

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Burke, Roger

1992-01-01

The System Diagnostic Builder (SDB) is an automated software verification and validation tool using state-of-the-art Artificial Intelligence (AI) technologies. The SDB is used extensively by project BURKE at NASA-JSC as one component of a software re-engineering toolkit. The SDB is applicable to any government or commercial organization which performs verification and validation tasks. The SDB has an X-window interface, which allows the user to 'train' a set of rules for use in a rule-based evaluator. The interface has a window that allows the user to plot up to five data parameters (attributes) at a time. Using these plots and a mouse, the user can identify and classify a particular behavior of the subject software. Once the user has identified the general behavior patterns of the software, he can train a set of rules to represent his knowledge of that behavior. The training process builds rules and fuzzy sets to use in the evaluator. The fuzzy sets classify those data points not clearly identified as a particular classification. Once an initial set of rules is trained, each additional data set given to the SDB will be used by a machine learning mechanism to refine the rules and fuzzy sets. This is a passive process and, therefore, it does not require any additional operator time. The evaluation component of the SDB can be used to validate a single software system using some number of different data sets, such as a simulator. Moreover, it can be used to validate software systems which have been re-engineered from one language and design methodology to a totally new implementation.

Securely Partitioning Spacecraft Computing Resources: Validation of a Separation Kernel

NASA Astrophysics Data System (ADS)

Bremer, Leon; Schreutelkamp, Erwin

2011-08-01

The F-35 Lightning II, also known as the Joint Strike Fighter, will be the first operational fighter aircraft equipped with an operational MultiShip Embedded Training capability. This onboard training system allows teams of fighter pilots to jointly operate their F-35 in flight against virtual threats, avoiding the need for real adversary air threats and surface threat systems in their training. The European Real-time Operations Simulator (EuroSim) framework is well known in the space domain, particularly in support of engineering and test phases of space system development. In the MultiShip Embedded Training project, EuroSim is not only the essential tool for development and verification throughout the project but is also the engine of the final embedded simulator on board of the F-35 aircraft. The novel ways in which EuroSim is applied in the project in relation to distributed simulation problems, team collaboration, tool chains and embedded systems can benefit many projects and applications. The paper describes the application of EuroSim as the simulation engine of the F-35 Embedded Training solution, the extensions to the EuroSim product that enable this application, and its usage in development and verification of the whole project as carried out at the sites of Dutch Space and the National Aerospace Laboratory (NLR).

The validity and reliability of script concordance test in otolaryngology residency training.

PubMed

Iravani, Kamyar; Amini, Mitra; Doostkam, Aida; Dehbozorgian, Mahnaz

2016-04-01

The script concordance test (SCT) is one the best tools used to evaluate clinical reasoning in ill-defined clinical situations. The aim of this study was to demonstrate SCT application in otolaryngology residency training. A 20 item otolaryngology SCT containing 60 questions was administered to 26 otolaryngology residents. The test was prepared by two otolaryngologists familiar to medical education. These questions have been validated by otolaryngology experts. The panel consisted of 9 academic staff in the field of otolaryngology. Pearson correlation test was used to assess the reliability of the test. The obtained mean scores were 68.4±5.8 (out of 100) for residents and 78.2±6.4(out of 100) for experts. There was a significant difference between the two scores (p<0.005). Cronbach's alpha value was 0.80. The SCT is a reliable tool to evaluate clinical reasoning in otolaryngology residents. It should be included in otolaryngology residency training.

Use of Multivariate Techniques to Validate and Improve the Current USAF Pilot Candidate Selection Model

DTIC Science & Technology

2003-03-01

organizations . Reducing attrition rates through optimal selection decisions can “reduce training cost, improve job performance, and enhance...capturing the weights for use in the SNR method is not straightforward. A special VBA application had to be written to capture and organize the network...before the VBA application can be used. Appendix D provides the VBA code used to import and organize the network weights and input standardization

Integrating Genetic, Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

PubMed Central

Mas, Sergi; Gassó, Patricia; Morer, Astrid; Calvo, Anna; Bargalló, Nuria; Lafuente, Amalia; Lázaro, Luisa

2016-01-01

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder. PMID:27093171

Application of artificial neural networks to establish a predictive mortality risk model in children admitted to a paediatric intensive care unit.

PubMed

Chan, C H; Chan, E Y; Ng, D K; Chow, P Y; Kwok, K L

2006-11-01

Paediatric risk of mortality and paediatric index of mortality (PIM) are the commonly-used mortality prediction models (MPM) in children admitted to paediatric intensive care unit (PICU). The current study was undertaken to develop a better MPM using artificial neural network, a domain of artificial intelligence. The purpose of this retrospective case series was to compare an artificial neural network (ANN) model and PIM with the observed mortality in a cohort of patients admitted to a five-bed PICU in a Hong Kong non-teaching general hospital. The patients were under the age of 17 years and admitted to our PICU from April 2001 to December 2004. Data were collected from each patient admitted to our PICU. All data were randomly allocated to either the training or validation set. The data from the training set were used to construct a series of ANN models. The data from the validation set were used to validate the ANN and PIM models. The accuracy of ANN models and PIM was assessed by area under the receiver operator characteristics (ROC) curve and calibration. All data were randomly allocated to either the training (n=274) or validation set (n=273). Three ANN models were developed using the data from the training set, namely ANN8 (trained with variables required for PIM), ANN9 (trained with variables required for PIM and pre-ICU intubation) and ANN23 (trained with variables required for ANN9 and 14 principal ICU diagnoses). Three ANN models and PIM were used to predict mortality in the validation set. We found that PIM and ANN9 had a high ROC curve (PIM: 0.808, 95 percent confidence interval 0.552 to 1.000, ANN9: 0.957, 95 percent confidence interval 0.915 to 1.000), whereas ANN8 and ANN23 gave a suboptimal area under the ROC curve. ANN8 required only five variables for the calculation of risk, compared with eight for PIM. The current study demonstrated the process of predictive mortality risk model development using ANN. Further multicentre studies are required to produce a representative ANN-based mortality prediction model for use in different PICUs.

Training quality job interviews with adults with developmental disabilities.

PubMed

Mozingo, D; Ackley, G B; Bailey, J S

1994-01-01

Supported work models of vocational integration have increased the employability of individuals with developmental disabilities. Interview questions most frequently used and corresponding responses considered most beneficial to job applicants were derived from an empirical analysis of the "hiring community" and served as a basis for the development of the verbal job interview skills training package evaluated in this research. Dependent measures were objective, behavioral indices of the quality of job interview responses. One-to-one training by a direct training staff, job coach, and a trained behavior analyst resulted in improved responding by all subjects as indicated in a multiple baseline design across interview questions. Improved quality in responding to questions generalized to variations in interview questions, to a novel interviewer, and in an in vivo interview situation. Finally, global measures of social validity support the value of the quality-of-response training.

Work Values, Cognitive Strategies, and Applicant Reactions in a Structured Pre-Employment Interview for Ethical Integrity.

ERIC Educational Resources Information Center

Pawlowski, Donna R.; Hollwitz, John

2000-01-01

Notes that companies emphasize ethical behavior, and schools and professional groups devote many resources to applied ethics training. Describes initial construct validation of a structured ethical integrity pre-employment interview. Reviews evidence relating to cognitive and impression management strategies used when college students encounter an…

Application of See One, Do One, Teach One Concept in Surgical Training

PubMed Central

Kotsis, Sandra V.; Chung, Kevin C.

2016-01-01

Background The traditional method of teaching in Surgery is known as “See One, Do One, Teach One.” However, many have argued that this method is no longer applicable mainly because of concerns for patient safety. The purpose of this paper is to show that the basis of the traditional teaching method is still valid in surgical training if it is combined with various adult learning principles. Methods We reviewed literature regarding the history of the formation of the surgical residency program, adult learning principles, mentoring, and medical simulation. We provide examples for how these learning techniques can be incorporated into a surgical resident training program. Results The surgical residency program created by Dr. William Halsted remained virtually unchanged until recently with reductions in resident work hours and changes to a competency-based training system. Such changes have reduced the teaching time between attending physicians and residents. Learning principles such as “Experience, Observation, Thinking and Action” as well as deliberate practice can be used to train residents. Mentoring is also an important aspect in teaching surgical technique. We review the different types of simulators: standardized patients, virtual reality applications, and high-fidelity mannequin simulators and the advantages and disadvantages of using them. Conclusions The traditional teaching method of “see one, do one, teach one” in surgical residency programs is simple but still applicable. It needs to evolve with current changes in the medical system to adequately train surgical residents and also provide patients with safe, evidence-based care. PMID:23629100

Spouses of thoracic surgery applicants: changing demographics and motivations in a new generation.

PubMed

Bohl, Michael; Reddy, Rishindra M

2013-01-01

Applications to thoracic residency have decreased. The causes are multifactorial, but include changing motivations such as lifestyle concerns. Thoracic residents (TRs) have been well studied, but no one has ever characterized the influence or motivations of their spouses. We sought to evaluate the demographics and interests of TR spouses. An electronic survey was sent to all TR applicants over 2 years at 2 training programs and to all current TRs in 2010. Recipients were asked to forward the survey to their spouses. Responses were analyzed globally and compared in subgroups. Sixty-six surveys were completed and returned for a response rate of 19%. Among them, 86% of respondents were female, with 82% being married for a mean of 4.3 years. Fifty-nine percent of respondents had children and 64% were planning on having more children within 3 years. Hundred percent felt optimistic that they would be financially stable after training, but only 57% were optimistic about quality of life after training. Eighty-four percent felt that they had influence on the choice of training program. Almost 80% wanted more information on salary, housing, and access to faculty spouses. Quality of fellowship, geographic location, and proximity to family were the top 3 factors in choosing a program. Nearly 90% of respondents reported they want to travel to more interviews, and nearly 90% of respondents reported having some to complete influence over which training program to attend. It is safe to presume, therefore, that applicant spouses are not only highly influential on TR applicants but also interested in greater inclusion in the interview process. The results show numerous demographic and characteristic trends which, if further validated by definitive studies, would be applicable to all post-surgery residency training programs and may help TR programs to be more competitive in attracting applicants and their families. Copyright © 2013 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Lateral dynamic interaction analysis of a train girder pier system

NASA Astrophysics Data System (ADS)

Xia, H.; Guo, W. W.; Wu, X.; Pi, Y. L.; Bradford, M. A.

2008-12-01

A dynamic model of a coupled train-girder-pier system is developed in this paper. Each vehicle in a train is modeled with 27 degrees-of-freedom for a 4-axle passenger coach or freight car, and 31 for a 6-axle locomotive. The bridge model is applicable to straight and curved bridges. The centrifugal forces of moving vehicles on curved bridges are considered in both the vehicle model and the bridge model. The dynamic interaction between the bridge and train is realized through an assumed wheel-hunting movement. A case study is performed for a test train traversing two straight and two curved multi-span bridges with high piers. The histories of the train traversing the bridges are simulated and the dynamic responses of the piers and the train vehicles are calculated. A field experiment is carried out to verify the results of the analysis, by which the lateral resonant train speed inducing the peak pier-top amplitudes and some other observations are validated.

The SAFE-T assessment tool: derivation and validation of a web-based application for point-of-care evaluation of gastroenterology fellow performance in colonoscopy.

PubMed

Kumar, Navin L; Kugener, Guillaume; Perencevich, Molly L; Saltzman, John R

2018-01-01

Attending assessment is a critical part of endoscopic education for gastroenterology fellows. The aim of this study was to develop and validate a concise assessment tool to evaluate real-time fellow performance in colonoscopy administered via a web-based application. The Skill Assessment in Fellow Endoscopy Training (SAFE-T) tool was derived as a novel 5-question evaluation tool that captures both summative and formative feedback adapted into a web-based application. A prospective study of 15 gastroenterology fellows (5 fellows each from years 1 to 3 of training) was performed using the SAFE-T tool. An independent reviewer evaluated a subset of these procedures and completed the SAFE-T tool and Mayo Colonoscopy Skills Assessment Tool (MCSAT) for reliability testing. Twenty-six faculty completed 350 SAFE-T evaluations of the 15 fellows in the study. The mean SAFE-T overall score (year 1, 2.00; year 2, 3.84; year 3, 4.28) differentiated each sequential fellow year of training (P < .0001). The mean SAFE-T overall score decreased with increasing case complexity score, with straightforward cases compared with average cases (4.07 vs 3.50, P < .0001), and average cases compared with challenging cases (3.50 vs 3.08, P = .0134). In dual-observed procedures, the SAFE-T tool showed excellent inter-rater reliability with a kappa agreement statistic of 0.898 (P < .0001). Correlation of the SAFE-T overall score with the MCSAT overall hands-on and individual motor scores was excellent (each r > 0.90, P < .0001). We developed and validated the SAFE-T assessment tool, a concise and web-based means of assessing real-time gastroenterology fellow performance in colonoscopy. Copyright © 2018 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Learning to recognize rat social behavior: Novel dataset and cross-dataset application.

PubMed

Lorbach, Malte; Kyriakou, Elisavet I; Poppe, Ronald; van Dam, Elsbeth A; Noldus, Lucas P J J; Veltkamp, Remco C

2018-04-15

Social behavior is an important aspect of rodent models. Automated measuring tools that make use of video analysis and machine learning are an increasingly attractive alternative to manual annotation. Because machine learning-based methods need to be trained, it is important that they are validated using data from different experiment settings. To develop and validate automated measuring tools, there is a need for annotated rodent interaction datasets. Currently, the availability of such datasets is limited to two mouse datasets. We introduce the first, publicly available rat social interaction dataset, RatSI. We demonstrate the practical value of the novel dataset by using it as the training set for a rat interaction recognition method. We show that behavior variations induced by the experiment setting can lead to reduced performance, which illustrates the importance of cross-dataset validation. Consequently, we add a simple adaptation step to our method and improve the recognition performance. Most existing methods are trained and evaluated in one experimental setting, which limits the predictive power of the evaluation to that particular setting. We demonstrate that cross-dataset experiments provide more insight in the performance of classifiers. With our novel, public dataset we encourage the development and validation of automated recognition methods. We are convinced that cross-dataset validation enhances our understanding of rodent interactions and facilitates the development of more sophisticated recognition methods. Combining them with adaptation techniques may enable us to apply automated recognition methods to a variety of animals and experiment settings. Copyright © 2017 Elsevier B.V. All rights reserved.

Automated detection of exudative age-related macular degeneration in spectral domain optical coherence tomography using deep learning.

PubMed

Treder, Maximilian; Lauermann, Jost Lennart; Eter, Nicole

2018-02-01

Our purpose was to use deep learning for the automated detection of age-related macular degeneration (AMD) in spectral domain optical coherence tomography (SD-OCT). A total of 1112 cross-section SD-OCT images of patients with exudative AMD and a healthy control group were used for this study. In the first step, an open-source multi-layer deep convolutional neural network (DCNN), which was pretrained with 1.2 million images from ImageNet, was trained and validated with 1012 cross-section SD-OCT scans (AMD: 701; healthy: 311). During this procedure training accuracy, validation accuracy and cross-entropy were computed. The open-source deep learning framework TensorFlow™ (Google Inc., Mountain View, CA, USA) was used to accelerate the deep learning process. In the last step, a created DCNN classifier, using the information of the above mentioned deep learning process, was tested in detecting 100 untrained cross-section SD-OCT images (AMD: 50; healthy: 50). Therefore, an AMD testing score was computed: 0.98 or higher was presumed for AMD. After an iteration of 500 training steps, the training accuracy and validation accuracies were 100%, and the cross-entropy was 0.005. The average AMD scores were 0.997 ± 0.003 in the AMD testing group and 0.9203 ± 0.085 in the healthy comparison group. The difference between the two groups was highly significant (p < 0.001). With a deep learning-based approach using TensorFlow™, it is possible to detect AMD in SD-OCT with high sensitivity and specificity. With more image data, an expansion of this classifier for other macular diseases or further details in AMD is possible, suggesting an application for this model as a support in clinical decisions. Another possible future application would involve the individual prediction of the progress and success of therapy for different diseases by automatically detecting hidden image information.

The role of virtual reality in surgical training in otorhinolaryngology.

PubMed

Fried, Marvin P; Uribe, José I; Sadoughi, Babak

2007-06-01

This article reviews the rationale, current status and future directions for the development and implementation of virtual reality surgical simulators as training tools. The complexity of modern surgical techniques, which utilize advanced technology, presents a dilemma for surgical training. Hands-on patient experience - the traditional apprenticeship method for teaching operations - may not apply because of the learning curve for skill acquisition and patient safety expectation. The paranasal sinuses and temporal bone have intricate anatomy with a significant amount of vital structures either within the surgical field or in close proximity. The current standard of surgical care in these areas involves the use of endoscopes, cameras and microscopes, requiring additional hand-eye coordination, an accurate command of fine motor skills, and a thorough knowledge of the anatomy under magnified vision. A surgeon's disorientation or loss of perspective can lead to complications, often catastrophic and occasionally lethal. These considerations define the ideal environment for surgical simulation; not surprisingly, significant research and validation of simulators in these areas have occurred. Virtual reality simulators are demonstrating validity as training and skills assessment tools. Future prototypes will find application for routine use in teaching, surgical planning and the development of new instruments and computer-assisted devices.

Two Validated Ways of Improving the Ability of Decision-Making in Emergencies; Results from a Literature Review

PubMed Central

Khorram-Manesh, Amir; Berlin, Johan; Carlström, Eric

2016-01-01

The aim of the current review wasto study the existing knowledge about decision-making and to identify and describe validated training tools.A comprehensive literature review was conducted by using the following keywords: decision-making, emergencies, disasters, crisis management, training, exercises, simulation, validated, real-time, command and control, communication, collaboration, and multi-disciplinary in combination or as an isolated word. Two validated training systems developed in Sweden, 3 level collaboration (3LC) and MacSim, were identified and studied in light of the literature review in order to identify how decision-making can be trained. The training models fulfilled six of the eight identified characteristics of training for decision-making.Based on the results, these training models contained methods suitable to train for decision-making. PMID:27878123

Application of the Monte Carlo method for building up models for octanol-water partition coefficient of platinum complexes

NASA Astrophysics Data System (ADS)

Toropov, Andrey A.; Toropova, Alla P.

2018-06-01

Predictive model of logP for Pt(II) and Pt(IV) complexes built up with the Monte Carlo method using the CORAL software has been validated with six different splits into the training and validation sets. The improving of the predictive potential of models for six different splits has been obtained using so-called index of ideality of correlation. The suggested models give possibility to extract molecular features, which cause the increase or vice versa decrease of the logP.

Using Focus Groups to Validate a Pharmacy Vaccination Training Program.

PubMed

Bushell, Mary; Morrissey, Hana; Ball, Patrick

2015-06-12

Introduction: Focus group methodology is commonly used to quickly collate, integrated views from a variety of different stakeholders. This paper provides an example of how focus groups can be employed to collate expert opinion informing amendments on a newly developed training program for integration into undergraduate pharmacy curricula. Materials and methods: Four focus groups were conducted, across three continents, to determine the appropriateness and reliability of a developed vaccination training program with nested injection skills training. All focus groups were comprised of legitimate experts in the field of vaccination, medicine and/or pharmacy. Results: Themes that emerged across focus groups informed amendments giving rise to a validated version of a training program. Discussion : The rigorous validation of the vaccination training program offers generalizable lessons to inform the design and validation of future training programs intended for the health sector and or pharmacy curricula. Using the knowledge and experience of focus group participants fostered collaborative problem solving and validation of material and concept development. The group dynamics of a focus group allowed synthesis of feedback in an inter-professional manner. Conclusions : This paper provides a demonstration of how focus groups can be structured and used by health researchers to validate a newly developed training program.

Systems approach used in the Gas Centrifuge Enrichment Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rooks, W.A. Jr.

A requirement exists for effective and efficient transfer of technical knowledge from the design engineering team to the production work force. Performance-Based Training (PBT) is a systematic approach to the design, development, and implementation of technical training. This approach has been successfully used by the US Armed Forces, industry, and other organizations. The advantages of the PBT approach are: cost-effectiveness (lowest life-cycle training cost), learning effectiveness, reduced implementation time, and ease of administration. The PBT process comprises five distinctive and rigorous phases: Analysis of Job Performance, Design of Instructional Strategy, Development of Training Materials and Instructional Media, Validation of Materialsmore » and Media, and Implementation of the Instructional Program. Examples from the Gas Centrifuge Enrichment Plant (GCEP) are used to illustrate the application of PBT.« less

Encoding, training and retrieval in ferroelectric tunnel junctions

NASA Astrophysics Data System (ADS)

Xu, Hanni; Xia, Yidong; Xu, Bo; Yin, Jiang; Yuan, Guoliang; Liu, Zhiguo

2016-05-01

Ferroelectric tunnel junctions (FTJs) are quantum nanostructures that have great potential in the hardware basis for future neuromorphic applications. Among recently proposed possibilities, the artificial cognition has high hopes, where encoding, training, memory solidification and retrieval constitute a whole chain that is inseparable. However, it is yet envisioned but experimentally unconfirmed. The poor retention or short-term store of tunneling electroresistance, in particular the intermediate states, is still a key challenge in FTJs. Here we report the encoding, training and retrieval in BaTiO3 FTJs, emulating the key features of information processing in terms of cognitive neuroscience. This is implemented and exemplified through processing characters. Using training inputs that are validated by the evolution of both barrier profile and domain configuration, accurate recalling of encoded characters in the retrieval stage is demonstrated.

Predictive Variables of Half-Marathon Performance for Male Runners.

PubMed

Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A; García-López, Juan

2017-06-01

The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO 2max , speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance.

High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

NASA Astrophysics Data System (ADS)

Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

2016-12-01

Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

Predictive Variables of Half-Marathon Performance for Male Runners

PubMed Central

Gómez-Molina, Josué; Ogueta-Alday, Ana; Camara, Jesus; Stickley, Christoper; Rodríguez-Marroyo, José A.; García-López, Juan

2017-01-01

The aims of this study were to establish and validate various predictive equations of half-marathon performance. Seventy-eight half-marathon male runners participated in two different phases. Phase 1 (n = 48) was used to establish the equations for estimating half-marathon performance, and Phase 2 (n = 30) to validate these equations. Apart from half-marathon performance, training-related and anthropometric variables were recorded, and an incremental test on a treadmill was performed, in which physiological (VO2max, speed at the anaerobic threshold, peak speed) and biomechanical variables (contact and flight times, step length and step rate) were registered. In Phase 1, half-marathon performance could be predicted to 90.3% by variables related to training and anthropometry (Equation 1), 94.9% by physiological variables (Equation 2), 93.7% by biomechanical parameters (Equation 3) and 96.2% by a general equation (Equation 4). Using these equations, in Phase 2 the predicted time was significantly correlated with performance (r = 0.78, 0.92, 0.90 and 0.95, respectively). The proposed equations and their validation showed a high prediction of half-marathon performance in long distance male runners, considered from different approaches. Furthermore, they improved the prediction performance of previous studies, which makes them a highly practical application in the field of training and performance. Key points The present study obtained four equations involving anthropometric, training, physiological and biomechanical variables to estimate half-marathon performance. These equations were validated in a different population, demonstrating narrows ranges of prediction than previous studies and also their consistency. As a novelty, some biomechanical variables (i.e. step length and step rate at RCT, and maximal step length) have been related to half-marathon performance. PMID:28630571

Design, Development and Delivery of Active Learning Tools in Software Verification & Validation Education

ERIC Educational Resources Information Center

Acharya, Sushil; Manohar, Priyadarshan Anant; Wu, Peter; Maxim, Bruce; Hansen, Mary

2018-01-01

Active learning tools are critical in imparting real world experiences to the students within a classroom environment. This is important because graduates are expected to develop software that meets rigorous quality standards in functional and application domains with little to no training. However, there is a well-recognized need for the…

Genomic prediction in bi-parental tropical maize populations in water-stressed and well-watered environments using low density and GBS SNPs

USDA-ARS?s Scientific Manuscript database

One of the most important applications of genomic selection in maize breeding is to predict and identify the best-untested individuals from bi-parental populations, when the training and validation sets are derived from the same cross. Nineteen tropical maize bi-parental populations evaluated in mul...

Modeling Expert Behavior in Support of an Adaptive Psychomotor Training Environment: A Marksmanship Use Case

ERIC Educational Resources Information Center

Goldberg, Benjamin; Amburn, Charles; Ragusa, Charlie; Chen, Dar-Wei

2018-01-01

The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…

Validity of the Medical College Admission Test for predicting MD-PhD student outcomes.

PubMed

Bills, James L; VanHouten, Jacob; Grundy, Michelle M; Chalkley, Roger; Dermody, Terence S

2016-03-01

The Medical College Admission Test (MCAT) is a quantitative metric used by MD and MD-PhD programs to evaluate applicants for admission. This study assessed the validity of the MCAT in predicting training performance measures and career outcomes for MD-PhD students at a single institution. The study population consisted of 153 graduates of the Vanderbilt Medical Scientist Training Program (combined MD-PhD program) who matriculated between 1963 and 2003 and completed dual-degree training. This population was divided into three cohorts corresponding to the version of the MCAT taken at the time of application. Multivariable regression (logistic for binary outcomes and linear for continuous outcomes) was used to analyze factors associated with outcome measures. The MCAT score and undergraduate GPA (uGPA) were treated as independent variables; medical and graduate school grades, time-to-PhD defense, USMLE scores, publication number, and career outcome were dependent variables. For cohort 1 (1963-1977), MCAT score was not associated with any assessed outcome, although uGPA was associated with medical school preclinical GPA and graduate school GPA (gsGPA). For cohort 2 (1978-1991), MCAT score was associated with USMLE Step II score and inversely correlated with publication number, and uGPA was associated with preclinical GPA (mspGPA) and clinical GPA (mscGPA). For cohort 3 (1992-2003), the MCAT score was associated with mscGPA, and uGPA was associated with gsGPA. Overall, MCAT score and uGPA were inconsistent or weak predictors of training metrics and career outcomes for this population of MD-PhD students.

Budget Online Learning Algorithm for Least Squares SVM.

PubMed

Jian, Ling; Shen, Shuqian; Li, Jundong; Liang, Xijun; Li, Lei

2017-09-01

Batch-mode least squares support vector machine (LSSVM) is often associated with unbounded number of support vectors (SVs'), making it unsuitable for applications involving large-scale streaming data. Limited-scale LSSVM, which allows efficient updating, seems to be a good solution to tackle this issue. In this paper, to train the limited-scale LSSVM dynamically, we present a budget online LSSVM (BOLSSVM) algorithm. Methodologically, by setting a fixed budget for SVs', we are able to update the LSSVM model according to the updated SVs' set dynamically without retraining from scratch. In particular, when a new small chunk of SVs' substitute for the old ones, the proposed algorithm employs a low rank correction technology and the Sherman-Morrison-Woodbury formula to compute the inverse of saddle point matrix derived from the LSSVM's Karush-Kuhn-Tucker (KKT) system, which, in turn, updates the LSSVM model efficiently. In this way, the proposed BOLSSVM algorithm is especially useful for online prediction tasks. Another merit of the proposed BOLSSVM is that it can be used for k -fold cross validation. Specifically, compared with batch-mode learning methods, the computational complexity of the proposed BOLSSVM method is significantly reduced from O(n 4 ) to O(n 3 ) for leave-one-out cross validation with n training samples. The experimental results of classification and regression on benchmark data sets and real-world applications show the validity and effectiveness of the proposed BOLSSVM algorithm.

Gamification of Cognitive Assessment and Cognitive Training: A Systematic Review of Applications and Efficacy

PubMed Central

Edwards, Elizabeth A; Lawrence, Natalia S; Coyle, David; Munafò, Marcus R

2016-01-01

Background Cognitive tasks are typically viewed as effortful, frustrating, and repetitive, which often leads to participant disengagement. This, in turn, may negatively impact data quality and/or reduce intervention effects. However, gamification may provide a possible solution. If game design features can be incorporated into cognitive tasks without undermining their scientific value, then data quality, intervention effects, and participant engagement may be improved. Objectives This systematic review aims to explore and evaluate the ways in which gamification has already been used for cognitive training and assessment purposes. We hope to answer 3 questions: (1) Why have researchers opted to use gamification? (2) What domains has gamification been applied in? (3) How successful has gamification been in cognitive research thus far? Methods We systematically searched several Web-based databases, searching the titles, abstracts, and keywords of database entries using the search strategy (gamif* OR game OR games) AND (cognit* OR engag* OR behavi* OR health* OR attention OR motiv*). Searches included papers published in English between January 2007 and October 2015. Results Our review identified 33 relevant studies, covering 31 gamified cognitive tasks used across a range of disorders and cognitive domains. We identified 7 reasons for researchers opting to gamify their cognitive training and testing. We found that working memory and general executive functions were common targets for both gamified assessment and training. Gamified tests were typically validated successfully, although mixed-domain measurement was a problem. Gamified training appears to be highly engaging and does boost participant motivation, but mixed effects of gamification on task performance were reported. Conclusions Heterogeneous study designs and typically small sample sizes highlight the need for further research in both gamified training and testing. Nevertheless, careful application of gamification can provide a way to develop engaging and yet scientifically valid cognitive assessments, and it is likely worthwhile to continue to develop gamified cognitive tasks in the future. PMID:27421244

Gamification of Cognitive Assessment and Cognitive Training: A Systematic Review of Applications and Efficacy.

PubMed

Lumsden, Jim; Edwards, Elizabeth A; Lawrence, Natalia S; Coyle, David; Munafò, Marcus R

2016-07-15

Cognitive tasks are typically viewed as effortful, frustrating, and repetitive, which often leads to participant disengagement. This, in turn, may negatively impact data quality and/or reduce intervention effects. However, gamification may provide a possible solution. If game design features can be incorporated into cognitive tasks without undermining their scientific value, then data quality, intervention effects, and participant engagement may be improved. This systematic review aims to explore and evaluate the ways in which gamification has already been used for cognitive training and assessment purposes. We hope to answer 3 questions: (1) Why have researchers opted to use gamification? (2) What domains has gamification been applied in? (3) How successful has gamification been in cognitive research thus far? We systematically searched several Web-based databases, searching the titles, abstracts, and keywords of database entries using the search strategy (gamif* OR game OR games) AND (cognit* OR engag* OR behavi* OR health* OR attention OR motiv*). Searches included papers published in English between January 2007 and October 2015. Our review identified 33 relevant studies, covering 31 gamified cognitive tasks used across a range of disorders and cognitive domains. We identified 7 reasons for researchers opting to gamify their cognitive training and testing. We found that working memory and general executive functions were common targets for both gamified assessment and training. Gamified tests were typically validated successfully, although mixed-domain measurement was a problem. Gamified training appears to be highly engaging and does boost participant motivation, but mixed effects of gamification on task performance were reported. Heterogeneous study designs and typically small sample sizes highlight the need for further research in both gamified training and testing. Nevertheless, careful application of gamification can provide a way to develop engaging and yet scientifically valid cognitive assessments, and it is likely worthwhile to continue to develop gamified cognitive tasks in the future.

Bimanual Psychomotor Performance in Neurosurgical Resident Applicants Assessed Using NeuroTouch, a Virtual Reality Simulator.

PubMed

Winkler-Schwartz, Alexander; Bajunaid, Khalid; Mullah, Muhammad A S; Marwa, Ibrahim; Alotaibi, Fahad E; Fares, Jawad; Baggiani, Marta; Azarnoush, Hamed; Zharni, Gmaan Al; Christie, Sommer; Sabbagh, Abdulrahman J; Werthner, Penny; Del Maestro, Rolando F

Current selection methods for neurosurgical residents fail to include objective measurements of bimanual psychomotor performance. Advancements in computer-based simulation provide opportunities to assess cognitive and psychomotor skills in surgically naive populations during complex simulated neurosurgical tasks in risk-free environments. This pilot study was designed to answer 3 questions: (1) What are the differences in bimanual psychomotor performance among neurosurgical residency applicants using NeuroTouch? (2) Are there exceptionally skilled medical students in the applicant cohort? and (3) Is there an influence of previous surgical exposure on surgical performance? Participants were instructed to remove 3 simulated brain tumors with identical visual appearance, stiffness, and random bleeding points. Validated tier 1, tier 2, and advanced tier 2 metrics were used to assess bimanual psychomotor performance. Demographic data included weeks of neurosurgical elective and prior operative exposure. This pilot study was carried out at the McGill Neurosurgical Simulation Research and Training Center immediately following neurosurgical residency interviews at McGill University, Montreal, Canada. All 17 medical students interviewed were asked to participate, of which 16 agreed. Performances were clustered in definable top, middle, and bottom groups with significant differences for all metrics. Increased time spent playing music, increased applicant self-evaluated technical skills, high self-ratings of confidence, and increased skin closures statistically influenced performance on univariate analysis. A trend for both self-rated increased operating room confidence and increased weeks of neurosurgical exposure to increased blood loss was seen in multivariate analysis. Simulation technology identifies neurosurgical residency applicants with differing levels of technical ability. These results provide information for studies being developed for longitudinal studies on the acquisition, development, and maintenance of psychomotor skills. Technical abilities customized training programs that maximize individual resident bimanual psychomotor training dependant on continuously updated and validated metrics from virtual reality simulation studies should be explored. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Identifying training and informational components to develop a psoriasis self- management application

PubMed Central

Safdari, Reza; Firoz, Alireza; Masoorian, Hoorie

2017-01-01

Background: Psoriasis is a complex disease with lifelong emotional and social consequences for affected patients. It also reduces the patients’ quality of life and requires a long-term management. Therefore, in addition to appropriate treatment of the disease, selfmanagement strategies to improve patient health and quality of life are essential. On the other hand, smartphone-based applications alter the way people interact with health care and public health systems. This study aimed at identifying training and informational components to develop a psoriasis self- management application. Methods: This descriptive-analytic study was conducted on 100 patients with psoriasis and 26 dermatologists who were selected randomly, using Morgan table. The data were collected using a researcher- made questionnaire, which included demographic and clinical information, lifestyle training and management, and application capabilities in psoriasis self-management. A group of experts and a test-retest method were used to confirm the validity and reliability of the questionnaire, respectively. Results: The mean scores for demographic and clinical information, lifestyle training and management, and application capabilities in self-management were 80.55%, 85.7%, and 88.8% from the patients’ perspective, and 83.7%, 71%, and 75% from the specialists’ viewpoint, respectively. Conclusion: Determining self-management components by patients as persons who are suffering from the disease and physicians as specialists in the field will be helpful in efficient psoriasis self-management. It is more likely that self-reliant patients, who are aware of the benefits and risks of their disease management application, will follow their treatment plan and pursue the management of their disease more seriously PMID:29445696

Decision tree methods: applications for classification and prediction.

PubMed

Song, Yan-Yan; Lu, Ying

2015-04-25

Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. This method classifies a population into branch-like segments that construct an inverted tree with a root node, internal nodes, and leaf nodes. The algorithm is non-parametric and can efficiently deal with large, complicated datasets without imposing a complicated parametric structure. When the sample size is large enough, study data can be divided into training and validation datasets. Using the training dataset to build a decision tree model and a validation dataset to decide on the appropriate tree size needed to achieve the optimal final model. This paper introduces frequently used algorithms used to develop decision trees (including CART, C4.5, CHAID, and QUEST) and describes the SPSS and SAS programs that can be used to visualize tree structure.

Smartphone based automatic organ validation in ultrasound video.

PubMed

Vaish, Pallavi; Bharath, R; Rajalakshmi, P

2017-07-01

Telesonography involves transmission of ultrasound video from remote areas to the doctors for getting diagnosis. Due to the lack of trained sonographers in remote areas, the ultrasound videos scanned by these untrained persons do not contain the proper information that is required by a physician. As compared to standard methods for video transmission, mHealth driven systems need to be developed for transmitting valid medical videos. To overcome this problem, we are proposing an organ validation algorithm to evaluate the ultrasound video based on the content present. This will guide the semi skilled person to acquire the representative data from patient. Advancement in smartphone technology allows us to perform high medical image processing on smartphone. In this paper we have developed an Application (APP) for a smartphone which can automatically detect the valid frames (which consist of clear organ visibility) in an ultrasound video and ignores the invalid frames (which consist of no-organ visibility), and produces a compressed sized video. This is done by extracting the GIST features from the Region of Interest (ROI) of the frame and then classifying the frame using SVM classifier with quadratic kernel. The developed application resulted with the accuracy of 94.93% in classifying valid and invalid images.

Establishing ultrasound based transient elastography cutoffs for different stages of hepatic fibrosis and cirrhosis in Egyptian chronic hepatitis C patients.

PubMed

Elsharkawy, Aisha; Alboraie, Mohamed; Fouad, Rabab; Asem, Noha; Abdo, Mahmoud; Elmakhzangy, Hesham; Mehrez, Mai; Khattab, Hany; Esmat, Gamal

2017-12-01

Transient elastography is widely used to assess fibrosis stage in chronic hepatitis C (CHC). We aimed to establish and validate different transient elastography cut-off values for significant fibrosis and cirrhosis in CHC genotype 4 patients. The data of 100 treatment-naive CHC patients (training set) and 652 patients (validation set) were analysed. The patients were subjected to routine pretreatment laboratory investigations, liver biopsy and histopathological staging of hepatic fibrosis according to the METAVIR scoring system. Transient elastography was performed before and in the same week as liver biopsy using FibroScan (Echosens, Paris, France). Transient elastography results were correlated to different stages of hepatic fibrosis in both the training and validation sets. ROC curves were constructed. In the training set, the best transient elastography cut-off values for significant hepatic fibrosis (≥F2 METAVIR), advanced hepatic fibrosis (≥F3 METAVIR) and cirrhosis (F4 METAVIR) were 7.1, 9 and 12.2 kPa, with sensitivities of 87%, 87.5% and 90.9% and specificities of 100%, 99.9% and 99.9%, respectively. The application of these cut-offs in the validation set showed sensitivities of 85.5%, 82.8% and 92% and specificities of 86%, 89.4% and 99.01% for significant hepatic fibrosis, advanced hepatic fibrosis and cirrhosis, respectively. Transient elastography performs well for significant hepatic fibrosis, advanced hepatic fibrosis and cirrhosis, with validated cut-offs of 7.1, 9 and 12.2 kPa, respectively, in genotype 4 CHC patients. Copyright © 2017 Pan-Arab Association of Gastroenterology. Published by Elsevier B.V. All rights reserved.

A machine learning approach to multi-level ECG signal quality classification.

PubMed

Li, Qiao; Rajagopalan, Cadathur; Clifford, Gari D

2014-12-01

Current electrocardiogram (ECG) signal quality assessment studies have aimed to provide a two-level classification: clean or noisy. However, clinical usage demands more specific noise level classification for varying applications. This work outlines a five-level ECG signal quality classification algorithm. A total of 13 signal quality metrics were derived from segments of ECG waveforms, which were labeled by experts. A support vector machine (SVM) was trained to perform the classification and tested on a simulated dataset and was validated using data from the MIT-BIH arrhythmia database (MITDB). The simulated training and test datasets were created by selecting clean segments of the ECG in the 2011 PhysioNet/Computing in Cardiology Challenge database, and adding three types of real ECG noise at different signal-to-noise ratio (SNR) levels from the MIT-BIH Noise Stress Test Database (NSTDB). The MITDB was re-annotated for five levels of signal quality. Different combinations of the 13 metrics were trained and tested on the simulated datasets and the best combination that produced the highest classification accuracy was selected and validated on the MITDB. Performance was assessed using classification accuracy (Ac), and a single class overlap accuracy (OAc), which assumes that an individual type classified into an adjacent class is acceptable. An Ac of 80.26% and an OAc of 98.60% on the test set were obtained by selecting 10 metrics while 57.26% (Ac) and 94.23% (OAc) were the numbers for the unseen MITDB validation data without retraining. By performing the fivefold cross validation, an Ac of 88.07±0.32% and OAc of 99.34±0.07% were gained on the validation fold of MITDB. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Brief report: application of the TEACCH program on Chinese pre-school children with autism--Does culture make a difference?

PubMed

Tsang, Sandra K M; Shek, Daniel T L; Lam, Lorinda L; Tang, Florence L Y; Cheung, Penita M P

2007-02-01

A longitudinal study was conducted on 34 children with autism to evaluate the usefulness of the Treatment and Education of Autistic and related Communication Handicapped Children (TEACCH) program for Chinese pre-school children in Hong Kong. Eighteen children received full-time center-based TEACCH program training. The control group included 16 children who received different types of individualized or group training but not TEACCH program training. Instruments validated in Hong Kong were used to assess the children's cognitive, social adaptive functioning and developmental abilities before and during the training at 6-month intervals for 12 months. Children in the experimental group showed better outcomes at posttest. They also showed progress in different developmental domains over time. The study provided initial support for the effectiveness of using the TEACCH program with Chinese children.

Ubiquitous Connected Train Based on Train-to-Ground and Intra-Wagon Communications Capable of Providing on Trip Customized Digital Services for Passengers

PubMed Central

Salaberria, Itziar; Perallos, Asier; Azpilicueta, Leire; Falcone, Francisco; Carballedo, Roberto; Angulo, Ignacio; Elejoste, Pilar; Bahillo, Alfonso; Astrain, José Javier; Villadangos, Jesús

2014-01-01

During the last years, the application of different wireless technologies has been explored in order to enable Internet connectivity from vehicles. In addition, the widespread adoption of smartphones by citizens represents a great opportunity to integrate such nomadic devices inside vehicles in order to provide new and personalized on trip services for passengers. In this paper, a proposal of communication architecture to provide the ubiquitous connectivity needed to enhance the smart train concept is presented and preliminarily tested. It combines an intra-wagon communication system based on nomadic devices connected through a Bluetooth Piconet Network with a highly innovative train-to-ground communication system. In order to validate this communication solution, several tests and simulations have been performed and their results are described in this paper. PMID:24803192

Vertical flight training: An overview of training and flight simulator technology with emphasis on rotary-wing requirements

NASA Technical Reports Server (NTRS)

Alderete, Thomas S.; Ascencio-Lee, Carmen E.; Bray, Richard; Carlton, John; Dohme, Jack; Eshow, Michelle M.; Francis, Stephen; Lee, Owen M.; Lintern, Gavan; Lombardo, David A.

1994-01-01

The principal purpose of this publication is to provide a broad overview of the technology that is relevant to the design of aviation training systems and of the techniques applicable to the development, use, and evaluation of those systems. The issues addressed in our 11 chapters are, for the most part, those that would be expected to surface in any informed discussion of the major characterizing elements of aviation training systems. Indeed, many of the same facets of vertical-flight training discussed were recognized and, to some extent, dealt with at the 1991 NASA/FAA Helicopter Simulator Workshop. These generic topics are essential to a sound understanding of training and training systems, and they quite properly form the basis of any attempt to systematize the development and evaluation of more effective, more efficient, more productive, and more economical approaches to aircrew training. Individual chapters address the following topics: an overview of the vertical flight industry: the source of training requirements; training and training schools: meeting current requirements; training systems design and development; transfer of training and cost-effectiveness; the military quest for flight training effectiveness; alternative training systems; training device manufacturing; simulator aero model implementation; simulation validation in the frequency domain; cockpit motion in helicopter simulation; and visual space perception in flight simulators.

Educational Technology Project, Volume One. The Development of Materials for the Training of Science Education Personnel in Educational Technology. Final Report.

ERIC Educational Resources Information Center

Ziener, George H.; And Others

The planning, production, validation, and revision of learning materials designed for use in institutes for science supervisors is described in this first of five volumes. Four sets of packages, ("Role of the Science Supervisor,""Introduction to Educational Technology,""An Application of Educational Technology," and "Management Kits,") each using…

Considering Personality Type in Adult Learning: Using the Myers-Briggs Type Indicator in Instructor Preparation at PricewaterhouseCoopers

ERIC Educational Resources Information Center

Daisley, Richard J.

2011-01-01

This article explores the feasibility of using the Myers-Briggs Type Indicator (MBTI) as a framework for instructor development in a professional services training environment. It explores the consistency of MBTI with common adult learning theory, addresses questions on MBTI's reliability and validity, and explores the applicability of MBTI to the…

Predicting ground contact events for a continuum of gait types: An application of targeted machine learning using principal component analysis.

PubMed

Osis, Sean T; Hettinga, Blayne A; Ferber, Reed

2016-05-01

An ongoing challenge in the application of gait analysis to clinical settings is the standardized detection of temporal events, with unobtrusive and cost-effective equipment, for a wide range of gait types. The purpose of the current study was to investigate a targeted machine learning approach for the prediction of timing for foot strike (or initial contact) and toe-off, using only kinematics for walking, forefoot running, and heel-toe running. Data were categorized by gait type and split into a training set (∼30%) and a validation set (∼70%). A principal component analysis was performed, and separate linear models were trained and validated for foot strike and toe-off, using ground reaction force data as a gold-standard for event timing. Results indicate the model predicted both foot strike and toe-off timing to within 20ms of the gold-standard for more than 95% of cases in walking and running gaits. The machine learning approach continues to provide robust timing predictions for clinical use, and may offer a flexible methodology to handle new events and gait types. Copyright © 2016 Elsevier B.V. All rights reserved.

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Multicenter Validation of a Customizable Scoring Tool for Selection of Trainees for a Residency or Fellowship Program. The EAST-IST Study.

PubMed

Bosslet, Gabriel T; Carlos, W Graham; Tybor, David J; McCallister, Jennifer; Huebert, Candace; Henderson, Ashley; Miles, Matthew C; Twigg, Homer; Sears, Catherine R; Brown, Cynthia; Farber, Mark O; Lahm, Tim; Buckley, John D

2017-04-01

Few data have been published regarding scoring tools for selection of postgraduate medical trainee candidates that have wide applicability. The authors present a novel scoring tool developed to assist postgraduate programs in generating an institution-specific rank list derived from selected elements of the U.S. Electronic Residency Application System (ERAS) application. The authors developed and validated an ERAS and interview day scoring tool at five pulmonary and critical care fellowship programs: the ERAS Application Scoring Tool-Interview Scoring Tool. This scoring tool was then tested for intrarater correlation versus subjective rankings of ERAS applications. The process for development of the tool was performed at four other institutions, and it was performed alongside and compared with the "traditional" ranking methods at the five programs and compared with the submitted National Residency Match Program rank list. The ERAS Application Scoring Tool correlated highly with subjective faculty rankings at the primary institution (average Spearman's r = 0.77). The ERAS Application Scoring Tool-Interview Scoring Tool method correlated well with traditional ranking methodology at all five institutions (Spearman's r = 0.54, 0.65, 0.72, 0.77, and 0.84). This study validates a process for selecting and weighting components of the ERAS application and interview day to create a customizable, institution-specific tool for ranking candidates to postgraduate medical education programs. This scoring system can be used in future studies to compare the outcomes of fellowship training.

European consensus on a competency-based virtual reality training program for basic endoscopic surgical psychomotor skills.

PubMed

van Dongen, Koen W; Ahlberg, Gunnar; Bonavina, Luigi; Carter, Fiona J; Grantcharov, Teodor P; Hyltander, Anders; Schijven, Marlies P; Stefani, Alessandro; van der Zee, David C; Broeders, Ivo A M J

2011-01-01

Virtual reality (VR) simulators have been demonstrated to improve basic psychomotor skills in endoscopic surgery. The exercise configuration settings used for validation in studies published so far are default settings or are based on the personal choice of the tutors. The purpose of this study was to establish consensus on exercise configurations and on a validated training program for a virtual reality simulator, based on the experience of international experts to set criterion levels to construct a proficiency-based training program. A consensus meeting was held with eight European teams, all extensively experienced in using the VR simulator. Construct validity of the training program was tested by 20 experts and 60 novices. The data were analyzed by using the t test for equality of means. Consensus was achieved on training designs, exercise configuration, and examination. Almost all exercises (7/8) showed construct validity. In total, 50 of 94 parameters (53%) showed significant difference. A European, multicenter, validated, training program was constructed according to the general consensus of a large international team with extended experience in virtual reality simulation. Therefore, a proficiency-based training program can be offered to training centers that use this simulator for training in basic psychomotor skills in endoscopic surgery.

Screening Tool to Determine Risk of Having Muscle Dysmorphia Symptoms in Men Who Engage in Weight Training at a Gym.

PubMed

Palazón-Bru, Antonio; Rizo-Baeza, María M; Martínez-Segura, Asier; Folgado-de la Rosa, David M; Gil-Guillén, Vicente F; Cortés-Castell, Ernesto

2018-03-01

Although 2 screening tests exist for having a high risk of muscle dysmorphia (MD) symptoms, they both require a long time to apply. Accordingly, we proposed the construction, validation, and implementation of such a test in a mobile application using easy-to-measure factors associated with MD. Cross-sectional observational study. Gyms in Alicante (Spain) during 2013 to 2014. One hundred forty-one men who engaged in weight training. The variables are as follows: age, educational level, income, buys own food, physical activity per week, daily meals, importance of nutrition, special nutrition, guilt about dietary nonadherence, supplements, and body mass index (BMI). A points system was constructed through a binary logistic regression model to predict a high risk of MD symptoms by testing all possible combinations of secondary variables (5035). The system was validated using bootstrapping and implemented in a mobile application. High risk of having MD symptoms (Muscle Appearance Satisfaction Scale). Of the 141 participants, 45 had a high risk of MD symptoms [31.9%, 95% confidence interval (CI), 24.2%-39.6%]. The logistic regression model combination providing the largest area under the receiver operating characteristic curve (0.76) included the following: age [odds ratio (OR) = 0.90; 95% CI, 0.84-0.97, P = 0.007], guilt about dietary nonadherence (OR = 2.46; 95% CI, 1.06-5.73, P = 0.037), energy supplements (OR = 3.60; 95% CI, 1.54-8.44, P = 0.003), and BMI (OR = 1.33, 95% CI, 1.12-1.57, P < 0.001). The points system was validated through 1000 bootstrap samples. A quick, easy-to-use, 4-factor test that could serve as a screening tool for a high risk of MD symptoms has been constructed, validated, and implemented in a mobile application.

Application of convolutional artificial neural networks to echocardiograms for differentiating congenital heart diseases in a pediatric population

NASA Astrophysics Data System (ADS)

Perrin, Douglas P.; Bueno, Alejandra; Rodriguez, Andrea; Marx, Gerald R.; del Nido, Pedro J.

2017-03-01

In this paper we describe a pilot study, where machine learning methods are used to differentiate between congenital heart diseases. Our approach was to apply convolutional neural networks (CNNs) to echocardiographic images from five different pediatric populations: normal, coarctation of the aorta (CoA), hypoplastic left heart syndrome (HLHS), transposition of the great arteries (TGA), and single ventricle (SV). We used a single network topology that was trained in a pairwise fashion in order to evaluate the potential to differentiate between patient populations. In total we used 59,151 echo frames drawn from 1,666 clinical sequences. Approximately 80% of the data was used for training, and the remainder for validation. Data was split at sequence boundaries to avoid having related images in the training and validation sets. While training was done with echo images/frames, evaluation was performed for both single frame discrimination as well as sequence discrimination (by majority voting). In total 10 networks were generated and evaluated. Unlike other domains where this network topology has been used, in ultrasound there is low visual variation between classes. This work shows the potential for CNNs to be applied to this low-variation domain of medical imaging for disease discrimination.

Quality control of colonoscopy procedures: a prospective validated method for the evaluation of professional practices applicable to all endoscopic units.

PubMed

Coriat, R; Pommaret, E; Chryssostalis, A; Viennot, S; Gaudric, M; Brezault, C; Lamarque, D; Roche, H; Verdier, D; Parlier, D; Prat, F; Chaussade, S

2009-02-01

To produce valid information, an evaluation of professional practices has to assess the quality of all practices before, during and after the procedure under study. Several auditing techniques have been proposed for colonoscopy. The purpose of this work is to describe a straightforward original validated method for the prospective evaluation of professional practices in the field of colonoscopy applicable in all endoscopy units without increasing the staff work load. Pertinent quality-control criteria (14 items) were identified by the endoscopists at the Cochin Hospital and were compatible with: findings in the available literature; guidelines proposed by the Superior Health Authority; and application in any endoscopy unit. Prospective routine data were collected and the methodology validated by evaluating 50 colonoscopies every quarter for one year. The relevance of the criteria was assessed using data collected during four separate periods. The standard checklist was complete for 57% of the colonoscopy procedures. The colonoscopy procedure was appropriate according to national guidelines in 94% of cases. These observations were particularly noteworthy: the quality of the colonic preparation was insufficient for 9% of the procedures; complete colonoscopy was achieved for 93% of patients; and 0.38 adenomas and 0.045 carcinomas were identified per colonoscopy. This simple and reproducible method can be used for valid quality-control audits in all endoscopy units. In France, unit-wide application of this method enables endoscopists to validate 100 of the 250 points required for continuous medical training. This is a quality-control tool that can be applied annually, using a random month to evaluate any changes in routine practices.

Can training in empathetic validation improve medical students' communication with patients suffering pain? A test of concept.

PubMed

Linton, Steven J; Flink, Ida K; Nilsson, Emma; Edlund, Sara

2017-05-01

Patient-centered, empathetic communication has been recommended as a means for improving the health care of patients suffering pain. However, a problem has been training health care providers since programs may be time-consuming and difficult to learn. Validation, a form of empathetic response that communicates that what a patient experiences is accepted as true, has been suggested as an appropriate method for improving communication with patients suffering pain. We study the immediate effects of providing medical students with a 2-session (45-minute duration each) program in validation skills on communication. A one group, pretest vs posttest design was employed with 22 volunteer medical students. To control patient variables, actors simulated 1 of 2 patient scenarios (randomly provided at pretest and posttest). Video recordings were blindly evaluated. Self-ratings of validation and satisfaction were also employed. Observed validation responses increased significantly after training and corresponded to significant reductions in invalidating responses. Both the patient simulators and the medical students were significantly more satisfied after the training. We demonstrated that training empathetic validation results in improved communication thus extending previous findings to a medical setting with patients suffering pain. Our results suggest that it would be feasible to provide validation training for health care providers and this warrants further investigation in controlled studies.

Computer-assisted teaching of skin flap surgery: validation of a mobile platform software for medical students.

PubMed

de Sena, David P; Fabricio, Daniela D; Lopes, Maria Helena I; da Silva, Vinicius D

2013-01-01

The purpose of this study was to develop and validate a multimedia software application for mobile platforms to assist in the teaching and learning process of design and construction of a skin flap. Traditional training in surgery is based on learning by doing. Initially, the use of cadavers and animal models appeared to be a valid alternative for training. However, many conflicts with these training models prompted progression to synthetic and virtual reality models. Fifty volunteer fifth- and sixth-year medical students completed a pretest and were randomly allocated into two groups of 25 students each. The control group was exposed for 5 minutes to a standard text-based print article, while the test group used multimedia software describing how to fashion a rhomboid flap. Each group then performed a cutaneous flap on a training bench model while being evaluated by three blinded BSPS (Brazilian Society of Plastic Surgery) board-certified surgeons using the OSATS (Objective Structured Assessment of Technical Skill) protocol and answered a post-test. The text-based group was then tested again using the software. The computer-assisted learning (CAL) group had superior performance as confirmed by checklist scores (p<0.002), overall global assessment (p = 0.017) and post-test results (p<0.001). All participants ranked the multimedia method as the best study tool. CAL learners exhibited better subjective and objective performance when fashioning rhomboid flaps as compared to those taught with standard print material. These findings indicate that students preferred to learn using the multimedia method.

Development and evaluation of a trauma decision-making simulator in Oculus virtual reality.

PubMed

Harrington, Cuan M; Kavanagh, Dara O; Quinlan, John F; Ryan, Donncha; Dicker, Patrick; O'Keeffe, Dara; Traynor, Oscar; Tierney, Sean

2018-01-01

Consumer-available virtual-reality technology was launched in 2016 with strong foundations in the entertainment-industry. We developed an innovative medical-training simulator on the Oculus™ Gear-VR platform. This novel application was developed utilising internationally recognised Advanced Trauma Life Support (ATLS) principles, requiring decision-making skills for critically-injured virtual-patients. Participants were recruited in June, 2016 at a single-centre trauma-course (ATLS, Leinster, Ireland) and trialled the platform. Simulator performances were correlated with individual expertise and course-performance measures. A post-intervention questionnaire relating to validity-aspects was completed. Eighteen(81.8%) eligible-candidates and eleven(84.6%) course-instructors voluntarily participated. The survey-responders mean-age was 38.9(±11.0) years with 80.8% male predominance. The instructor-group caused significantly less fatal-errors (p < 0.050) and proportions of incorrect-decisions (p < 0.050). The VR-hardware and trauma-application's mean ratings were 5.09 and 5.04 out of 7 respectively. Participants reported it was an enjoyable method of learning (median-6.0), the learning platform of choice (median-5.0) and a cost-effective training tool (median-5.0). Our research has demonstrated evidence of validity-criteria for a concept application on virtual-reality headsets. We believe that virtual-reality technology is a viable platform for medical-simulation into the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Survey Instrument Validity Part I: Principles of Survey Instrument Development and Validation in Athletic Training Education Research

ERIC Educational Resources Information Center

Burton, Laura J.; Mazerolle, Stephanie M.

2011-01-01

Context: Instrument validation is an important facet of survey research methods and athletic trainers must be aware of the important underlying principles. Objective: To discuss the process of survey development and validation, specifically the process of construct validation. Background: Athletic training researchers frequently employ the use of…

Objective structured clinical interview training using a virtual human patient.

PubMed

Parsons, Thomas D; Kenny, Patrick; Ntuen, Celestine A; Pataki, Caroly S; Pato, Michele T; Rizzo, Albert A; St-George, Cheryl; Sugar, Jeffery

2008-01-01

Effective interview skills are a core competency for psychiatry residents and developing psychotherapists. Although schools commonly make use of standardized patients to teach interview skills, the diversity of the scenarios standardized patients can characterize is limited by availability of human actors. Further, there is the economic concern related to the time and money needed to train standardized patients. Perhaps most damaging is the "standardization" of standardized patients -- will they in fact consistently proffer psychometrically reliable and valid interactions with the training clinicians. Virtual Human Agent (VHA) technology has evolved to a point where researchers may begin developing mental health applications that make use of virtual reality patients. The work presented here is a preliminary attempt at what we believe to be a large application area. Herein we describe an ongoing study of our virtual patients (VP). We present an approach that allows novice mental health clinicians to conduct an interview with a virtual character that emulates an adolescent male with conduct disorder. This study illustrates the ways in which a variety of core research components developed at the University of Southern California facilitates the rapid development of mental health applications.

Nutrition screening tools: an analysis of the evidence.

PubMed

Skipper, Annalynn; Ferguson, Maree; Thompson, Kyle; Castellanos, Victoria H; Porcari, Judy

2012-05-01

In response to questions about tools for nutrition screening, an evidence analysis project was developed to identify the most valid and reliable nutrition screening tools for use in acute care and hospital-based ambulatory care settings. An oversight group defined nutrition screening and literature search criteria. A trained analyst conducted structured searches of the literature for studies of nutrition screening tools according to predetermined criteria. Eleven nutrition screening tools designed to detect undernutrition in patients in acute care and hospital-based ambulatory care were identified. Trained analysts evaluated articles for quality using criteria specified by the American Dietetic Association's Evidence Analysis Library. Members of the oversight group assigned quality grades to the tools based on the quality of the supporting evidence, including reliability and validity data. One tool, the NRS-2002, received a grade I, and 4 tools-the Simple Two-Part Tool, the Mini-Nutritional Assessment-Short Form (MNA-SF), the Malnutrition Screening Tool (MST), and Malnutrition Universal Screening Tool (MUST)-received a grade II. The MST was the only tool shown to be both valid and reliable for identifying undernutrition in the settings studied. Thus, validated nutrition screening tools that are simple and easy to use are available for application in acute care and hospital-based ambulatory care settings.

Building resilience with the Stress Resilience Training System: Design validation and applications.

PubMed

de Visser, Ewart J; Dorfman, Alix; Chartrand, Donald; Lamon, Jonathan; Freedy, Elan; Weltman, Gershon

2016-05-24

Resilience to stress is critical in today's military service. Past work has shown that experts handle stress in more productive ways compared to novices. Training that specifically addresses stress regulation, such as the Graduated Stress Exposure paradigm, can build individual and unit resilience as well as adaptability so that stressors trigger effective stress coping skills rather than stress injury. We developed the Stress Resilience Training System (SRTS), a product of Perceptronics Solutions Inc., to demonstrate that a software training app can provide an effective individualized method for mitigating the negative effects of situational and mission-related stress, at the same time eliciting potentially positive effects on performance. Seven separate evaluations including a usability study, controlled experiments, and field evaluations have been conducted to date. These studies have shown that the SRTS program effectively engages users to manage their stress, effectively reduces stress symptoms, and improves job performance. The SRTS system is a highly effective method for individualized training to inoculate professionals against the negative consequences of stress, while teaching them to harness its positive effects. SRTS is a technology that can be widely applied to many professions that are concerned with well-being. We discuss applications to law enforcement, athletics, personal fitness and healthcare in the Appendix.

An instrument to assess subjective task value beliefs regarding the decision to pursue postgraduate training.

PubMed

Hagemeier, Nicholas E; Murawski, Matthew M

2014-02-12

To develop and validate an instrument to assess subjective ratings of the perceived value of various postgraduate training paths followed using expectancy-value as a theoretical framework; and to explore differences in value beliefs across type of postgraduate training pursued and type of pharmacy training completed prior to postgraduate training. A survey instrument was developed to sample 4 theoretical domains of subjective task value: intrinsic value, attainment value, utility value, and perceived cost. Retrospective self-report methodology was employed to examine respondents' (N=1,148) subjective task value beliefs specific to their highest level of postgraduate training completed. Exploratory and confirmatory factor analytic techniques were used to evaluate and validate value belief constructs. Intrinsic, attainment, utility, cost, and financial value constructs resulted from exploratory factor analysis. Cross-validation resulted in a 26-item instrument that demonstrated good model fit. Differences in value beliefs were noted across type of postgraduate training pursued and pharmacy training characteristics. The Postgraduate Training Value Instrument demonstrated evidence of reliability and construct validity. The survey instrument can be used to assess value beliefs regarding multiple postgraduate training options in pharmacy and potentially inform targeted recruiting of individuals to those paths best matching their own value beliefs.

Simulation-based training for prostate surgery.

PubMed

Khan, Raheej; Aydin, Abdullatif; Khan, Muhammad Shamim; Dasgupta, Prokar; Ahmed, Kamran

2015-10-01

To identify and review the currently available simulators for prostate surgery and to explore the evidence supporting their validity for training purposes. A review of the literature between 1999 and 2014 was performed. The search terms included a combination of urology, prostate surgery, robotic prostatectomy, laparoscopic prostatectomy, transurethral resection of the prostate (TURP), simulation, virtual reality, animal model, human cadavers, training, assessment, technical skills, validation and learning curves. Furthermore, relevant abstracts from the American Urological Association, European Association of Urology, British Association of Urological Surgeons and World Congress of Endourology meetings, between 1999 and 2013, were included. Only studies related to prostate surgery simulators were included; studies regarding other urological simulators were excluded. A total of 22 studies that carried out a validation study were identified. Five validated models and/or simulators were identified for TURP, one for photoselective vaporisation of the prostate, two for holmium enucleation of the prostate, three for laparoscopic radical prostatectomy (LRP) and four for robot-assisted surgery. Of the TURP simulators, all five have demonstrated content validity, three face validity and four construct validity. The GreenLight laser simulator has demonstrated face, content and construct validities. The Kansai HoLEP Simulator has demonstrated face and content validity whilst the UroSim HoLEP Simulator has demonstrated face, content and construct validity. All three animal models for LRP have been shown to have construct validity whilst the chicken skin model was also content valid. Only two robotic simulators were identified with relevance to robot-assisted laparoscopic prostatectomy, both of which demonstrated construct validity. A wide range of different simulators are available for prostate surgery, including synthetic bench models, virtual-reality platforms, animal models, human cadavers, distributed simulation and advanced training programmes and modules. The currently validated simulators can be used by healthcare organisations to provide supplementary training sessions for trainee surgeons. Further research should be conducted to validate simulated environments, to determine which simulators have greater efficacy than others and to assess the cost-effectiveness of the simulators and the transferability of skills learnt. With surgeons investigating new possibilities for easily reproducible and valid methods of training, simulation offers great scope for implementation alongside traditional methods of training. © 2014 The Authors BJU International © 2014 BJU International Published by John Wiley & Sons Ltd.

A model for flexible tools used in minimally invasive medical virtual environments.

PubMed

Soler, Francisco; Luzon, M Victoria; Pop, Serban R; Hughes, Chris J; John, Nigel W; Torres, Juan Carlos

2011-01-01

Within the limits of current technology, many applications of a virtual environment will trade-off accuracy for speed. This is not an acceptable compromise in a medical training application where both are essential. Efficient algorithms must therefore be developed. The purpose of this project is the development and validation of a novel physics-based real time tool manipulation model, which is easy to integrate into any medical virtual environment that requires support for the insertion of long flexible tools into complex geometries. This encompasses medical specialities such as vascular interventional radiology, endoscopy, and laparoscopy, where training, prototyping of new instruments/tools and mission rehearsal can all be facilitated by using an immersive medical virtual environment. Our model recognises and uses accurately patient specific data and adapts to the geometrical complexity of the vessel in real time.

Operation of a sampling train for the analysis of environmental species in coal gasification gas-phase process streams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pochan, M.J.; Massey, M.J.

1979-02-01

This report discusses the results of actual raw product gas sampling efforts and includes: Rationale for raw product gas sampling efforts; design and operation of the CMU gas sampling train; development and analysis of a sampling train data base; and conclusions and future application of results. The results of sampling activities at the CO/sub 2/-Acceptor and Hygas pilot plants proved that: The CMU gas sampling train is a valid instrument for characterization of environmental parameters in coal gasification gas-phase process streams; depending on the particular process configuration, the CMU gas sampling train can reduce gasifier effluent characterization activity to amore » single location in the raw product gas line; and in contrast to the slower operation of the EPA SASS Train, CMU's gas sampling train can collect representative effluent data at a rapid rate (approx. 2 points per hour) consistent with the rate of change of process variables, and thus function as a tool for process engineering-oriented analysis of environmental characteristics.« less

QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371

Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.

Validation of the GreenLight™ Simulator and development of a training curriculum for photoselective vaporisation of the prostate.

PubMed

Aydin, Abdullatif; Muir, Gordon H; Graziano, Manuela E; Khan, Muhammad Shamim; Dasgupta, Prokar; Ahmed, Kamran

2015-06-01

To assess face, content and construct validity, and feasibility and acceptability of the GreenLight™ Simulator as a training tool for photoselective vaporisation of the prostate (PVP), and to establish learning curves and develop an evidence-based training curriculum. This prospective, observational and comparative study, recruited novice (25 participants), intermediate (14) and expert-level urologists (seven) from the UK and Europe at the 28th European Association of Urological Surgeons Annual Meeting 2013. A group of novices (12 participants) performed 10 sessions of subtask training modules followed by a long operative case, whereas a second group (13) performed five sessions of a given case module. Intermediate and expert groups performed all training modules once, followed by one operative case. The outcome measures for learning curves and construct validity were time to task, coagulation time, vaporisation time, average sweep speed, average laser distance, blood loss, operative errors, and instrument cost. Face and content validity, feasibility and acceptability were addressed through a quantitative survey. Construct validity was demonstrated in two of five training modules (P = 0.038; P = 0.018) and in a considerable number of case metrics (P = 0.034). Learning curves were seen in all five training modules (P < 0.001) and significant reduction in case operative time (P < 0.001) and error (P = 0.017) were seen. An evidence-based training curriculum, to help trainees acquire transferable skills, was produced using the results. This study has shown the GreenLight Simulator to be a valid and useful training tool for PVP. It is hoped that by using the training curriculum for the GreenLight Simulator, novice trainees can acquire skills and knowledge to a predetermined level of proficiency. © 2014 The Authors. BJU International © 2014 BJU International.

Validity and validation of expert (Q)SAR systems.

PubMed

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

Evaluation of the impact of deep learning architectural components selection and dataset size on a medical imaging task

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Gros, Eric

2018-03-01

Deep Learning (DL) has been successfully applied in numerous fields fueled by increasing computational power and access to data. However, for medical imaging tasks, limited training set size is a common challenge when applying DL. This paper explores the applicability of DL to the task of classifying a single axial slice from a CT exam into one of six anatomy regions. A total of 29000 images selected from 223 CT exams were manually labeled for ground truth. An additional 54 exams were labeled and used as an independent test set. The network architecture developed for this application is composed of 6 convolutional layers and 2 fully connected layers with RELU non-linear activations between each layer. Max-pooling was used after every second convolutional layer, and a softmax layer was used at the end. Given this base architecture, the effect of inclusion of network architecture components such as Dropout and Batch Normalization on network performance and training is explored. The network performance as a function of training and validation set size is characterized by training each network architecture variation using 5,10,20,40,50 and 100% of the available training data. The performance comparison of the various network architectures was done for anatomy classification as well as two computer vision datasets. The anatomy classifier accuracy varied from 74.1% to 92.3% in this study depending on the training size and network layout used. Dropout layers improved the model accuracy for all training sizes.

Virtual reality-assisted robotic surgery simulation.

PubMed

Albani, Justin M; Lee, David I

2007-03-01

For more than a decade, advancing computer technologies have allowed incorporation of virtual reality (VR) into surgical training. This has become especially important in training for laparoscopic procedures, which often are complex and leave little room for error. With the advent of robotic surgery and the development and prevalence of a commercial surgical system (da Vinci robot; Intuitive Surgical, Sunnyvale, CA), a valid VR-assisted robotic surgery simulator could minimize the steep learning curve associated with many of these complex procedures and thus enable better outcomes. To date, such simulation does not exist; however, several agencies and corporations are involved in making this dream a reality. We review the history and progress of VR simulation in surgical training, its promising applications in robotic-assisted surgery, and the remaining challenges to implementation.

A WSN-based tool for urban and industrial fire-fighting.

PubMed

De San Bernabe Clemente, Alberto; Martínez-de Dios, José Ramiro; Ollero Baturone, Aníbal

2012-11-06

This paper describes a WSN tool to increase safety in urban and industrial fire-fighting activities. Unlike most approaches, we assume that there is no preexisting WSN in the building, which involves interesting advantages but imposes some constraints. The system integrates the following functionalities: fire monitoring, firefighter monitoring and dynamic escape path guiding. It also includes a robust localization method that employs RSSI-range models dynamically trained to cope with the peculiarities of the environment. The training and application stages of the method are applied simultaneously, resulting in significant adaptability. Besides simulations and laboratory tests, a prototype of the proposed system has been validated in close-to-operational conditions.

Development of the Internet-Enabled System for Exercise Telerehabilitation and Cardiovascular Training.

PubMed

Dedov, Vadim N; Dedova, Irina V

2015-07-01

Sustained exercise training could significantly improve patient rehabilitation and management of noncommunicable diseases in the community. This study aimed to develop a universal telecare system for delivery of exercise rehabilitation and cardiovascular training services at home. An innovative bilateral leg training device was equipped with an electronic system for the ongoing measurement of training activities with the device. A single-item parameter reflecting the intensity of training was monitored using several modern telecommunication technologies. According to the application protocol, eight volunteers first tried the device for 30-60 min to determine their personal training capacity. Then, they were provided with equipment to use at home for 4 weeks. Adherence to daily training was assessed by the number of training days per week, training intensity, and duration of training sessions. The system provided reliable recording of training activities with the device using (1) long-term data logging without an ongoing connection to the computer, (2) wireless monitoring and recording of training activities on a stand-alone computer, and (3) a secure cloud-based monitoring over the Internet connection using electronic devices, including smartphones. Overall analysis of recordings and phone feedbacks to participants took only approximately 5 h for the duration of study. This study, although of a pilot nature, described the comprehensive exercise telerehabilitation system integrating mobile training equipment with personalized training protocols and remote monitoring. A single-item electronic parameter of the system usage facilitated time-effective data management. Wireless connection allowed various locations of device application and several monitoring arrangements ranging from real-time monitoring to long-term recording of exercise activities. A cloud-based software platform enabled management of multiple users at distance. Implementation of this model may facilitate both accessibility and availability of personalized exercise telerehabilitation services. Further studies would validate it in the clinical and healthcare environment.

Selling points: What cognitive abilities are tapped by casual video games?

PubMed Central

Baniqued, Pauline L.; Lee, Hyunkyu; Voss, Michelle W.; Basak, Chandramallika; Cosman, Joshua D.; DeSouza, Shanna; Severson, Joan; Salthouse, Timothy A.; Kramer, Arthur F.

2013-01-01

The idea that video games or computer-based applications can improve cognitive function has led to a proliferation of programs claiming to “train the brain.” However, there is often little scientific basis in the development of commercial training programs, and many research-based programs yield inconsistent or weak results. In this study, we sought to better understand the nature of cognitive abilities tapped by casual video games and thus reflect on their potential as a training tool. A moderately large sample of participants (n=209) played 20 web-based casual games and performed a battery of cognitive tasks. We used cognitive task analysis and multivariate statistical techniques to characterize the relationships between performance metrics. We validated the cognitive abilities measured in the task battery, examined a task analysis-based categorization of the casual games, and then characterized the relationship between game and task performance. We found that games categorized to tap working memory and reasoning were robustly related to performance on working memory and fluid intelligence tasks, with fluid intelligence best predicting scores on working memory and reasoning games. We discuss these results in the context of overlap in cognitive processes engaged by the cognitive tasks and casual games, and within the context of assessing near and far transfer. While this is not a training study, these findings provide a methodology to assess the validity of using certain games as training and assessment devices for specific cognitive abilities, and shed light on the mixed transfer results in the computer-based training literature. Moreover, the results can inform design of a more theoretically-driven and methodologically-sound cognitive training program. PMID:23246789

Selling points: What cognitive abilities are tapped by casual video games?

PubMed

Baniqued, Pauline L; Lee, Hyunkyu; Voss, Michelle W; Basak, Chandramallika; Cosman, Joshua D; Desouza, Shanna; Severson, Joan; Salthouse, Timothy A; Kramer, Arthur F

2013-01-01

The idea that video games or computer-based applications can improve cognitive function has led to a proliferation of programs claiming to "train the brain." However, there is often little scientific basis in the development of commercial training programs, and many research-based programs yield inconsistent or weak results. In this study, we sought to better understand the nature of cognitive abilities tapped by casual video games and thus reflect on their potential as a training tool. A moderately large sample of participants (n=209) played 20 web-based casual games and performed a battery of cognitive tasks. We used cognitive task analysis and multivariate statistical techniques to characterize the relationships between performance metrics. We validated the cognitive abilities measured in the task battery, examined a task analysis-based categorization of the casual games, and then characterized the relationship between game and task performance. We found that games categorized to tap working memory and reasoning were robustly related to performance on working memory and fluid intelligence tasks, with fluid intelligence best predicting scores on working memory and reasoning games. We discuss these results in the context of overlap in cognitive processes engaged by the cognitive tasks and casual games, and within the context of assessing near and far transfer. While this is not a training study, these findings provide a methodology to assess the validity of using certain games as training and assessment devices for specific cognitive abilities, and shed light on the mixed transfer results in the computer-based training literature. Moreover, the results can inform design of a more theoretically-driven and methodologically-sound cognitive training program. Copyright © 2012 Elsevier B.V. All rights reserved.

On the road to becoming a responsible leader: A simulation-based training approach for final year medical students

PubMed Central

Schmidt-Huber, Marion; Netzel, Janine; Kiesewetter, Jan

2017-01-01

Background and objective: There is a need for young physicians to take a responsible role in clinical teams, comparable to a leadership role. However, today’s medical curricula barely consider the development of leadership competencies. Acquisition of leadership skills are currently a by-product of medical education, even though it seems to be a competency relevant for physicians’ success. Therefore, an innovative leadership training program for young physicians was developed and validated. Training conceptualisation were based upon findings of critical incidents interviews (N=19) with relevant personnel (e.g. experienced doctors/nurses, residents) and upon evidence-based leadership contents focusing on ethical leadership behaviors. Method: The training consists of four sessions (3-4 hours each) and provided evidence-based lectures of leadership theory and effective leader behaviors, interactive training elements and a simulation-based approach with professional role players focusing on interprofessional collaboration with care staff. Training evaluation was assessed twice after completion of the program (N=37). Assessments included items from validated and approved evaluation instruments regarding diverse learning outcomes (satisfaction/reaction, learning, self-efficacy, and application/transfer) and transfer indicators. Furthermore, training success predictors were assessed based on stepwise regression analysis. In addition, long-term trainings effects and behavioral changes were analysed. Results: Various learning outcomes are achieved (self-reported training satisfaction, usefulness of the content and learning effects) and results show substantial transfer effects of the training contents and a strengthened awareness for the leadership role (e.g. self-confidence, ideas dealing with work-related problems in a role as responsible physician). We identified competence of trainer, training of applied tools, awareness of job expectations, and the opportunity to learn from experiences of other participants as predictors of training success. Additionally, we found long-term training effects and participants reported an increase in specific competencies, relevant for effective interprofessional collaboration (active perspective-taking, communication, conflict management, personal competencies). Conclusion: The training of leadership competencies for young physicians seems feasible to develop constructive influence strategies for a successful interprofessional collaboration in early career stages. The simulation-based approach is beneficial for residents to practice leadership behaviour in realistic job situations. PMID:28890925

On the road to becoming a responsible leader: A simulation-based training approach for final year medical students.

PubMed

Schmidt-Huber, Marion; Netzel, Janine; Kiesewetter, Jan

2017-01-01

Background and objective: There is a need for young physicians to take a responsible role in clinical teams, comparable to a leadership role. However, today's medical curricula barely consider the development of leadership competencies. Acquisition of leadership skills are currently a by-product of medical education, even though it seems to be a competency relevant for physicians' success. Therefore, an innovative leadership training program for young physicians was developed and validated. Training conceptualisation were based upon findings of critical incidents interviews ( N =19) with relevant personnel (e.g. experienced doctors/nurses, residents) and upon evidence-based leadership contents focusing on ethical leadership behaviors. Method: The training consists of four sessions (3-4 hours each) and provided evidence-based lectures of leadership theory and effective leader behaviors, interactive training elements and a simulation-based approach with professional role players focusing on interprofessional collaboration with care staff. Training evaluation was assessed twice after completion of the program ( N =37). Assessments included items from validated and approved evaluation instruments regarding diverse learning outcomes (satisfaction/reaction, learning, self-efficacy, and application/transfer) and transfer indicators. Furthermore, training success predictors were assessed based on stepwise regression analysis. In addition, long-term trainings effects and behavioral changes were analysed. Results: Various learning outcomes are achieved (self-reported training satisfaction, usefulness of the content and learning effects) and results show substantial transfer effects of the training contents and a strengthened awareness for the leadership role (e.g. self-confidence, ideas dealing with work-related problems in a role as responsible physician). We identified competence of trainer, training of applied tools, awareness of job expectations, and the opportunity to learn from experiences of other participants as predictors of training success. Additionally, we found long-term training effects and participants reported an increase in specific competencies, relevant for effective interprofessional collaboration (active perspective-taking, communication, conflict management, personal competencies). Conclusion: The training of leadership competencies for young physicians seems feasible to develop constructive influence strategies for a successful interprofessional collaboration in early career stages. The simulation-based approach is beneficial for residents to practice leadership behaviour in realistic job situations.

Training in Multiple Launch Rocket System Units

DTIC Science & Technology

1992-04-01

training conducted is Section-level training. This training is typically conducted in the garrison environment , rather than in the field. 29 4. The major... environment . Such vehicles could also be used to train on land navigation and other terrain appreciation and analysis tasks, movement techniques, and...including Batery , Platoon, and Section, of the person interviewed. Valid values for Battery are A through I. Valid codes for Platoon are 1 through 3

The Biographical Personality Interview (BPI)--a new approach to the assessment of premorbid personality in psychiatric research. Part II: Psychometric properties.

PubMed

von Zerssen, D; Barthelmes, H; Pössl, J; Black, C; Garzynski, E; Wessel, E; Hecht, H

1998-01-01

The Biographical Personality Interview (BPI) was applied to 179 subjects (158 psychiatric patients and 21 probands from the general population); 100 patients and 20 healthy controls served as a validation sample; the others had been interviewed during the training period or did not meet the inclusion criteria for the validation of the BPI. The acceptance of the interview was high, the inter-rater reliability of the ratings of premorbid personality structures ("types") varied between 0.81 and 0.88 per type. Concurrent validity of the typological constructs as assessed by means of the BPI was inferred from the intercorrelations of type scores and correlations of these scores with questionnaire data and proved to be adequate. Clinical validity of the assessment was indicated by statistically significant differences between diagnostic groups. Problems and further developments of the instrument and its application are discussed.

Update on simulation-based surgical training and assessment in ophthalmology: a systematic review.

PubMed

Thomsen, Ann Sofia S; Subhi, Yousif; Kiilgaard, Jens Folke; la Cour, Morten; Konge, Lars

2015-06-01

This study reviews the evidence behind simulation-based surgical training of ophthalmologists to determine (1) the validity of the reported models and (2) the ability to transfer skills to the operating room. Simulation-based training is established widely within ophthalmology, although it often lacks a scientific basis for implementation. We conducted a systematic review of trials involving simulation-based training or assessment of ophthalmic surgical skills among health professionals. The search included 5 databases (PubMed, EMBASE, PsycINFO, Cochrane Library, and Web of Science) and was completed on March 1, 2014. Overall, the included trials were divided into animal, cadaver, inanimate, and virtual-reality models. Risk of bias was assessed using the Cochrane Collaboration's tool. Validity evidence was evaluated using a modern validity framework (Messick's). We screened 1368 reports for eligibility and included 118 trials. The most common surgery simulated was cataract surgery. Most validity trials investigated only 1 or 2 of 5 sources of validity (87%). Only 2 trials (48 participants) investigated transfer of skills to the operating room; 4 trials (65 participants) evaluated the effect of simulation-based training on patient-related outcomes. Because of heterogeneity of the studies, it was not possible to conduct a quantitative analysis. The methodologic rigor of trials investigating simulation-based surgical training in ophthalmology is inadequate. To ensure effective implementation of training models, evidence-based knowledge of validity and efficacy is needed. We provide a useful tool for implementation and evaluation of research in simulation-based training. Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

The construct validity of session RPE during an intensive camp in young male Karate athletes.

PubMed

Padulo, Johnny; Chaabène, Helmi; Tabben, Montassar; Haddad, Monoem; Gevat, Cecilia; Vando, Stefano; Maurino, Lucio; Chaouachi, Anis; Chamari, Karim

2014-04-01

the aim of this study was to assess the validity of the session rating of perceived exertion (RPE) method and two objective HR-based methods for quantifying karate's training load (TL) in young Karatekas. eleven athletes (age 12.50±1.84 years) participated in this study. The training period/camp was performed on 5 consecutive days with two training session (s) per-day (d). Construct validity of RPE method in young Karate athletes, was studied by correlation analysis between RPE session's training load and both Edwards and Banister's training impulse score' method. significant relationship was found between inter-day (n-11 × d-5 × s-2 = 110) sessions RPE and Edwards (r values from 0.84 to 0.92 p < 0.001) and Banister's (r values from 0.84 to 0.97 p < 0.001), respectively. this study showed that session-RPE can be considered a valid method for quantifying karate's training load in young karate athletes.

Applied Virtual Reality in Reusable Launch Vehicle Design, Operations Development, and Training

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

1997-01-01

Application of Virtual Reality (VR) technology offers much promise to enhance and accelerate the development of Reusable Launch Vehicle (RLV) infrastructure and operations while simultaneously reducing developmental and operational costs. One of the primary cost areas in the RLV concept that is receiving special attention is maintenance and refurbishment operations. To produce and operate a cost effective RLV, turnaround cost must be minimized. Designing for maintainability is a necessary requirement in developing RLVs. VR can provide cost effective methods to design and evaluate components and systems for maintenance and refurbishment operations. The National Aeronautics and Space Administration (NASA)/Marshall Space Flight Center (MSFC) is beginning to utilize VR for design, operations development, and design analysis for RLVs. A VR applications program has been under development at NASA/MSFC since 1989. The objectives of the MSFC VR Applications Program are to develop, assess, validate, and utilize VR in hardware development, operations development and support, mission operations training and science training. The NASA/MSFC VR capability has also been utilized in several applications. These include: 1) the assessment of the design of the late Space Station Freedom Payload Control Area (PCA), the control room from which onboard payload operations are managed; 2) a viewing analysis of the Tethered Satellite System's (TSS) "end-of-reel" tether marking options; 3) development of a virtual mockup of the International Space Welding Experiment for science viewing analyses from the Shuttle Remote Manipulator System elbow camera and as a trainer for ground controllers; and 4) teleoperations using VR. This presentation will give a general overview of the MSFC VR Applications Program and describe the use of VR in design analyses, operations development, and training for RLVs.

Experimental validation of a numerical model for subway induced vibrations

NASA Astrophysics Data System (ADS)

Gupta, S.; Degrande, G.; Lombaert, G.

2009-04-01

This paper presents the experimental validation of a coupled periodic finite element-boundary element model for the prediction of subway induced vibrations. The model fully accounts for the dynamic interaction between the train, the track, the tunnel and the soil. The periodicity or invariance of the tunnel and the soil in the longitudinal direction is exploited using the Floquet transformation, which allows for an efficient formulation in the frequency-wavenumber domain. A general analytical formulation is used to compute the response of three-dimensional invariant or periodic media that are excited by moving loads. The numerical model is validated by means of several experiments that have been performed at a site in Regent's Park on the Bakerloo line of London Underground. Vibration measurements have been performed on the axle boxes of the train, on the rail, the tunnel invert and the tunnel wall, and in the free field, both at the surface and at a depth of 15 m. Prior to these vibration measurements, the dynamic soil characteristics and the track characteristics have been determined. The Bakerloo line tunnel of London Underground has been modelled using the coupled periodic finite element-boundary element approach and free field vibrations due to the passage of a train at different speeds have been predicted and compared to the measurements. The correspondence between the predicted and measured response in the tunnel is reasonably good, although some differences are observed in the free field. The discrepancies are explained on the basis of various uncertainties involved in the problem. The variation in the response with train speed is similar for the measurements as well as the predictions. This study demonstrates the applicability of the coupled periodic finite element-boundary element model to make realistic predictions of the vibrations from underground railways.

Electric train energy consumption modeling

DOE PAGES

Wang, Jinghui; Rakha, Hesham A.

2017-05-01

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error ofmore » 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.« less

Electric train energy consumption modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jinghui; Rakha, Hesham A.

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error ofmore » 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.« less

Adaptive local linear regression with application to printer color management.

PubMed

Gupta, Maya R; Garcia, Eric K; Chin, Erika

2008-06-01

Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

Effective prediction of biodiversity in tidal flat habitats using an artificial neural network.

PubMed

Yoo, Jae-Won; Lee, Yong-Woo; Lee, Chang-Gun; Kim, Chang-Soo

2013-02-01

Accurate predictions of benthic macrofaunal biodiversity greatly benefit the efficient planning and management of habitat restoration efforts in tidal flat habitats. Artificial neural network (ANN) prediction models for such biodiversity were developed and tested based on 13 biophysical variables, collected from 50 sites of tidal flats along the coast of Korea during 1991-2006. The developed model showed high predictions during training, cross-validation and testing. Besides the training and testing procedures, an independent dataset from a different time period (2007-2010) was used to test the robustness and practical usage of the model. High prediction on the independent dataset (r = 0.84) validated the networks proper learning of predictive relationship and its generality. Key influential variables identified by follow-up sensitivity analyses were related with topographic dimension, environmental heterogeneity, and water column properties. Study demonstrates the successful application of ANN for the accurate prediction of benthic macrofaunal biodiversity and understanding of dynamics of candidate variables. Copyright © 2012 Elsevier Ltd. All rights reserved.

76 FR 10624 - Agency Information Collection Activities; Submission for OMB Review; Comment Request; Employment...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-25

...) sponsored information collection request (ICR) titled, ``Employment and Training Data Validation Requirement... report accurate and reliable program and financial information. Data validation requires States and... Employment Program. The Employment and Training Data Validation Requirement is an information collection is...

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context.

PubMed

Storelli, L; Pagani, E; Rocca, M A; Horsfield, M A; Gallo, A; Bisecco, A; Battaglini, M; De Stefano, N; Vrenken, H; Thomas, D L; Mancini, L; Ropele, S; Enzinger, C; Preziosa, P; Filippi, M

2016-07-21

The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS. © 2016 American Society of Neuroradiology.

Evaluating information skills training in health libraries: a systematic review.

PubMed

Brettle, Alison

2007-12-01

Systematic reviews have shown that there is limited evidence to demonstrate that the information literacy training health librarians provide is effective in improving clinicians' information skills or has an impact on patient care. Studies lack measures which demonstrate validity and reliability in evaluating the impact of training. To determine what measures have been used; the extent to which they are valid and reliable; to provide guidance for health librarians who wish to evaluate the impact of their information skills training. Systematic review methodology involved searching seven databases, and personal files. Studies were included if they were about information skills training, used an objective measure to assess outcomes, and occurred in a health setting. Fifty-four studies were included in the review. Most outcome measures used in the studies were not tested for the key criteria of validity and reliability. Three tested for validity and reliability are described in more detail. Selecting an appropriate measure to evaluate the impact of training is a key factor in carrying out any evaluation. This systematic review provides guidance to health librarians by highlighting measures used in various circumstances, and those that demonstrate validity and reliability.

One Size Fits All: Evaluation of the Transferability of a New "Learning" Histologic Image Analysis Application.

PubMed

Arlt, Janine; Homeyer, André; Sänger, Constanze; Dahmen, Uta; Dirsch, Olaf

2016-01-01

Quantitative analysis of histologic slides is of importance for pathology and also to address surgical questions. Recently, a novel application was developed for the automated quantification of whole-slide images. The aim of this study was to test and validate the underlying image analysis algorithm with respect to user friendliness, accuracy, and transferability to different histologic scenarios. The algorithm splits the images into tiles of a predetermined size and identifies the tissue class of each tile. In the training procedure, the user specifies example tiles of the different tissue classes. In the subsequent analysis procedure, the algorithm classifies each tile into the previously specified classes. User friendliness was evaluated by recording training time and testing reproducibility of the training procedure of users with different background. Accuracy was determined with respect to single and batch analysis. Transferability was demonstrated by analyzing tissue of different organs (rat liver, kidney, small bowel, and spleen) and with different stainings (glutamine synthetase and hematoxylin-eosin). Users of different educational background could apply the program efficiently after a short introduction. When analyzing images with similar properties, accuracy of >90% was reached in single images as well as in batch mode. We demonstrated that the novel application is user friendly and very accurate. With the "training" procedure the application can be adapted to novel image characteristics simply by giving examples of relevant tissue structures. Therefore, it is suitable for the fast and efficient analysis of high numbers of fully digitalized histologic sections, potentially allowing "high-throughput" quantitative "histomic" analysis.

Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer

PubMed Central

Basavanhally, Ajay; Viswanath, Satish; Madabhushi, Anant

2015-01-01

Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield inaccurate and unstable classification performance. In this paper, we aim to address two common concerns in classifier selection for clinical trials: (1) predicting expected classifier performance for large datasets based on error rates calculated from smaller datasets and (2) the selection of appropriate classifiers based on expected performance for larger datasets. We present a framework for comparative evaluation of classifiers using only limited amounts of training data by using random repeated sampling (RRS) in conjunction with a cross-validation sampling strategy. Extrapolated error rates are subsequently validated via comparison with leave-one-out cross-validation performed on a larger dataset. The ability to predict error rates as dataset size increases is demonstrated on both synthetic data as well as three different computational imaging tasks: detecting cancerous image regions in prostate histopathology, differentiating high and low grade cancer in breast histopathology, and detecting cancerous metavoxels in prostate magnetic resonance spectroscopy. For each task, the relationships between 3 distinct classifiers (k-nearest neighbor, naive Bayes, Support Vector Machine) are explored. Further quantitative evaluation in terms of interquartile range (IQR) suggests that our approach consistently yields error rates with lower variability (mean IQRs of 0.0070, 0.0127, and 0.0140) than a traditional RRS approach (mean IQRs of 0.0297, 0.0779, and 0.305) that does not employ cross-validation sampling for all three datasets. PMID:25993029

[Upper limb functional assessment scale for children with Duchenne muscular dystrophy and Spinal muscular atrophy].

PubMed

Escobar, Raúl G; Lucero, Nayadet; Solares, Carmen; Espinoza, Victoria; Moscoso, Odalie; Olguín, Polín; Muñoz, Karin T; Rosas, Ricardo

2016-08-16

Duchenne muscular dystrophy (DMD) and Spinal muscular atrophy (SMA) causes significant disability and progressive functional impairment. Readily available instruments that assess functionality, especially in advanced stages of the disease, are required to monitor the progress of the disease and the impact of therapeutic interventions. To describe the development of a scale to evaluate upper limb function (UL) in patients with DMD and SMA, and describe its validation process, which includes self-training for evaluators. The development of the scale included a review of published scales, an exploratory application of a pilot scale in healthy children and those with DMD, self-training of evaluators in applying the scale using a handbook and video tutorial, and assessment of a group of children with DMD and SMA using the final scale. Reliability was assessed using Cronbach and Kendall concordance and with intra and inter-rater test-retest, and validity with concordance and factorial analysis. A high level of reliability was observed, with high internal consistency (Cronbach α=0.97), and inter-rater (Kendall W=0.96) and intra-rater concordance (r=0.97 to 0.99). The validity was demonstrated by the absence of significant differences between results by different evaluators with an expert evaluator (F=0.023, P>.5), and by the factor analysis that showed that four factors account for 85.44% of total variance. This scale is a reliable and valid tool for assessing UL functionality in children with DMD and SMA. It is also easily implementable due to the possibility of self-training and the use of simple and inexpensive materials. Copyright © 2016 Sociedad Chilena de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

PubMed

Mutasa, Simukayi; Chang, Peter D; Ruzal-Shapiro, Carrie; Ayyala, Rama

2018-02-05

Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch Dis Child 81.2:172-173, 1999) atlas. The evaluation of BAA can be a tedious and time-consuming process for the radiologist. As such, several computer-assisted detection/diagnosis (CAD) methods have been proposed for automation of BAA. Classical CAD tools have traditionally relied on hard-coded algorithmic features for BAA which suffer from a variety of drawbacks. Recently, the advent and proliferation of convolutional neural networks (CNNs) has shown promise in a variety of medical imaging applications. There have been at least two published applications of using deep learning for evaluation of bone age (Med Image Anal 36:41-51, 2017; JDI 1-5, 2017). However, current implementations are limited by a combination of both architecture design and relatively small datasets. The purpose of this study is to demonstrate the benefits of a customized neural network algorithm carefully calibrated to the evaluation of bone age utilizing a relatively large institutional dataset. In doing so, this study will aim to show that advanced architectures can be successfully trained from scratch in the medical imaging domain and can generate results that outperform any existing proposed algorithm. The training data consisted of 10,289 images of different skeletal age examinations, 8909 from the hospital Picture Archiving and Communication System at our institution and 1383 from the public Digital Hand Atlas Database. The data was separated into four cohorts, one each for male and female children above the age of 8, and one each for male and female children below the age of 10. The testing set consisted of 20 radiographs of each 1-year-age cohort from 0 to 1 years to 14-15+ years, half male and half female. The testing set included left-hand radiographs done for bone age assessment, trauma evaluation without significant findings, and skeletal surveys. A 14 hidden layer-customized neural network was designed for this study. The network included several state of the art techniques including residual-style connections, inception layers, and spatial transformer layers. Data augmentation was applied to the network inputs to prevent overfitting. A linear regression output was utilized. Mean square error was used as the network loss function and mean absolute error (MAE) was utilized as the primary performance metric. MAE accuracies on the validation and test sets for young females were 0.654 and 0.561 respectively. For older females, validation and test accuracies were 0.662 and 0.497 respectively. For young males, validation and test accuracies were 0.649 and 0.585 respectively. Finally, for older males, validation and test set accuracies were 0.581 and 0.501 respectively. The female cohorts were trained for 900 epochs each and the male cohorts were trained for 600 epochs. An eightfold cross-validation set was employed for hyperparameter tuning. Test error was obtained after training on a full data set with the selected hyperparameters. Using our proposed customized neural network architecture on our large available data, we achieved an aggregate validation and test set mean absolute errors of 0.637 and 0.536 respectively. To date, this is the best published performance on utilizing deep learning for bone age assessment. Our results support our initial hypothesis that customized, purpose-built neural networks provide improved performance over networks derived from pre-trained imaging data sets. We build on that initial work by showing that the addition of state-of-the-art techniques such as residual connections and inception architecture further improves prediction accuracy. This is important because the current assumption for use of residual and/or inception architectures is that a large pre-trained network is required for successful implementation given the relatively small datasets in medical imaging. Instead we show that a small, customized architecture incorporating advanced CNN strategies can indeed be trained from scratch, yielding significant improvements in algorithm accuracy. It should be noted that for all four cohorts, testing error outperformed validation error. One reason for this is that our ground truth for our test set was obtained by averaging two pediatric radiologist reads compared to our training data for which only a single read was used. This suggests that despite relatively noisy training data, the algorithm could successfully model the variation between observers and generate estimates that are close to the expected ground truth.

World Workshop on Oral Medicine VI: an international validation study of clinical competencies for advanced training in oral medicine.

PubMed

Steele, John C; Clark, Hadleigh J; Hong, Catherine H L; Jurge, Sabine; Muthukrishnan, Arvind; Kerr, A Ross; Wray, David; Prescott-Clements, Linda; Felix, David H; Sollecito, Thomas P

2015-08-01

To explore international consensus for the validation of clinical competencies for advanced training in Oral Medicine. An electronic survey of clinical competencies was designed. The survey was sent to and completed by identified international stakeholders during a 10-week period. To be validated, an individual competency had to achieve 90% or greater consensus to keep it in its current format. Stakeholders from 31 countries responded. High consensus agreement was achieved with 93 of 101 (92%) competencies exceeding the benchmark for agreement. Only 8 warranted further attention and were reviewed by a focus group. No additional competencies were suggested. This is the first international validated study of clinical competencies for advanced training in Oral Medicine. These validated clinical competencies could provide a model for countries developing an advanced training curriculum for Oral Medicine and also inform review of existing curricula. Copyright © 2015 Elsevier Inc. All rights reserved.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies.

PubMed

McManus, I C; Dewberry, Chris; Nicholson, Sandra; Dowell, Jonathan S; Woolf, Katherine; Potts, Henry W W

2013-11-14

Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, 'dark matter' and 'dark energy' are posited to balance various theoretical equations, so medical student selection must also have its 'dark variance', whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

PubMed Central

2013-01-01

Background Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Methods Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Results Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Conclusions Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, ‘dark matter’ and ‘dark energy’ are posited to balance various theoretical equations, so medical student selection must also have its ‘dark variance’, whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills. PMID:24229353

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

PubMed Central

2010-01-01

Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general. PMID:20144194

The Teamwork Assessment Scale: A Novel Instrument to Assess Quality of Undergraduate Medical Students' Teamwork Using the Example of Simulation-based Ward-Rounds.

PubMed

Kiesewetter, Jan; Fischer, Martin R

2015-01-01

Simulation-based teamwork trainings are considered a powerful training method to advance teamwork, which becomes more relevant in medical education. The measurement of teamwork is of high importance and several instruments have been developed for various medical domains to meet this need. To our knowledge, no theoretically-based and easy-to-use measurement instrument has been published nor developed specifically for simulation-based teamwork trainings of medical students. Internist ward-rounds function as an important example of teamwork in medicine. The purpose of this study was to provide a validated, theoretically-based instrument that is easy-to-use. Furthermore, this study aimed to identify if and when rater scores relate to performance. Based on a theoretical framework for teamwork behaviour, items regarding four teamwork components (Team Coordination, Team Cooperation, Information Exchange, Team Adjustment Behaviours) were developed. In study one, three ward-round scenarios, simulated by 69 students, were videotaped and rated independently by four trained raters. The instrument was tested for the embedded psychometric properties and factorial structure. In study two, the instrument was tested for construct validity with an external criterion with a second set of 100 students and four raters. In study one, the factorial structure matched the theoretical components but was unable to separate Information Exchange and Team Cooperation. The preliminary version showed adequate psychometric properties (Cronbach's α=.75). In study two, the instrument showed physician rater scores were more reliable in measurement than those of student raters. Furthermore, a close correlation between the scale and clinical performance as an external criteria was shown (r=.64) and the sufficient psychometric properties were replicated (Cronbach's α=.78). The validation allows for use of the simulated teamwork assessment scale in undergraduate medical ward-round trainings to reliably measure teamwork by physicians. Further studies are needed to verify the applicability of the instrument.

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies.

PubMed

David, Maria Pamela C; Concepcion, Gisela P; Padlan, Eduardo A

2010-02-08

All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.

The Teamwork Assessment Scale: A Novel Instrument to Assess Quality of Undergraduate Medical Students' Teamwork Using the Example of Simulation-based Ward-Rounds

PubMed Central

Kiesewetter, Jan; Fischer, Martin R.

2015-01-01

Background: Simulation-based teamwork trainings are considered a powerful training method to advance teamwork, which becomes more relevant in medical education. The measurement of teamwork is of high importance and several instruments have been developed for various medical domains to meet this need. To our knowledge, no theoretically-based and easy-to-use measurement instrument has been published nor developed specifically for simulation-based teamwork trainings of medical students. Internist ward-rounds function as an important example of teamwork in medicine. Purposes: The purpose of this study was to provide a validated, theoretically-based instrument that is easy-to-use. Furthermore, this study aimed to identify if and when rater scores relate to performance. Methods: Based on a theoretical framework for teamwork behaviour, items regarding four teamwork components (Team Coordination, Team Cooperation, Information Exchange, Team Adjustment Behaviours) were developed. In study one, three ward-round scenarios, simulated by 69 students, were videotaped and rated independently by four trained raters. The instrument was tested for the embedded psychometric properties and factorial structure. In study two, the instrument was tested for construct validity with an external criterion with a second set of 100 students and four raters. Results: In study one, the factorial structure matched the theoretical components but was unable to separate Information Exchange and Team Cooperation. The preliminary version showed adequate psychometric properties (Cronbach’s α=.75). In study two, the instrument showed physician rater scores were more reliable in measurement than those of student raters. Furthermore, a close correlation between the scale and clinical performance as an external criteria was shown (r=.64) and the sufficient psychometric properties were replicated (Cronbach’s α=.78). Conclusions: The validation allows for use of the simulated teamwork assessment scale in undergraduate medical ward-round trainings to reliably measure teamwork by physicians. Further studies are needed to verify the applicability of the instrument. PMID:26038684

Current status of validation for robotic surgery simulators - a systematic review.

PubMed

Abboudi, Hamid; Khan, Mohammed S; Aboumarzouk, Omar; Guru, Khurshid A; Challacombe, Ben; Dasgupta, Prokar; Ahmed, Kamran

2013-02-01

To analyse studies validating the effectiveness of robotic surgery simulators. The MEDLINE(®), EMBASE(®) and PsycINFO(®) databases were systematically searched until September 2011. References from retrieved articles were reviewed to broaden the search. The simulator name, training tasks, participant level, training duration and evaluation scoring were extracted from each study. We also extracted data on feasibility, validity, cost-effectiveness, reliability and educational impact. We identified 19 studies investigating simulation options in robotic surgery. There are five different robotic surgery simulation platforms available on the market. In all, 11 studies sought opinion and compared performance between two different groups; 'expert' and 'novice'. Experts ranged in experience from 21-2200 robotic cases. The novice groups consisted of participants with no prior experience on a robotic platform and were often medical students or junior doctors. The Mimic dV-Trainer(®), ProMIS(®), SimSurgery Educational Platform(®) (SEP) and Intuitive systems have shown face, content and construct validity. The Robotic Surgical SimulatorTM system has only been face and content validated. All of the simulators except SEP have shown educational impact. Feasibility and cost-effectiveness of simulation systems was not evaluated in any trial. Virtual reality simulators were shown to be effective training tools for junior trainees. Simulation training holds the greatest potential to be used as an adjunct to traditional training methods to equip the next generation of robotic surgeons with the skills required to operate safely. However, current simulation models have only been validated in small studies. There is no evidence to suggest one type of simulator provides more effective training than any other. More research is needed to validate simulated environments further and investigate the effectiveness of animal and cadaveric training in robotic surgery. © 2012 BJU International.

Development and validation of a questionnaire to evaluate the factors influencing training transfer among nursing professionals.

PubMed

Bai, Yangjing; Li, Jiping; Bai, Yangjuan; Ma, Weiguang; Yang, Xiangyu; Ma, Fang

2018-02-13

Most organizations invest in people for training to improve human capital and maximize profitability. Yet it is reported in industry and nursing as well that training effectiveness is constrained because of inadequate transfer of training and the underlying reasons for the transfer problem remain unknown. And there is lack of tool to measure transfer problem. The purpose of this study was to develop and validate a questionnaire to evaluate the scores of factors influencing training transfer (FITT) among nursing professionals. The questionnaire was developed by item generation through interview with nurses and literature review. The FITT was validated in terms of content validity through expert reviews. Psychometric properties of the final instrument were assessed in a sample of 960 nurses with training experiences. The content validity of the instrument were as follows: the IR was 0.8095. 51 items on the 63-item scale had I-CVIs of 1.0 and the remaining 12 items had I-CVIs of 0.88. The S-CVI/UA was 0.976 and the S-CVI/Ave was 0.977. For the exploratory step, principal axis factoring (PAF) was selected for this study. Parallel analysis was used to decide the number of factors to extract and oblimin rotation method was used. Exploratory factor analysis identified a five-factor solution including 53 items, accounting for 68.23% of the total variance. The confirmatory factor analysis showed some support for this five-factor model. The findings demonstrate high internal consistency (Cronbach's alpha = .965). This study indicates that the FITT is a valid and reliable instrument for assessing the factors influencing training transfer among nursing professionals. The FITT can be used to assess individual perceptions of catalysts and barriers to the transfer of training among nursing professionals, which can help promote training transfer and training effectiveness in the workplace.

Student peer assessment in evidence-based medicine (EBM) searching skills training: an experiment

PubMed Central

Eldredge, Jonathan D.; Bear, David G.; Wayne, Sharon J.; Perea, Paul P.

2013-01-01

Background: Student peer assessment (SPA) has been used intermittently in medical education for more than four decades, particularly in connection with skills training. SPA generally has not been rigorously tested, so medical educators have limited evidence about SPA effectiveness. Methods: Experimental design: Seventy-one first-year medical students were stratified by previous test scores into problem-based learning tutorial groups, and then these assigned groups were randomized further into intervention and control groups. All students received evidence-based medicine (EBM) training. Only the intervention group members received SPA training, practice with assessment rubrics, and then application of anonymous SPA to assignments submitted by other members of the intervention group. Results: Students in the intervention group had higher mean scores on the formative test with a potential maximum score of 49 points than did students in the control group, 45.7 and 43.5, respectively (P = 0.06). Conclusions: SPA training and the application of these skills by the intervention group resulted in higher scores on formative tests compared to those in the control group, a difference approaching statistical significance. The extra effort expended by librarians, other personnel, and medical students must be factored into the decision to use SPA in any specific educational context. Implications: SPA has not been rigorously tested, particularly in medical education. Future, similarly rigorous studies could further validate use of SPA so that librarians can optimally make use of limited contact time for information skills training in medical school curricula. PMID:24163593

The rates of protein synthesis and degradation account for the differential response of neurons to spaced and massed training protocols.

PubMed

Naqib, Faisal; Farah, Carole A; Pack, Christopher C; Sossin, Wayne S

2011-12-01

The sensory-motor neuron synapse of Aplysia is an excellent model system for investigating the biochemical changes underlying memory formation. In this system, training that is separated by rest periods (spaced training) leads to persistent changes in synaptic strength that depend on biochemical pathways that are different from those that occur when the training lacks rest periods (massed training). Recently, we have shown that in isolated sensory neurons, applications of serotonin, the neurotransmitter implicated in inducing these synaptic changes during memory formation, lead to desensitization of the PKC Apl II response, in a manner that depends on the method of application (spaced versus massed). Here, we develop a mathematical model of this response in order to gain insight into how neurons sense these different training protocols. The model was developed incrementally, and each component was experimentally validated, leading to two novel findings: First, the increased desensitization due to PKA-mediated heterologous desensitization is coupled to a faster recovery than the homologous desensitization that occurs in the absence of PKA activity. Second, the model suggests that increased spacing leads to greater desensitization due to the short half-life of a hypothetical protein, whose production prevents homologous desensitization. Thus, we predict that the effects of differential spacing are largely driven by the rates of production and degradation of proteins. This prediction suggests a powerful mechanism by which information about time is incorporated into neuronal processing.

Full immersion simulation: validation of a distributed simulation environment for technical and non-technical skills training in Urology.

PubMed

Brewin, James; Tang, Jessica; Dasgupta, Prokar; Khan, Muhammad S; Ahmed, Kamran; Bello, Fernando; Kneebone, Roger; Jaye, Peter

2015-07-01

To evaluate the face, content and construct validity of the distributed simulation (DS) environment for technical and non-technical skills training in endourology. To evaluate the educational impact of DS for urology training. DS offers a portable, low-cost simulated operating room environment that can be set up in any open space. A prospective mixed methods design using established validation methodology was conducted in this simulated environment with 10 experienced and 10 trainee urologists. All participants performed a simulated prostate resection in the DS environment. Outcome measures included surveys to evaluate the DS, as well as comparative analyses of experienced and trainee urologist's performance using real-time and 'blinded' video analysis and validated performance metrics. Non-parametric statistical methods were used to compare differences between groups. The DS environment demonstrated face, content and construct validity for both non-technical and technical skills. Kirkpatrick level 1 evidence for the educational impact of the DS environment was shown. Further studies are needed to evaluate the effect of simulated operating room training on real operating room performance. This study has shown the validity of the DS environment for non-technical, as well as technical skills training. DS-based simulation appears to be a valuable addition to traditional classroom-based simulation training. © 2014 The Authors BJU International © 2014 BJU International Published by John Wiley & Sons Ltd.

The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

PubMed

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2014-03-01

We present a novel approach to generating fragment-based molecular descriptors. The molecules are represented by labeled undirected chemical graph. Fast Frequent Subgraph Mining (FFSM) is used to find chemical-fragments (subgraphs) that occur in at least a subset of all molecules in a dataset. The collection of frequent subgraphs (FSG) forms a dataset-specific descriptors whose values for each molecule are defined by the number of times each frequent fragment occurs in this molecule. We have employed the FSG descriptors to develop variable selection k Nearest Neighbor (kNN) QSAR models of several datasets with binary target property including Maximum Recommended Therapeutic Dose (MRTD), Salmonella Mutagenicity (Ames Genotoxicity), and P-Glycoprotein (PGP) data. Each dataset was divided into training, test, and validation sets to establish the statistical figures of merit reflecting the model validated predictive power. The classification accuracies of models for both training and test sets for all datasets exceeded 75 %, and the accuracy for the external validation sets exceeded 72 %. The model accuracies were comparable or better than those reported earlier in the literature for the same datasets. Furthermore, the use of fragment-based descriptors affords mechanistic interpretation of validated QSAR models in terms of essential chemical fragments responsible for the compounds' target property. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Diagnostic flexible pharyngo-laryngoscopy: development of a procedure specific assessment tool using a Delphi methodology.

PubMed

Melchiors, Jacob; Henriksen, Mikael Johannes Vuokko; Dikkers, Frederik G; Gavilán, Javier; Noordzij, J Pieter; Fried, Marvin P; Novakovic, Daniel; Fagan, Johannes; Charabi, Birgitte W; Konge, Lars; von Buchwald, Christian

2018-05-01

Proper training and assessment of skill in flexible pharyngo-laryngoscopy are central in the education of otorhinolaryngologists. To facilitate an evidence-based approach to curriculum development in this field, a structured analysis of what constitutes flexible pharyngo-laryngoscopy is necessary. Our aim was to develop an assessment tool based on this analysis. We conducted an international Delphi study involving experts from twelve countries in five continents. Utilizing reiterative assessment, the panel defined the procedure and reached consensus (defined as 80% agreement) on the phrasing of an assessment tool. FIFTY PANELISTS COMPLETED THE DELPHI PROCESS. THE MEDIAN AGE OF THE PANELISTS WAS 44 YEARS (RANGE 33-64 YEARS). MEDIAN EXPERIENCE IN OTORHINOLARYNGOLOGY WAS 15 YEARS (RANGE 6-35 YEARS). TWENTY-FIVE WERE SPECIALIZED IN LARYNGOLOGY, 16 WERE HEAD AND NECK SURGEONS, AND NINE WERE GENERAL OTORHINOLARYNGOLOGISTS. AN ASSESSMENT TOOL WAS CREATED CONSISTING OF TWELVE DISTINCT ITEMS.: Conclusion The gathering of validity evidence for assessment of core procedural skills within Otorhinolaryngology is central to the development of a competence-based education. The use of an international Delphi panel allows for the creation of an assessment tool which is widely applicable and valid. This work allows for an informed approach to technical skills training for flexible pharyngo-laryngoscopy and as further validity evidence is gathered allows for a valid assessment of clinical performance within this important skillset.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Establishing the Validity of the Affirmative Training Inventory: Assessing the Relationship between Lesbian, Gay, and Bisexual Affirmative Training and Students' Clinical Competence

ERIC Educational Resources Information Center

Carlson, Thomas Stone; McGeorge, Christi R.; Toomey, Russell B.

2013-01-01

This study established the validity and factor structure of the Affirmative Training Inventory (ATI; T. S. Carlson, C. R. McGeorge & M. Rock, unpublished) as a measure of lesbian, gay, and bisexual (LGB) affirmative clinical training. Additionally, this study examined the latent associations among the subscales of the ATI and the Sexual…

Predictive Validity of the Air Force Officer Qualifying Test for USAF Air Battle Manager Training Performance

DTIC Science & Technology

2008-09-01

performance criteria including passing/failing training, training grades, class rank (Carretta & Ree, 2003; Olea & Ree, 1994), and several non...are consistent with prior validations of the AFOQT versus academic performance criteria in pilot (Carretta & Ree, 1995; Olea & Ree, 1994; Ree...Carretta, & Teachout, 1995)) and navigator ( Olea & Ree, 1994) training. Subsequent analyses took three different approaches to examine the

Slow walking model for children with multiple disabilities via an application of humanoid robot

NASA Astrophysics Data System (ADS)

Wang, ZeFeng; Peyrodie, Laurent; Cao, Hua; Agnani, Olivier; Watelain, Eric; Wang, HaoPing

2016-02-01

Walk training research with children having multiple disabilities is presented. Orthosis aid in walking for children with multiple disabilities such as Cerebral Palsy continues to be a clinical and technological challenge. In order to reduce pain and improve treatment strategies, an intermediate structure - humanoid robot NAO - is proposed as an assay platform to study walking training models, to be transferred to future special exoskeletons for children. A suitable and stable walking model is proposed for walk training. It would be simulated and tested on NAO. This comparative study of zero moment point (ZMP) supports polygons and energy consumption validates the model as more stable than the conventional NAO. Accordingly direction variation of the center of mass and the slopes of linear regression knee/ankle angles, the Slow Walk model faithfully emulates the gait pattern of children.

Mobile Phone Training Platform for the Nursing Staff in the Emergency Department.

PubMed

Liu, Xueqing; Cheng, Jing; Huang, Sufang

2018-05-09

Continuous education is required for nursing staff, but continuous education can be complicated for nurses working shifts, such as those in the emergency department (ED). To explore the effectiveness of the ED Training Platform of Tongji Hospital for conventional continuing education of emergency nurses. The training completion rate and training outcomes were validated. This was a retrospective study of all in-service emergency nurses working at the Tongji Medical College of Huazhong University of Science and Technology between August 2016 and August 2017. The training results of the previous year of the same group were used as controls. The platform used was an online system called JikeXuetang ( www.jkxuetang.com/ ), using the WeChat application as a carrier. The training completion rate and pass rate were compared with the control data. Among 124 nurses, the training completion rate increased from <60% to 100%, and the passing rate was 100%. Among 121 nurses, 92.5% considered that the mobile phone platform was more convenient than conventional training course; 89.7% believed it as an effective tool of learning, and intended to join public courses after completion; and 63.4% nurses expressed the wish to receive push services once or twice weekly for training course. The outcome of emergency nurse training was improved using the mobile training platform. This approach was more feasible and easier for training.

Active and Passive Haptic Training Approaches in VR Laparoscopic Surgery Training.

PubMed

Marutani, Takafumi; Kato, Toma; Tagawa, Kazuyoshi; Tanaka, Hiromi T; Komori, Masaru; Kurumi, Yoshimasa; Morikawa, Shigehiro

2016-01-01

Laparoscopic surgery has become a widely performed surgery as it is one of the most common minimally invasive surgeries. Doctors perform the surgery by manipulating thin and long surgical instruments precisely with the assistance of laparoscopic video with limited field of view. The power control of the instruments' tip is especially very important, because excessive power may damage internal organs. The training of this surgical technique is mainly supervised by an expert in hands-on coaching program. However, it is difficult for the experts to spend sufficient time for coaching. Therefore, we aim to teach the expert's hand movements in laparoscopic surgery to trainees using VR-based simulator, which is equipped with a guidance force display device. To realize the system, we propose two haptic training approaches for transferring the expert's hand movements to the trainee. One is active training, and the other is passive training. The former approach shows the expert's movements only when the trainee makes large errors while the latter shows the expert's movements continuously. In this study, we validate the applicability of these approaches through tasks in VR laparoscopic surgery training simulator, and identify the differences between these approaches.

Validity of worksheet-based guided inquiry and mind mapping for training students’ creative thinking skills

NASA Astrophysics Data System (ADS)

Susanti, L. B.; Poedjiastoeti, S.; Taufikurohmah, T.

2018-04-01

The purpose of this study is to explain the validity of guided inquiry and mind mapping-based worksheet that has been developed in this study. The worksheet implemented the phases of guided inquiry teaching models in order to train students’ creative thinking skills. The creative thinking skills which were trained in this study included fluency, flexibility, originality and elaboration. The types of validity used in this study included content and construct validity. The type of this study is development research with Research and Development (R & D) method. The data of this study were collected using review and validation sheets. Sources of the data were chemistry lecturer and teacher. The data is the analyzed descriptively. The results showed that the worksheet is very valid and could be used as a learning media with the percentage of validity ranged from 82.5%-92.5%.

Comparison of machine learned approaches for thyroid nodule characterization from shear wave elastography images

NASA Astrophysics Data System (ADS)

Pereira, Carina; Dighe, Manjiri; Alessio, Adam M.

2018-02-01

Various Computer Aided Diagnosis (CAD) systems have been developed that characterize thyroid nodules using the features extracted from the B-mode ultrasound images and Shear Wave Elastography images (SWE). These features, however, are not perfect predictors of malignancy. In other domains, deep learning techniques such as Convolutional Neural Networks (CNNs) have outperformed conventional feature extraction based machine learning approaches. In general, fully trained CNNs require substantial volumes of data, motivating several efforts to use transfer learning with pre-trained CNNs. In this context, we sought to compare the performance of conventional feature extraction, fully trained CNNs, and transfer learning based, pre-trained CNNs for the detection of thyroid malignancy from ultrasound images. We compared these approaches applied to a data set of 964 B-mode and SWE images from 165 patients. The data were divided into 80% training/validation and 20% testing data. The highest accuracies achieved on the testing data for the conventional feature extraction, fully trained CNN, and pre-trained CNN were 0.80, 0.75, and 0.83 respectively. In this application, classification using a pre-trained network yielded the best performance, potentially due to the relatively limited sample size and sub-optimal architecture for the fully trained CNN.

Development and application of neuropsychology in Hong Kong: implications of its value and future advancement.

PubMed

Chan, Agnes S; Sze, Sophia L; Cheung, Mei-Chun; Han, Yvonne M Y

2016-11-01

To review the development, application, and value of neuropsychology, and the standard education and training pathway for neuropsychologists or clinical neuropsychologists in Hong Kong. The information provided here was gathered via a literature review of the status of neuropsychology and the validity of commonly adopted neuropsychological tests in Hong Kong. Additional details were acquired via the internet about local tertiary education curricula and the related requirements, the availability of professional associations for licensure or board certification, and relevant statistics/surveys conducted by the government. Some information about the clinical practice of neuropsychology was collected through personal communication with local clinical psychologists. The development of neuropsychology in Hong Kong over the past 20 years is rapid and productive, given the increasing application of advanced neuroimaging techniques, neuropsychological tests, and opportunities for exchanging up-to-date neuropsychological knowledge and professional training through international conferences, workshops, and seminars. Given that neuropsychology services are often provided by clinical psychologists who are master's degree graduates in clinical psychology, the relatively limited training in neuropsychological knowledge and skills and the lack of division for membership or mandatory registration as a neuropsychologist/clinical neuropsychologist may have an impact on the quality of clinical neuropsychological services and the development of this specialty. These findings signify a need for further improvement or refinement of educational and training pathways for neuropsychologist or clinical neuropsychologist along with the recognition of its value in clinical practice through registration of different disciplines of psychology in Hong Kong.

Effectiveness of evidence-based medicine training for undergraduate students at a Chinese Military Medical University: a self-controlled trial.

PubMed

Ma, Xiangyu; Xu, Bin; Liu, Qingyun; Zhang, Yao; Xiong, Hongyan; Li, Yafei

2014-07-04

To evaluate the effect of the integration of evidence-based medicine (EBM) into medical curriculum by measuring undergraduate medical students' EBM knowledge, attitudes, personal application, and anticipated future use. A self-controlled trial was conducted with 251 undergraduate students at a Chinese Military Medical University, using a validated questionnaire regarding the students' evidence-based practice (EBP) about knowledge (EBP-K), attitude (EBP-A), personal application (EBP-P), and future anticipated use (EBP-F). The educational intervention was a 20-hour EBM course formally included in the university's medical curriculum, combining lectures with small group discussion and student-teacher exchange sessions. Data were analyzed using paired t-tests to test the significance of the difference between a before and after comparison. The difference between the pre- and post-training scores were statistically significant for EBP-K, EBP-A, EBP-P, and EBP-F. The scores for EBP-P showed the most pronounced percentage change after EBM training (48.97 ± 8.6%), followed by EBP-A (20.83 ± 2.1%), EBP-K (19.21 ± 3.2%), and EBP-F (17.82 ± 5.7%). Stratified analyses by gender, and program subtypes did not result in any significant changes to the results. The integration of EBM into the medical curriculum improved undergraduate medical students' EBM knowledge, attitudes, personal application, and anticipated future use. A well-designed EBM training course and objective outcome measurements are necessary to ensure the optimum learning opportunity for students.

A WSN-Based Tool for Urban and Industrial Fire-Fighting

PubMed Central

De San Bernabe Clemente, Alberto; Dios, José Ramiro Martínez-de; Baturone, Aníbal Ollero

2012-01-01

This paper describes a WSN tool to increase safety in urban and industrial fire-fighting activities. Unlike most approaches, we assume that there is no preexisting WSN in the building, which involves interesting advantages but imposes some constraints. The system integrates the following functionalities: fire monitoring, firefighter monitoring and dynamic escape path guiding. It also includes a robust localization method that employs RSSI-range models dynamically trained to cope with the peculiarities of the environment. The training and application stages of the method are applied simultaneously, resulting in significant adaptability. Besides simulations and laboratory tests, a prototype of the proposed system has been validated in close-to-operational conditions. PMID:23202198

Face validity, construct validity and training benefits of a virtual reality TURP simulator.

PubMed

Bright, Elizabeth; Vine, Samuel; Wilson, Mark R; Masters, Rich S W; McGrath, John S

2012-01-01

To assess face validity, construct validity and the training benefits of a virtual reality TURP simulator. 11 novices (no TURP experience) and 7 experts (>200 TURP's) completed a virtual reality median lobe prostate resection task on the TURPsim™ (Simbionix USA Corp., Cleveland, OH). Performance indicators (percentage of prostate resected (PR), percentage of capsular resection (CR) and time diathermy loop active without tissue contact (TAWC) were recorded via the TURPsim™ and compared between novices and experts to assess construct validity. Verbal comments provided by experts following task completion were used to assess face validity. Repeated attempts of the task by the novices were analysed to assess the training benefits of the TURPsim™. Experts resected a significantly greater percentage of prostate per minute (p < 0.01) and had significantly less active diathermy time without tissue contact (p < 0.01) than novices. After practice, novices were able to perform the simulation more effectively, with significant improvement in all measured parameters. Improvement in performance was noted in novices following repetitive training, as evidenced by improved TAWC scores that were not significantly different from the expert group (p = 0.18). This study has established face and construct validity for the TURPsim™. The potential benefit in using this tool to train novices has also been demonstrated. Copyright © 2012 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Passive haptics in a knee arthroscopy simulator: is it valid for core skills training?

PubMed

McCarthy, Avril D; Moody, Louise; Waterworth, Alan R; Bickerstaff, Derek R

2006-01-01

Previous investigation of a cost-effective virtual reality arthroscopic training system, the Sheffield Knee Arthroscopy Training System (SKATS), indicated the desirability of including haptic feedback. A formal task analysis confirmed the importance of knee positioning as a core skill for trainees learning to navigate the knee arthroscopically. The system cost and existing limb interface, which permits knee positioning, would be compromised by the addition of commercial active haptic devices available currently. The validation results obtained when passive haptic feedback (resistance provided by physical structures) is provided indicate that SKATS has construct, predictive and face validity for navigation and triangulation training. When tested using SKATS, experienced surgeons (n = 11) performed significantly faster, located significantly more pathologies, and showed significantly shorter arthroscope path lengths than a less experienced surgeon cohort (n = 12). After SKATS training sessions, novices (n = 3) showed significant improvements in: task completion time, shorter arthroscope path lengths, shorter probe path lengths, and fewer arthroscope tip contacts. Main improvements occurred after the first two practice sessions, indicating rapid familiarization and a training effect. Feedback from questionnaires completed by orthopaedic surgeons indicates that the system has face validity for its remit of basic arthroscopic training.

Field validation of the dnph method for aldehydes and ketones. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Workman, G.S.; Steger, J.L.

1996-04-01

A stationary source emission test method for selected aldehydes and ketones has been validated. The method employs a sampling train with impingers containing 2,4-dinitrophenylhydrazine (DNPH) to derivatize the analytes. The resulting hydrazones are recovered and analyzed by high performance liquid chromatography. Nine analytes were studied; the method was validated for formaldehyde, acetaldehyde, propionaldehyde, acetophenone and isophorone. Acrolein, menthyl ethyl ketone, menthyl isobutyl ketone, and quinone did not meet the validation criteria. The study employed the validation techniques described in EPA method 301, which uses train spiking to determine bias, and collocated sampling trains to determine precision. The studies were carriedmore » out at a plywood veneer dryer and a polyester manufacturing plant.« less

The construct validity of session RPE during an intensive camp in young male Karate athletes

PubMed Central

Padulo, Johnny; Chaabène, Helmi; Tabben, Montassar; Haddad, Monoem; Gevat, Cecilia; Vando, Stefano; Maurino, Lucio; Chaouachi, Anis; Chamari, Karim

2014-01-01

Summary Background: the aim of this study was to assess the validity of the session rating of perceived exertion (RPE) method and two objective HR-based methods for quantifying karate’s training load (TL) in young Karatekas. Methods: eleven athletes (age 12.50±1.84 years) participated in this study. The training period/camp was performed on 5 consecutive days with two training session (s) per-day (d). Construct validity of RPE method in young Karate athletes, was studied by correlation analysis between RPE session’s training load and both Edwards and Banister’s training impulse score’ method. Results: significant relationship was found between inter-day (n-11 × d-5 × s-2 = 110) sessions RPE and Edwards (r values from 0.84 to 0.92 p < 0.001) and Banister’s (r values from 0.84 to 0.97 p < 0.001), respectively Conclusion: this study showed that session-RPE can be considered a valid method for quantifying karate’s training load in young karate athletes. PMID:25332921

Application of a Cognitive Model for Army Training: Handbook for Strategic Intelligence Analysis

DTIC Science & Technology

1984-10-01

sources of uncertainty. By reducing uncertainty, information, in accordance with consumers of ITAC products are able to requirements validated by the...plan would have to beil designed and integrated with these * Know the envronment.I goals in mind. According to the SBDP, *Dvlpamtoia prah .4Soviet...political climate, and the cultural history each of which can revise and append of the country or countries implicated in the message according to

Pilot Validation Study of the European Association of Urology Robotic Training Curriculum.

PubMed

Volpe, Alessandro; Ahmed, Kamran; Dasgupta, Prokar; Ficarra, Vincenzo; Novara, Giacomo; van der Poel, Henk; Mottrie, Alexandre

2015-08-01

The development of structured and validated training curricula is one of the current priorities in robot-assisted urological surgery. To establish the feasibility, acceptability, face validity, and educational impact of a structured training curriculum for robot-assisted radical prostatectomy (RARP), and to assess improvements in performance and ability to perform RARP after completion of the curriculum. A 12-wk training curriculum was developed based on an expert panel discussion and used to train ten fellows from major European teaching institutions. The curriculum included: (1) e-learning, (2) 1 wk of structured simulation-based training (virtual reality synthetic, animal, and cadaveric platforms), and (3) supervised modular training for RARP. The feasibility, acceptability, face validity, and educational impact were assessed using quantitative surveys. Improvement in the technical skills of participants over the training period was evaluated using the inbuilt validated assessment metrics on the da Vinci surgical simulator (dVSS). A final RARP performed by fellows on completion of their training was assessed using the Global Evaluative Assessment of Robotic Skills (GEARS) score and generic and procedure-specific scoring criteria. The median baseline experience of participants as console surgeon was 4 mo (interquartile range [IQR] 0-6.5 mo). All participants completed the curriculum and were involved in a median of 18 RARPs (IQR 14-36) during modular training. The overall score for dVSS tasks significantly increased over the training period (p<0.001-0.005). At the end of the curriculum, eight fellows (80%) were deemed able by their mentors to perform a RARP independently, safely, and effectively. At assessment of the final RARP, the participants achieved an average score ≥4 (scale 1-5) for all domains using the GEARS scale and an average score >10 (scale 4-16) for all procedural steps using a generic dedicated scoring tool. In performance comparison using this scoring tool, the experts significantly outperformed the fellows (mean score for all steps 13.6 vs 11). The European robot-assisted urologic training curriculum is acceptable, valid, and effective for training in RARP. This study shows that a 12-wk structured training program including simulation-based training and mentored training in the operating room allows surgeons with limited robotic experience to increase their robotic skills and their ability to perform the surgical steps of robot-assisted radical prostatectomy. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Validation of a novel basic virtual reality simulator, the LAP-X, for training basic laparoscopic skills.

PubMed

Kawaguchi, Koji; Egi, Hiroyuki; Hattori, Minoru; Sawada, Hiroyuki; Suzuki, Takahisa; Ohdan, Hideki

2014-10-01

Virtual reality surgical simulators are becoming popular as a means of providing trainees with an opportunity to practice laparoscopic skills. The Lap-X (Epona Medical, Rotterdam, the Netherlands) is a novel VR simulator for training basic skills in laparoscopic surgery. The objective of this study was to validate the LAP-X laparoscopic virtual reality simulator by assessing the face and construct validity in order to determine whether the simulator is adequate for basic skills training. The face and content validity were evaluated using a structured questionnaire. To assess the construct validity, the participants, nine expert surgeons (median age: 40 (32-45)) (>100 laparoscopic procedures) and 11 novices performed three basic laparoscopic tasks using the Lap-X. The participants reported a high level of content validity. No significant differences were found between the expert surgeons and the novices (Ps > 0.246). The performance of the expert surgeons on the three tasks was significantly better than that of the novices in all parameters (Ps < 0.05). This study demonstrated the face, content and construct validity of the Lap-X. The Lap-X holds real potential as a home and hospital training device.

Proficiency training on a virtual reality robotic surgical skills curriculum.

PubMed

Bric, Justin; Connolly, Michael; Kastenmeier, Andrew; Goldblatt, Matthew; Gould, Jon C

2014-12-01

The clinical application of robotic surgery is increasing. The skills necessary to perform robotic surgery are unique from those required in open and laparoscopic surgery. A validated laparoscopic surgical skills curriculum (Fundamentals of Laparoscopic Surgery or FLS™) has transformed the way surgeons acquire laparoscopic skills. There is a need for a similar skills training and assessment tool for robotic surgery. Our research group previously developed and validated a robotic training curriculum in a virtual reality (VR) simulator. We hypothesized that novice robotic surgeons could achieve proficiency levels defined by more experienced robotic surgeons on the VR robotic curriculum, and that this would result in improved performance on the actual daVinci Surgical System™. 25 medical students with no prior robotic surgery experience were recruited. Prior to VR training, subjects performed 2 FLS tasks 3 times each (Peg Transfer, Intracorporeal Knot Tying) using the daVinci Surgical System™ docked to a video trainer box. Task performance for the FLS tasks was scored objectively. Subjects then practiced on the VR simulator (daVinci Skills Simulator) until proficiency levels on all 5 tasks were achieved before completing a post-training assessment of the 2 FLS tasks on the daVinci Surgical System™ in the video trainer box. All subjects to complete the study (1 dropped out) reached proficiency levels on all VR tasks in an average of 71 (± 21.7) attempts, accumulating 164.3 (± 55.7) minutes of console training time. There was a significant improvement in performance on the robotic FLS tasks following completion of the VR training curriculum. Novice robotic surgeons are able to attain proficiency levels on a VR simulator. This leads to improved performance in the daVinci surgical platform on simulated tasks. Training to proficiency on a VR robotic surgery simulator is an efficient and viable method for acquiring robotic surgical skills.

Development and Validation of the Musical Ear Training Assessment (META)

ERIC Educational Resources Information Center

Wolf, Anna; Kopiez, Reinhard

2018-01-01

In the following study, we have developed an assessment instrument for the practice-dependent skill of analytical hearing following a strict test theoretical validation, resulting in the Musical Ear Training Assessment (META). By means of three pilot studies, a developmental study, and a validation study, we verified a one-dimensional test model…

Sample selection via angular distance in the space of the arguments of an artificial neural network

NASA Astrophysics Data System (ADS)

Fernández Jaramillo, J. M.; Mayerle, R.

2018-05-01

In the construction of an artificial neural network (ANN) a proper data splitting of the available samples plays a major role in the training process. This selection of subsets for training, testing and validation affects the generalization ability of the neural network. Also the number of samples has an impact in the time required for the design of the ANN and the training. This paper introduces an efficient and simple method for reducing the set of samples used for training a neural network. The method reduces the required time to calculate the network coefficients, while keeping the diversity and avoiding overtraining the ANN due the presence of similar samples. The proposed method is based on the calculation of the angle between two vectors, each one representing one input of the neural network. When the angle formed among samples is smaller than a defined threshold only one input is accepted for the training. The accepted inputs are scattered throughout the sample space. Tidal records are used to demonstrate the proposed method. The results of a cross-validation show that with few inputs the quality of the outputs is not accurate and depends on the selection of the first sample, but as the number of inputs increases the accuracy is improved and differences among the scenarios with a different starting sample have and important reduction. A comparison with the K-means clustering algorithm shows that for this application the proposed method with a smaller number of samples is producing a more accurate network.

Physics in the Courtroom

NASA Astrophysics Data System (ADS)

Vosk, Ted

2011-10-01

The principles, methods and technologies of physics can provide a powerful tool for the discovery of truth in the criminal justice system. Accordingly, physics based forensic evidence is relied upon in criminal prosecutions around the country every day. Infrared spectroscopy for the determination of the alcohol concentration of an individual's breath, force, momentum and multi-body dynamics for purposes of accident reconstruction and the basic application of sound metrological (measurement) practices constitute but a few examples. In many cases, a jury's determination of guilt or innocence, upon which the liberty of a Citizen rests, may in fact be determined by such evidence. Society may well place a high degree of confidence in the integrity of verdicts so obtained when ``the physics'' has been applied in a valid manner. Unfortunately, as concluded by the National Academy of Sciences, ``The law's greatest dilemma in its heavy reliance on forensic evidence--concerns the question of whether---and to what extent-- -there is science in any given `forensic science' discipline.'' Even where valid physical principles are relied upon, their improper application by forensic practitioners who have little physics training, background and/or understanding calls into question the validity of results or conclusions obtained. This presentation provides examples of the application of physics in the courtroom, where problems have been discovered and how they can be addressed by the physics community.

Application of computational methods for the design of BACE-1 inhibitors: validation of in silico modelling.

PubMed

Bajda, Marek; Jończyk, Jakub; Malawska, Barbara; Filipek, Sławomir

2014-03-24

β-Secretase (BACE-1) constitutes an important target for search of anti-Alzheimer's drugs. The first inhibitors of this enzyme were peptidic compounds with high molecular weight and low bioavailability. Therefore, the search for new efficient non-peptidic inhibitors has been undertaken by many scientific groups. We started our work from the development of in silico methodology for the design of novel BACE-1 ligands. It was validated on the basis of crystal structures of complexes with inhibitors, redocking, cross-docking and training/test sets of reference ligands. The presented procedure of assessment of the novel compounds as β-secretase inhibitors could be widely used in the design process.

Transfer of training for aerospace operations: How to measure, validate, and improve it

NASA Technical Reports Server (NTRS)

Cohen, Malcolm M.

1993-01-01

It has been a commonly accepted practice to train pilots and astronauts in expensive, extremely sophisticated, high fidelity simulators, with as much of the real-world feel and response as possible. High fidelity and high validity have often been assumed to be inextricably interwoven, although this assumption may not be warranted. The Project Mercury rate-damping task on the Naval Air Warfare Center's Human Centrifuge Dynamic Flight Simulator, the shuttle landing task on the NASA-ARC Vertical Motion Simulator, and the almost complete acceptance by the airline industry of full-up Boeing 767 flight simulators, are just a few examples of this approach. For obvious reasons, the classical models of transfer of training have never been adequately evaluated in aerospace operations, and there have been few, if any, scientifically valid replacements for the classical models. This paper reviews some of the earlier work involving transfer of training in aerospace operations, and discusses some of the methods by which appropriate criteria for assessing the validity of training may be established.

Construct validity of the ovine model in endoscopic sinus surgery training.

PubMed

Awad, Zaid; Taghi, Ali; Sethukumar, Priya; Tolley, Neil S

2015-03-01

To demonstrate construct validity of the ovine model as a tool for training in endoscopic sinus surgery (ESS). Prospective, cross-sectional evaluation study. Over 18 consecutive months, trainees and experts were evaluated in their ability to perform a range of tasks (based on previous face validation and descriptive studies conducted by the same group) relating to ESS on the sheep-head model. Anonymized randomized video recordings of the above were assessed by two independent and blinded assessors. A validated assessment tool utilizing a five-point Likert scale was employed. Construct validity was calculated by comparing scores across training levels and experts using mean and interquartile range of global and task-specific scores. Subgroup analysis of the intermediate group ascertained previous experience. Nonparametric descriptive statistics were used, and analysis was carried out using SPSS version 21 (IBM, Armonk, NY). Reliability of the assessment tool was confirmed. The model discriminated well between different levels of expertise in global and task-specific scores. A positive correlation was noted between year in training and both global and task-specific scores (P < .001). Experience of the intermediate group was variable, and the number of ESS procedures performed under supervision had the highest impact on performance. This study describes an alternative model for ESS training and assessment. It is also the first to demonstrate construct validity of the sheep-head model for ESS training. © 2014 The American Laryngological, Rhinological and Otological Society, Inc.

A pre-trained convolutional neural network based method for thyroid nodule diagnosis.

PubMed

Ma, Jinlian; Wu, Fa; Zhu, Jiang; Xu, Dong; Kong, Dexing

2017-01-01

In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, we propose a hybrid method for thyroid nodule diagnosis, which is a fusion of two pre-trained convolutional neural networks (CNNs) with different convolutional layers and fully-connected layers. Firstly, the two networks pre-trained with ImageNet database are separately trained. Secondly, we fuse feature maps learned by trained convolutional filters, pooling and normalization operations of the two CNNs. Finally, with the fused feature maps, a softmax classifier is used to diagnose thyroid nodules. The proposed method is validated on 15,000 ultrasound images collected from two local hospitals. Experiment results show that the proposed CNN based methods can accurately and effectively diagnose thyroid nodules. In addition, the fusion of the two CNN based models lead to significant performance improvement, with an accuracy of 83.02%±0.72%. These demonstrate the potential clinical applications of this method. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and validation of immune dysfunction score to predict 28-day mortality of sepsis patients

PubMed Central

Fang, Wen-Feng; Douglas, Ivor S.; Chen, Yu-Mu; Lin, Chiung-Yu; Kao, Hsu-Ching; Fang, Ying-Tang; Huang, Chi-Han; Chang, Ya-Ting; Huang, Kuo-Tung; Wang, Yi-His; Wang, Chin-Chou

2017-01-01

Background Sepsis-induced immune dysfunction ranging from cytokines storm to immunoparalysis impacts outcomes. Monitoring immune dysfunction enables better risk stratification and mortality prediction and is mandatory before widely application of immunoadjuvant therapies. We aimed to develop and validate a scoring system according to patients’ immune dysfunction status for 28-day mortality prediction. Methods A prospective observational study from a cohort of adult sepsis patients admitted to ICU between August 2013 and June 2016 at Kaohsiung Chang Gung Memorial Hospital in Taiwan. We evaluated immune dysfunction status through measurement of baseline plasma Cytokine levels, Monocyte human leukocyte-DR expression by flow cytometry, and stimulated immune response using post LPS stimulated cytokine elevation ratio. An immune dysfunction score was created for 28-day mortality prediction and was validated. Results A total of 151 patients were enrolled. Data of the first consecutive 106 septic patients comprised the training cohort, and of other 45 patients comprised the validation cohort. Among the 106 patients, 21 died and 85 were still alive on day 28 after ICU admission. (mortality rate, 19.8%). Independent predictive factors revealed via multivariate logistic regression analysis included segmented neutrophil-to-monocyte ratio, granulocyte-colony stimulating factor, interleukin-10, and monocyte human leukocyte antigen-antigen D–related levels, all of which were selected to construct the score, which predicted 28-day mortality with area under the curve of 0.853 and 0.789 in the training and validation cohorts, respectively. Conclusions The immune dysfunction scoring system developed here included plasma granulocyte-colony stimulating factor level, interleukin-10 level, serum segmented neutrophil-to-monocyte ratio, and monocyte human leukocyte antigen-antigen D–related expression appears valid and reproducible for predicting 28-day mortality. PMID:29073262

A review of the available urology skills training curricula and their validation.

PubMed

Shepherd, William; Arora, Karan Singh; Abboudi, Hamid; Shamim Khan, Mohammed; Dasgupta, Prokar; Ahmed, Kamran

2014-01-01

The transforming field of urological surgery continues to demand development of novel training devices and curricula for its trainees. Contemporary trainees have to balance workplace demands while overcoming the cognitive barriers of acquiring skills in rapidly multiplying and advancing surgical techniques. This article provides a brief review of the process involved in developing a surgical curriculum and the current status of real and simulation-based curricula in the 4 subgroups of urological surgical practice: open, laparoscopic, endoscopic, and robotic. An informal literature review was conducted to provide a snapshot into the variety of simulation training tools available for technical and nontechnical urological surgical skills within all subgroups of urological surgery using the following keywords: "urology, surgery, training, curriculum, validation, non-technical skills, technical skills, LESS, robotic, laparoscopy, animal models." Validated training tools explored in research were tabulated and summarized. A total of 20 studies exploring validated training tools were identified. Huge variation was noticed in the types of validity sought by researchers and suboptimal incorporation of these tools into curricula was noted across the subgroups of urological surgery. The following key recommendations emerge from the review: adoption of simulation-based curricula in training; better integration of dedicated training time in simulated environments within a trainee's working hours; better incentivization for educators and assessors to improvise, research, and deliver teaching using the technologies available; and continued emphasis on developing nontechnical skills in tandem with technical operative skills. © 2013 Published by Association of Program Directors in Surgery on behalf of Association of Program Directors in Surgery.

Can virtual reality simulation be used for advanced bariatric surgical training?

PubMed

Lewis, Trystan M; Aggarwal, Rajesh; Kwasnicki, Richard M; Rajaretnam, Niro; Moorthy, Krishna; Ahmed, Ahmed; Darzi, Ara

2012-06-01

Laparoscopic bariatric surgery is a safe and effective way of treating morbid obesity. However, the operations are technically challenging and training opportunities for junior surgeons are limited. This study aims to assess whether virtual reality (VR) simulation is an effective adjunct for training and assessment of laparoscopic bariatric technical skills. Twenty bariatric surgeons of varying experience (Five experienced, five intermediate, and ten novice) were recruited to perform a jejuno-jejunostomy on both cadaveric tissue and on the bariatric module of the Lapmentor VR simulator (Simbionix Corporation, Cleveland, OH). Surgical performance was assessed using validated global rating scales (GRS) and procedure specific video rating scales (PSRS). Subjects were also questioned about the appropriateness of VR as a training tool for surgeons. Construct validity of the VR bariatric module was demonstrated with a significant difference in performance between novice and experienced surgeons on the VR jejuno-jejunostomy module GRS (median 11-15.5; P = .017) and PSRS (median 11-13; P = .003). Content validity was demonstrated with surgeons describing the VR bariatric module as useful and appropriate for training (mean Likert score 4.45/7) and they would highly recommend VR simulation to others for bariatric training (mean Likert score 5/7). Face and concurrent validity were not established. This study shows that the bariatric module on a VR simulator demonstrates construct and content validity. VR simulation appears to be an effective method for training of advanced bariatric technical skills for surgeons at the start of their bariatric training. However, assessment of technical skills should still take place on cadaveric tissue. Copyright © 2012. Published by Mosby, Inc.

Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data

PubMed Central

Prieto, Sandra P.; Lai, Keith K.; Laryea, Jonathan A.; Mizell, Jason S.; Muldoon, Timothy J.

2016-01-01

Abstract. Qualitative screening for colorectal polyps via fiber bundle microendoscopy imaging has shown promising results, with studies reporting high rates of sensitivity and specificity, as well as low interobserver variability with trained clinicians. A quantitative image quality control and image feature extraction algorithm (QFEA) was designed to lessen the burden of training and provide objective data for improved clinical efficacy of this method. After a quantitative image quality control step, QFEA extracts field-of-view area, crypt area, crypt circularity, and crypt number per image. To develop and validate this QFEA, a training set of microendoscopy images was collected from freshly resected porcine colon epithelium. The algorithm was then further validated on ex vivo image data collected from eight human subjects, selected from clinically normal appearing regions distant from grossly visible tumor in surgically resected colorectal tissue. QFEA has proven flexible in application to both mosaics and individual images, and its automated crypt detection sensitivity ranges from 71 to 94% despite intensity and contrast variation within the field of view. It also demonstrates the ability to detect and quantify differences in grossly normal regions among different subjects, suggesting the potential efficacy of this approach in detecting occult regions of dysplasia. PMID:27335893

Designing a robust activity recognition framework for health and exergaming using wearable sensors.

PubMed

Alshurafa, Nabil; Xu, Wenyao; Liu, Jason J; Huang, Ming-Chun; Mortazavi, Bobak; Roberts, Christian K; Sarrafzadeh, Majid

2014-09-01

Detecting human activity independent of intensity is essential in many applications, primarily in calculating metabolic equivalent rates and extracting human context awareness. Many classifiers that train on an activity at a subset of intensity levels fail to recognize the same activity at other intensity levels. This demonstrates weakness in the underlying classification method. Training a classifier for an activity at every intensity level is also not practical. In this paper, we tackle a novel intensity-independent activity recognition problem where the class labels exhibit large variability, the data are of high dimensionality, and clustering algorithms are necessary. We propose a new robust stochastic approximation framework for enhanced classification of such data. Experiments are reported using two clustering techniques, K-Means and Gaussian Mixture Models. The stochastic approximation algorithm consistently outperforms other well-known classification schemes which validate the use of our proposed clustered data representation. We verify the motivation of our framework in two applications that benefit from intensity-independent activity recognition. The first application shows how our framework can be used to enhance energy expenditure calculations. The second application is a novel exergaming environment aimed at using games to reward physical activity performed throughout the day, to encourage a healthy lifestyle.

A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

PubMed

Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert

2009-01-01

The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction.

PubMed

Hamadache, Mabrouk; Benkortbi, Othmane; Hanini, Salah; Amrane, Abdeltif; Khaouane, Latifa; Si Moussa, Cherif

2016-02-13

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q(2)ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides. Copyright © 2015 Elsevier B.V. All rights reserved.

How do we estimate survival? External validation of a tool for survival estimation in patients with metastatic bone disease-decision analysis and comparison of three international patient populations.

PubMed

Piccioli, Andrea; Spinelli, M Silvia; Forsberg, Jonathan A; Wedin, Rikard; Healey, John H; Ippolito, Vincenzo; Daolio, Primo Andrea; Ruggieri, Pietro; Maccauro, Giulio; Gasbarrini, Alessandro; Biagini, Roberto; Piana, Raimondo; Fazioli, Flavio; Luzzati, Alessandro; Di Martino, Alberto; Nicolosi, Francesco; Camnasio, Francesco; Rosa, Michele Attilio; Campanacci, Domenico Andrea; Denaro, Vincenzo; Capanna, Rodolfo

2015-05-22

We recently developed a clinical decision support tool, capable of estimating the likelihood of survival at 3 and 12 months following surgery for patients with operable skeletal metastases. After making it publicly available on www.PATHFx.org , we attempted to externally validate it using independent, international data. We collected data from patients treated at 13 Italian orthopaedic oncology referral centers between 2010 and 2013, then applied to PATHFx, which generated a probability of survival at three and 12-months for each patient. We assessed accuracy using the area under the receiver-operating characteristic curve (AUC), clinical utility using Decision Curve Analysis (DCA), and compared the Italian patient data to the training set (United States) and first external validation set (Scandinavia). The Italian dataset contained 287 records with at least 12 months follow-up information. The AUCs for the three-month and 12-month estimates was 0.80 and 0.77, respectively. There were missing data, including the surgeon's estimate of survival that was missing in the majority of records. Physiologically, Italian patients were similar to patients in the training and first validation sets. However notable differences were observed in the proportion of those surviving three and 12-months, suggesting differences in referral patterns and perhaps indications for surgery. PATHFx was successfully validated in an Italian dataset containing missing data. This study demonstrates its broad applicability to European patients, even in centers with differing treatment philosophies from those previously studied.

Construct Validity of Fresh Frozen Human Cadaver as a Training Model in Minimal Access Surgery

PubMed Central

Macafee, David; Pranesh, Nagarajan; Horgan, Alan F.

2012-01-01

Background: The construct validity of fresh human cadaver as a training tool has not been established previously. The aims of this study were to investigate the construct validity of fresh frozen human cadaver as a method of training in minimal access surgery and determine if novices can be rapidly trained using this model to a safe level of performance. Methods: Junior surgical trainees, novices (<3 laparoscopic procedure performed) in laparoscopic surgery, performed 10 repetitions of a set of structured laparoscopic tasks on fresh frozen cadavers. Expert laparoscopists (>100 laparoscopic procedures) performed 3 repetitions of identical tasks. Performances were scored using a validated, objective Global Operative Assessment of Laparoscopic Skills scale. Scores for 3 consecutive repetitions were compared between experts and novices to determine construct validity. Furthermore, to determine if the novices reached a safe level, a trimmed mean of the experts score was used to define a benchmark. Mann-Whitney U test was used for construct validity analysis and 1-sample t test to compare performances of the novice group with the benchmark safe score. Results: Ten novices and 2 experts were recruited. Four out of 5 tasks (nondominant to dominant hand transfer; simulated appendicectomy; intracorporeal and extracorporeal knot tying) showed construct validity. Novices’ scores became comparable to benchmark scores between the eighth and tenth repetition. Conclusion: Minimal access surgical training using fresh frozen human cadavers appears to have construct validity. The laparoscopic skills of novices can be accelerated through to a safe level within 8 to 10 repetitions. PMID:23318058

Automated identification of wound information in clinical notes of patients with heart diseases: Developing and validating a natural language processing application.

PubMed

Topaz, Maxim; Lai, Kenneth; Dowding, Dawn; Lei, Victor J; Zisberg, Anna; Bowles, Kathryn H; Zhou, Li

2016-12-01

Electronic health records are being increasingly used by nurses with up to 80% of the health data recorded as free text. However, only a few studies have developed nursing-relevant tools that help busy clinicians to identify information they need at the point of care. This study developed and validated one of the first automated natural language processing applications to extract wound information (wound type, pressure ulcer stage, wound size, anatomic location, and wound treatment) from free text clinical notes. First, two human annotators manually reviewed a purposeful training sample (n=360) and random test sample (n=1100) of clinical notes (including 50% discharge summaries and 50% outpatient notes), identified wound cases, and created a gold standard dataset. We then trained and tested our natural language processing system (known as MTERMS) to process the wound information. Finally, we assessed our automated approach by comparing system-generated findings against the gold standard. We also compared the prevalence of wound cases identified from free-text data with coded diagnoses in the structured data. The testing dataset included 101 notes (9.2%) with wound information. The overall system performance was good (F-measure is a compiled measure of system's accuracy=92.7%), with best results for wound treatment (F-measure=95.7%) and poorest results for wound size (F-measure=81.9%). Only 46.5% of wound notes had a structured code for a wound diagnosis. The natural language processing system achieved good performance on a subset of randomly selected discharge summaries and outpatient notes. In more than half of the wound notes, there were no coded wound diagnoses, which highlight the significance of using natural language processing to enrich clinical decision making. Our future steps will include expansion of the application's information coverage to other relevant wound factors and validation of the model with external data. Copyright © 2016 Elsevier Ltd. All rights reserved.

An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs.

PubMed

Harvey, Naomi D; Craigon, Peter J; Blythe, Simon A; England, Gary C W; Asher, Lucy

2017-01-01

Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5-8, 8-12 and 5-12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting the training outcome of individual working dogs.

Cross-validation of a Shortened Battery for the Assessment of Dysexecutive Disorders in Alzheimer Disease.

PubMed

Godefroy, Olivier; Martinaud, Olivier; Verny, Marc; Mosca, Chrystèle; Lenoir, Hermine; Bretault, Eric; Devendeville, Agnès; Diouf, Momar; Pere, Jean-Jacques; Bakchine, Serge; Delabrousse-Mayoux, Jean-Philippe; Roussel, Martine

2016-01-01

The frequency of executive disorders in mild-to-moderate Alzheimer disease (AD) has been demonstrated by the application of a comprehensive battery. The present study analyzed data from 2 recent multicenter studies based on the same executive battery. The objective was to derive a shortened battery by using the GREFEX population as a training dataset and by cross-validating the results in the REFLEX population. A total of 102 AD patients of the GREFEX study (MMSE=23.2±2.9) and 72 patients of the REFLEX study (MMSE=20.8±3.5) were included. Tests were selected and receiver operating characteristic curves were generated relative to the performance of 780 controls from the GREFEX study. Stepwise logistic regression identified 3 cognitive tests (Six Elements Task, categorical fluency and Trail Making Test B error) and behavioral disorders globally referred as global hypoactivity (P=0.0001, all). This shortened battery was as accurate as the entire GREFEX battery in diagnosing dysexecutive disorders in both training group and the validation group. Bootstrap procedure confirmed the stability of AUC. A shortened battery based on 3 cognitive tests and 3 behavioral domains provides a high diagnosis accuracy of executive disorders in mild-to-moderate AD.

Competency-Based Training and Simulation: Making a "Valid" Argument.

PubMed

Noureldin, Yasser A; Lee, Jason Y; McDougall, Elspeth M; Sweet, Robert M

2018-02-01

The use of simulation as an assessment tool is much more controversial than is its utility as an educational tool. However, without valid simulation-based assessment tools, the ability to objectively assess technical skill competencies in a competency-based medical education framework will remain challenging. The current literature in urologic simulation-based training and assessment uses a definition and framework of validity that is now outdated. This is probably due to the absence of awareness rather than an absence of comprehension. The following review article provides the urologic community an updated taxonomy on validity theory as it relates to simulation-based training and assessments and translates our simulation literature to date into this framework. While the old taxonomy considered validity as distinct subcategories and focused on the simulator itself, the modern taxonomy, for which we translate the literature evidence, considers validity as a unitary construct with a focus on interpretation of simulator data/scores.

Development and validation of a virtual reality simulator: human factors input to interventional radiology training.

PubMed

Johnson, Sheena Joanne; Guediri, Sara M; Kilkenny, Caroline; Clough, Peter J

2011-12-01

This study developed and validated a virtual reality (VR) simulator for use by interventional radiologists. Research in the area of skill acquisition reports practice as essential to become a task expert. Studies on simulation show skills learned in VR can be successfully transferred to a real-world task. Recently, with improvements in technology, VR simulators have been developed to allow complex medical procedures to be practiced without risking the patient. Three studies are reported. In Study I, 35 consultant interventional radiologists took part in a cognitive task analysis to empirically establish the key competencies of the Seldinger procedure. In Study 2, 62 participants performed one simulated procedure, and their performance was compared by expertise. In Study 3, the transferability of simulator training to a real-world procedure was assessed with 14 trainees. Study I produced 23 key competencies that were implemented as performance measures in the simulator. Study 2 showed the simulator had both face and construct validity, although some issues were identified. Study 3 showed the group that had undergone simulator training received significantly higher mean performance ratings on a subsequent patient procedure. The findings of this study support the centrality of validation in the successful design of simulators and show the utility of simulators as a training device. The studies show the key elements of a validation program for a simulator. In addition to task analysis and face and construct validities, the authors highlight the importance of transfer of training in validation studies.

CONSTRUCTION AND VALIDATION OF LOW COST LAPAROSCOPIC SIMULATOR USING ANDROID SMARTPHONE AND POP CAST AND A LAPTOP.

PubMed

Vyas, A; Goel, G

2017-09-01

Minimal invasive surgery training requires a lot of practice and for this purpose innovative tools are needed to develop methods for practice and training skills outside the operating room. Commercially available devices are readily available but cost effectiveness and availability are major limiting factors in resource limited setting. We present an innovative and cost effective laparoscopic simulator which can be easily manufactured and used for practice of laparoscopic surgery. Using a free android application, such as IP webcam we can relay video to laptop without the use of any cables and uniquely we use the flash of a camera as the light source and a selfie stick for movement of the camera. Use of this type of setup can help to reduce cost of simulated learning in low income countries and makes laparoscopic training facilities readily available. Copyright© Authors.

The use of Facebook and WhatsApp application in learning process of physics to train students’ critical thinking skills

NASA Astrophysics Data System (ADS)

Kustijono, R.; Zuhri, F.

2018-01-01

The purpose of this research is to describe the learning process by using Facebook and WhatsApp to train students’ critical thinking skills. The research steps are: 1) analysis; 2) design; 3) development; 4) implementation; 5) evaluation. The research subjects are 40 students of Physics Department of Universitas Negeri Surabaya. This research used descriptive qualitative approach. The study The validation point, practicality, effectiveness, and critical thinking skills of students assessment use Likert scale. Learning process criteria are eligible if ≥ 60% is rated good or excellent. The results are: 1) the use of Facebook and WhatsApp can be implemented in the learning process, and the existing constraints can be overcome; 2) the assessment of students’ critical thinking skills is categorized as good and excellent. These results suggest that learning by using Facebook and WhatsApp can be used to train students’ critical thinking skills.

A New Structure-Activity Relationship (SAR) Model for Predicting Drug-Induced Liver Injury, Based on Statistical and Expert-Based Structural Alerts

PubMed Central

Pizzo, Fabiola; Lombardo, Anna; Manganaro, Alberto; Benfenati, Emilio

2016-01-01

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure-activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80%) and test sets (20%). We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non-hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68%, specificity 89, 33, and 33%, sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform. PMID:27920722

Evaluation of recruitment and selection for specialty training in public health: interim results of a prospective cohort study to measure the predictive validity of the selection process.

PubMed

Pashayan, Nora; Gray, Selena; Duff, Celia; Parkes, Julie; Williams, David; Patterson, Fiona; Koczwara, Anna; Fisher, Grant; Mason, Brendan W

2016-06-01

The recruitment process for public health specialty training includes an assessment centre (AC) with three components, Rust Advanced Numerical Reasoning Appraisal (RANRA), Watson-Glaser Critical Thinking Appraisal (WGCT) and a Situation Judgement Test (SJT), which determines invitation to a selection centre (SC). The scores are combined into a total recruitment (TR) score that determines the offers of appointment. A prospective cohort study using anonymous record linkage to investigate the association between applicant's scores in the recruitment process and registrar's progress through training measured by results of Membership Faculty Public Health (MFPH) examinations and outcomes of the Annual Review of Competence Progression (ARCP). Higher scores in RANRA, WGCT, AC, SC and TR were all significantly associated with higher adjusted odds of passing Part A MFPH exam at the first attempt. Higher scores in AC, SC and TR were significantly associated with passing Part B exam at the first attempt. Higher scores in SJT, AC and SC were significantly associated with satisfactory ARCP outcomes. The current UK national recruitment and selection process for public health specialty training has good predictive validity. The individual components of the process are testing different skills and abilities and together they are providing additive value. © The Author 2015. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Determination of Minimum Training Sample Size for Microarray-Based Cancer Outcome Prediction–An Empirical Assessment

PubMed Central

Cheng, Ningtao; Wu, Leihong; Cheng, Yiyu

2013-01-01

The promise of microarray technology in providing prediction classifiers for cancer outcome estimation has been confirmed by a number of demonstrable successes. However, the reliability of prediction results relies heavily on the accuracy of statistical parameters involved in classifiers. It cannot be reliably estimated with only a small number of training samples. Therefore, it is of vital importance to determine the minimum number of training samples and to ensure the clinical value of microarrays in cancer outcome prediction. We evaluated the impact of training sample size on model performance extensively based on 3 large-scale cancer microarray datasets provided by the second phase of MicroArray Quality Control project (MAQC-II). An SSNR-based (scale of signal-to-noise ratio) protocol was proposed in this study for minimum training sample size determination. External validation results based on another 3 cancer datasets confirmed that the SSNR-based approach could not only determine the minimum number of training samples efficiently, but also provide a valuable strategy for estimating the underlying performance of classifiers in advance. Once translated into clinical routine applications, the SSNR-based protocol would provide great convenience in microarray-based cancer outcome prediction in improving classifier reliability. PMID:23861920

Training community practitioners in a research intervention: practice examples at the intersection of cancer, Western science, and native Hawaiian healing.

PubMed

Ka'opua, Lana Sue I

2003-01-01

This practice paper describes the preintervention training component of a feasibility study exploring the use of ho'oponopono, an indigenous Hawaiian healing practice, for enhancing psychosocial adaptation to breast cancer among Native Hawaiian women. Practitioners' adherence to research protocols and competence in intervention delivery are both regarded as essential to obtaining valid results in tests of intervention feasibility and efficacy; thus, training in this study dually focused on fortification of adherence and enhancing competence among those recruited to deliver the ho'oponopono intervention. A manual-based training, using adult pedagogical strategies infused with Native Hawaiian cultural practices, was delivered to community practitioners. Effects of the training on practitioners' knowledge and skills were evaluated through multiple methods. Knowledge significantly increased between pre- and post-intervention assessment. However, knowledge application for some practitioners was hindered by skill deficits, stylistic differences, and cultural conflict. Ongoing attention to competence and adherence is indicated. In-service training may bolster competence; however, practitioners may have difficulty in adhering to protocols for different reasons, and individualized clinical supervision and cultural consultation may be helpful in some situations.

An Open-Structure Treadmill Gait Trainer: From Research to Application.

PubMed

Li, Jian; Chen, Diansheng; Fan, Yubo

2017-01-01

Lower limb rehabilitation robots are designed to enhance gait function in individuals with motor impairments. Although numerous rehabilitation robots have been developed, only few of these robots have been used in practical health care, particularly in China. The objective of this study is to construct a lower limb rehabilitation robot and bridge the gap between research and application. Open structure to facilitate practical application was created for the whole robot. Three typical movement patterns of a single leg were adopted in designing the exoskeletons, and force models for patient training were established and analyzed under three different conditions, respectively, and then a control system and security strategy were introduced. After establishing the robot, a preliminary experiment on the actual use of a prototype by patients was conducted to validate the functionality of the robot. The experiment showed that different patients and stages displayed different performances, and results on the trend variations across patients and across stages confirmed the validity of the robot and suggested that the design may lead to a system that could be successful in the treatment of patients with walking disorders in China. Furthermore, this study could provide a reference for a similar application design.

Quantitative structural modeling on the wavelength interval (Δλ) in synchronous fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Samari, Fayezeh; Yousefinejad, Saeed

2017-11-01

Emission fluorescence spectroscopy has an extremely restricted scope of application to analyze of complex mixtures since its selectivity is reduced by the extensive spectral overlap. Synchronous fluorescence spectroscopy (SFS) is a technique enables us to analyze complex mixtures with overlapped emission and/or excitation spectra. The difference of excitation and emission wavelength of compounds (interval wavelength or Δλ) is an important characteristic in SFS. Thus a multi-parameter model was constructed to predict Δλ in 63 fluorescent compounds and the regression coefficient in training set, cross validation and test set were 0.88, 0.85 and 0.91 respectively. Furthermore, the applicability and validity of model were evaluated using different statistical methods such as y-scrambling and applicability domain. It was concluded that increasing average valence connectivity, number of Al2-NH functional group and Geary autocorrelation (lag 4) with electronegative weights can lead to increasing Δλ in the fluorescent compounds. The current study obtained an insight into the structural properties of compounds effective on their Δλ as an important parameter in SFS.

Field Demonstration and Validation of TREECS (trademark) and CTS for the Risk Assessment of Contaminants on Department of Defense (DoD) Ranges

DTIC Science & Technology

2017-04-01

unlimited. N/A The objective of this project was to demonstrate and validate the integrated Training Range Environmental Evaluation and Characterization...Defense (DoD) training and testing ranges. Training Range Environmental Evaluation and Characterization System (TREECS™), Environmental Fate Simulator...Defense (DoD) Ranges” ERDC/EL TR-17-5 ii Abstract The Training Range Environmental Evaluation and Characterization Sys- tem (TREECS™) was developed to

Hypnosis, Ericksonian hypnotherapy, and Aikido.

PubMed

Windle, R; Samko, M

1992-04-01

Several key Ericksonian concepts find cross-cultural validation and practical application in the Japanese martial art of Aikido. The Aikido psychophysiological state of centering shares several important attributes with the trance state, particularly in the relational aspects of shared trance. In Aikido methodology for dealing with others, blending is an almost exact parallel to Ericksonian utilization. The Aikido view of resistance offers an increased understanding of strategic/Ericksonian approaches. Therapist training may be enhanced by combining Aikido principles with traditional methods.

Allometric scaling of biceps strength before and after resistance training in men.

PubMed

Zoeller, Robert F; Ryan, Eric D; Gordish-Dressman, Heather; Price, Thomas B; Seip, Richard L; Angelopoulos, Theodore J; Moyna, Niall M; Gordon, Paul M; Thompson, Paul D; Hoffman, Eric P

2007-06-01

The purposes of this study were 1) derive allometric scaling models of isometric biceps muscle strength using pretraining body mass (BM) and muscle cross-sectional area (CSA) as scaling variables in adult males, 2) test model appropriateness using regression diagnostics, and 3) cross-validate the models before and after 12 wk of resistance training. A subset of FAMuSS (Functional SNP Associated with Muscle Size and Strength) study data (N=136) were randomly split into two groups (A and B). Allometric scaling models using pretraining BM and CSA were derived and tested for group A. The scaling exponents determined from these models were then applied to and tested on group B pretraining data. Finally, these scaling exponents were applied to and tested on group A and B posttraining data. BM and CSA models produced scaling exponents of 0.64 and 0.71, respectively. Regression diagnostics determined both models to be appropriate. Cross-validation of the models to group B showed that the BM model, but not the CSA model, was appropriate. Removal of the largest six subjects (CSA>30 cm) from group B resulted in an appropriate fit for the CSA model. Application of the models to group A posttraining data showed that both models were appropriate, but only the body mass model was successful for group B. These data suggest that the application of scaling exponents of 0.64 and 0.71, using BM and CSA, respectively, are appropriate for scaling isometric biceps strength in adult males. However, the scaling exponent using CSA may not be appropriate for individuals with biceps CSA>30 cm. Finally, 12 wk of resistance training does not alter the relationship between BM, CSA, and muscular strength as assessed by allometric scaling.

Validation of a novel duplex ultrasound objective structured assessment of technical skills (DUOSATS) for arterial stenosis detection.

PubMed

Jaffer, U; Singh, P; Pandey, V A; Aslam, M; Standfield, N J

2014-01-01

Duplex ultrasound facilitates bedside diagnosis and hence timely patient care. Its uptake has been hampered by training and accreditation issues. We have developed an assessment tool for Duplex arterial stenosis measurement for both simulator and patient based training. A novel assessment tool: duplex ultrasound assessment of technical skills was developed. A modified duplex ultrasound assessment of technical skills was used for simulator training. Novice, intermediate experience and expert users of duplex ultrasound were invited to participate. Participants viewed an instructional video and were allowed ample time to familiarize with the equipment. Participants' attempts were recorded and independently assessed by four experts using the modified duplex ultrasound assessment of technical skills. 'Global' assessment was also done on a four point Likert scale. Content, construct and concurrent validity as well as reliability were evaluated. Content and construct validity as well as reliability were demonstrated. The simulator had good satisfaction rating from participants: median 4; range 3-5. Receiver operator characteristic analysis has established a cut point of 22/ 34 and 25/ 40 were most appropriate for simulator and patient based assessment respectively. We have validated a novel assessment tool for duplex arterial stenosis detection. Further work is underway to establish transference validity of simulator training to improved skill in scanning patients. We have developed and validated duplex ultrasound assessment of technical skills for simulator training.

Effects of Task Index Variations On Transfer of Training Criteria. Final Report.

ERIC Educational Resources Information Center

Mirabella, Angelo; Wheaton, George R.

The concluding series of a research program designed to validate a battery of task indexes for use in forecasting the effectiveness of training devices is described. Phase I collated 17 task indexes and applied them to sonar training devices, while in Phase II the 17 index battery was validated, using skill acquisition measures as criteria.…

Evaluation of the user experience of "astronaut training device": an immersive, vr-based, motion-training system

NASA Astrophysics Data System (ADS)

Yue, Kang; Wang, Danli; Yang, Xinpan; Hu, Haichen; Liu, Yuqing; Zhu, Xiuqing

2016-10-01

To date, as the different application fields, most VR-based training systems have been different. Therefore, we should take the characteristics of application field into consideration and adopt different evaluation methods when evaluate the user experience of these training systems. In this paper, we propose a method to evaluate the user experience of virtual astronauts training system. Also, we design an experiment based on the proposed method. The proposed method takes learning performance as one of the evaluation dimensions, also combines with other evaluation dimensions such as: presence, immersion, pleasure, satisfaction and fatigue to evaluation user experience of the System. We collect subjective and objective data, the subjective data are mainly from questionnaire designed based on the evaluation dimensions and user interview conducted before and after the experiment. While the objective data are consisted of Electrocardiogram (ECG), reaction time, numbers of reaction error and the video data recorded during the experiment. For the analysis of data, we calculate the integrated score of each evaluation dimension by using factor analysis. In order to improve the credibility of the assessment, we use the ECG signal and reaction test data before and after experiment to validate the changes of fatigue during the experiment, and the typical behavioral features extracted from the experiment video to explain the result of subjective questionnaire. Experimental results show that the System has a better user experience and learning performance, but slight visual fatigue exists after experiment.

Social validation and training of emergency fire safety skills for potential injury prevention and life saving.

PubMed Central

Jones, R T; Kazdin, A E; Haney, J I

1981-01-01

A multifaceted behavioral program designed to teach emergency fire escape procedures to children was evaluated in a multiple-baseline design. Five children were trained to respond correctly to nine home emergency fire situations under simulated conditions. The situations and responses focused upon in training were identified by a social validation procedure involving consultation with several safety agencies, including the direct input of firefighters. Training, carried out in simulated bedrooms at school, resulted in significant improvements in both overt behavior and self-report of fire safety skills. The gains were maintained at a post-check assessment 2 weeks after training had been terminated. The results are discussed in relation both to the importance of social validation of targets and outcomes and the implications for further research in assessing and developing emergency response skills. PMID:7298537

CADASTER QSPR Models for Predictions of Melting and Boiling Points of Perfluorinated Chemicals.

PubMed

Bhhatarai, Barun; Teetz, Wolfram; Liu, Tao; Öberg, Tomas; Jeliazkova, Nina; Kochev, Nikolay; Pukalov, Ognyan; Tetko, Igor V; Kovarich, Simona; Papa, Ester; Gramatica, Paola

2011-03-14

Quantitative structure property relationship (QSPR) studies on per- and polyfluorinated chemicals (PFCs) on melting point (MP) and boiling point (BP) are presented. The training and prediction chemicals used for developing and validating the models were selected from Syracuse PhysProp database and literatures. The available experimental data sets were split in two different ways: a) random selection on response value, and b) structural similarity verified by self-organizing-map (SOM), in order to propose reliable predictive models, developed only on the training sets and externally verified on the prediction sets. Individual linear and non-linear approaches based models developed by different CADASTER partners on 0D-2D Dragon descriptors, E-state descriptors and fragment based descriptors as well as consensus model and their predictions are presented. In addition, the predictive performance of the developed models was verified on a blind external validation set (EV-set) prepared using PERFORCE database on 15 MP and 25 BP data respectively. This database contains only long chain perfluoro-alkylated chemicals, particularly monitored by regulatory agencies like US-EPA and EU-REACH. QSPR models with internal and external validation on two different external prediction/validation sets and study of applicability-domain highlighting the robustness and high accuracy of the models are discussed. Finally, MPs for additional 303 PFCs and BPs for 271 PFCs were predicted for which experimental measurements are unknown. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Measuring competence in endoscopic sinus surgery.

PubMed

Syme-Grant, J; White, P S; McAleer, J P G

2008-02-01

Competence based education is currently being introduced into higher surgical training in the UK. Valid and reliable performance assessment tools are essential to ensure competencies are achieved. No such tools have yet been reported in the UK literature. We sought to develop and pilot test an Endoscopic Sinus Surgery Competence Assessment Tool (ESSCAT). The ESSCAT was designed for in-theatre assessment of higher surgical trainees in the UK. The ESSCAT rating matrix was developed through task analysis of ESS procedures. All otolaryngology consultants and specialist registrars in Scotland were given the opportunity to contribute to its refinement. Two cycles of in-theatre testing were used to ensure utility and gather quantitative data on validity and reliability. Videos of trainees performing surgery were used in establishing inter-rater reliability. National consultation, the consensus derived minimum standard of performance, Cronbach's alpha = 0.89 and demonstration of trainee learning (p = 0.027) during the in vivo application of the ESSCAT suggest a high level of validity. Inter-rater reliability was moderate for competence decisions (Cohen's Kappa = 0.5) and good for total scores (Intra-Class Correlation Co-efficient = 0.63). Intra-rater reliability was good for both competence decisions (Kappa = 0.67) and total scores (Kendall's Tau-b = 0.73). The ESSCAT generates a valid and reliable assessment of trainees' in-theatre performance of endoscopic sinus surgery. In conjunction with ongoing evaluation of the instrument we recommend the use of the ESSCAT in higher specialist training in otolaryngology in the UK.

Validation of Competences and Professionalisation of Teachers and Trainers = Validation des Acquis et Professionnalisation des Enseignants et Formateurs. CEDEFOP Dossier Series.

ERIC Educational Resources Information Center

de Blignieres-Legeraud, Anne; Bjornavold, Jens; Charraud, Anne-Marie; Gerard, Francoise; Diamanti, Stamatina; Freundlinger, Alfred; Bjerknes, Ellen; Covita, Horacio

A workshop aimed to clarify under what conditions the validation of knowledge gained through experience can be considered a professionalizing factor for European Union teachers and trainers by creating a better link between experience and training and between vocational training and qualifications. Seven papers were presented in addition to an…

Air Combat Training: Good Stick Index Validation. Final Report for Period 3 April 1978-1 April 1979.

ERIC Educational Resources Information Center

Moore, Samuel B.; And Others

A study was conducted to investigate and statistically validate a performance measuring system (the Good Stick Index) in the Tactical Air Command Combat Engagement Simulator I (TAC ACES I) Air Combat Maneuvering (ACM) training program. The study utilized a twelve-week sample of eighty-nine student pilots to statistically validate the Good Stick…

The development of a model of psychological first aid for non-mental health trained public health personnel: the Johns Hopkins RAPID-PFA.

PubMed

Everly, George S; Lee McCabe, O; Semon, Natalie L; Thompson, Carol B; Links, Jonathan M

2014-01-01

The Johns Hopkins Center for Public Health Preparedness, which houses the Centers for Disease Control and Prevention-funded Preparedness and Emergency Response Learning Center, has been addressing the challenge of disaster-caused behavioral health surge by conducting training programs in psychological first aid (PFA) for public health professionals. This report describes our approach, named RAPID-PFA, and summarizes training evaluation data to determine if relevant knowledge, skills, and attitudes are imparted to trainees to support effective PFA delivery. In the wake of disasters, there is an increase in psychological distress and dysfunction among survivors and first responders. To meet the challenges posed by this surge, a professional workforce trained in PFA is imperative. More than 1500 participants received a 1-day RAPID-PFA training. Pre-/postassessments were conducted to measure (a) required knowledge to apply PFA; (b) perceived self-efficacy, that is, belief in one's own ability, to apply PFA techniques; and (c) confidence in one's own resilience in a crisis context. Statistical techniques were used to validate the extent to which the survey successfully measured individual PFA constructs, that is, unidimensionality, and to quantify the reliability of the assessment tool. Statistically significant pre-/postimprovements were observed in (a) knowledge items supportive of PFA delivery, (b) perceived self-efficacy to apply PFA interventions, and (c) confidence about being a resilient PFA provider. Cronbach alpha coefficients ranging from 0.87 to 0.90 suggested that the self-reported measures possessed sufficient internal consistency. Findings were consistent with our pilot work, and with our complementary research initiatives validating a variant of RAPID-PFA with faith communities. The RAPID-PFA model promises to be a broadly applicable approach to extending community behavioral health surge capacity. Relevant next steps include evaluating the effectiveness of trained providers in real crisis situations, and determining if PFA training may have potential beyond the disaster context.

A test of the validity of the motivational interviewing treatment integrity code.

PubMed

Forsberg, Lars; Berman, Anne H; Kallmén, Håkan; Hermansson, Ulric; Helgason, Asgeir R

2008-01-01

To evaluate the Swedish version of the Motivational Interviewing Treatment Code (MITI), MITI coding was applied to tape-recorded counseling sessions. Construct validity was assessed using factor analysis on 120 MITI-coded sessions. Discriminant validity was assessed by comparing MITI coding of motivational interviewing (MI) sessions with information- and advice-giving sessions as well as by comparing MI-trained practitioners with untrained practitioners. A principal-axis factoring analysis yielded some evidence for MITI construct validity. MITI differentiated between practitioners with different levels of MI training as well as between MI practitioners and advice-giving counselors, thus supporting discriminant validity. MITI may be used as a training tool together with supervision to confirm and enhance MI practice in clinical settings. MITI can also serve as a tool for evaluating MI integrity in clinical research.

The development, assessment and validation of virtual reality for human anatomy instruction

NASA Technical Reports Server (NTRS)

Marshall, Karen Benn

1996-01-01

This research project seeks to meet the objective of science training by developing, assessing, validating and utilizing VR as a human anatomy training medium. Current anatomy instruction is primarily in the form of lectures and usage of textbooks. In ideal situations, anatomic models, computer-based instruction, and cadaver dissection are utilized to augment traditional methods of instruction. At many institutions, lack of financial resources limits anatomy instruction to textbooks and lectures. However, human anatomy is three-dimensional, unlike the one-dimensional depiction found in textbooks and the two-dimensional depiction found on the computer. Virtual reality allows one to step through the computer screen into a 3-D artificial world. The primary objective of this project is to produce a virtual reality application of the abdominopelvic region of a human cadaver that can be taken back to the classroom. The hypothesis is that an immersive learning environment affords quicker anatomic recognition and orientation and a greater level of retention in human anatomy instruction. The goal is to augment not replace traditional modes of instruction.

An artificial intelligence approach to Bacillus amyloliquefaciens CCMI 1051 cultures: application to the production of anti-fungal compounds.

PubMed

Caldeira, A Teresa; Arteiro, José M; Roseiro, José C; Neves, José; Vicente, H

2011-01-01

The combined effect of incubation time (IT) and aspartic acid concentration (AA) on the predicted biomass concentration (BC), Bacillus sporulation (BS) and anti-fungal activity of compounds (AFA) produced by Bacillus amyloliquefaciens CCMI 1051, was studied using Artificial Neural Networks (ANNs). The values predicted by ANN were in good agreement with experimental results, and were better than those obtained when using Response Surface Methodology. The database used to train and validate ANNs contains experimental data of B. amyloliquefaciens cultures (AFA, BS and BC) with different incubation times (1-9 days) using aspartic acid (3-42 mM) as nitrogen source. After the training and validation stages, the 2-7-6-3 neural network results showed that maximum AFA can be achieved with 19.5 mM AA on day 9; however, maximum AFA can also be obtained with an incubation time as short as 6 days with 36.6 mM AA. Furthermore, the model results showed two distinct behaviors for AFA, depending on IT. Copyright © 2010 Elsevier Ltd. All rights reserved.

Visualization and Phospholipid Identification (VaLID): online integrated search engine capable of identifying and visualizing glycerophospholipids with given mass

PubMed Central

Figeys, Daniel; Fai, Stephen; Bennett, Steffany A. L.

2013-01-01

Motivation: Establishing phospholipid identities in large lipidomic datasets is a labour-intensive process. Where genomics and proteomics capitalize on sequence-based signatures, glycerophospholipids lack easily definable molecular fingerprints. Carbon chain length, degree of unsaturation, linkage, and polar head group identity must be calculated from mass to charge (m/z) ratios under defined mass spectrometry (MS) conditions. Given increasing MS sensitivity, many m/z values are not represented in existing prediction engines. To address this need, Visualization and Phospholipid Identification is a web-based application that returns all theoretically possible phospholipids for any m/z value and MS condition. Visualization algorithms produce multiple chemical structure files for each species. Curated lipids detected by the Canadian Institutes of Health Research Training Program in Neurodegenerative Lipidomics are provided as high-resolution structures. Availability: VaLID is available through the Canadian Institutes of Health Research Training Program in Neurodegenerative Lipidomics resources web site at https://www.med.uottawa.ca/lipidomics/resources.html. Contacts: lipawrd@uottawa.ca Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:23162086

Automatic sleep stage classification using two facial electrodes.

PubMed

Virkkala, Jussi; Velin, Riitta; Himanen, Sari-Leena; Värri, Alpo; Müller, Kiti; Hasan, Joel

2008-01-01

Standard sleep stage classification is based on visual analysis of central EEG, EOG and EMG signals. Automatic analysis with a reduced number of sensors has been studied as an easy alternative to the standard. In this study, a single-channel electro-oculography (EOG) algorithm was developed for separation of wakefulness, SREM, light sleep (S1, S2) and slow wave sleep (S3, S4). The algorithm was developed and tested with 296 subjects. Additional validation was performed on 16 subjects using a low weight single-channel Alive Monitor. In the validation study, subjects attached the disposable EOG electrodes themselves at home. In separating the four stages total agreement (and Cohen's Kappa) in the training data set was 74% (0.59), in the testing data set 73% (0.59) and in the validation data set 74% (0.59). Self-applicable electro-oculography with only two facial electrodes was found to provide reasonable sleep stage information.

Prediction of pelvic organ prolapse using an artificial neural network.

PubMed

Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

2008-08-01

The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

Effectiveness of evidence-based medicine training for undergraduate students at a Chinese Military Medical University: a self-controlled trial

PubMed Central

2014-01-01

Background To evaluate the effect of the integration of evidence-based medicine (EBM) into medical curriculum by measuring undergraduate medical students’ EBM knowledge, attitudes, personal application, and anticipated future use. Methods A self-controlled trial was conducted with 251 undergraduate students at a Chinese Military Medical University, using a validated questionnaire regarding the students’ evidence-based practice (EBP) about knowledge (EBP-K), attitude (EBP-A), personal application (EBP-P), and future anticipated use (EBP-F). The educational intervention was a 20-hour EBM course formally included in the university’s medical curriculum, combining lectures with small group discussion and student-teacher exchange sessions. Data were analyzed using paired t-tests to test the significance of the difference between a before and after comparison. Results The difference between the pre- and post-training scores were statistically significant for EBP-K, EBP-A, EBP-P, and EBP-F. The scores for EBP-P showed the most pronounced percentage change after EBM training (48.97 ± 8.6%), followed by EBP-A (20.83 ± 2.1%), EBP-K (19.21 ± 3.2%), and EBP-F (17.82 ± 5.7%). Stratified analyses by gender, and program subtypes did not result in any significant changes to the results. Conclusions The integration of EBM into the medical curriculum improved undergraduate medical students’ EBM knowledge, attitudes, personal application, and anticipated future use. A well-designed EBM training course and objective outcome measurements are necessary to ensure the optimum learning opportunity for students. PMID:24996537

The Role of Simulation in Microsurgical Training.

PubMed

Evgeniou, Evgenios; Walker, Harriet; Gujral, Sameer

Simulation has been established as an integral part of microsurgical training. The aim of this study was to assess and categorize the various simulation models in relation to the complexity of the microsurgical skill being taught and analyze the assessment methods commonly employed in microsurgical simulation training. Numerous courses have been established using simulation models. These models can be categorized, according to the level of complexity of the skill being taught, into basic, intermediate, and advanced. Microsurgical simulation training should be assessed using validated assessment methods. Assessment methods vary significantly from subjective expert opinions to self-assessment questionnaires and validated global rating scales. The appropriate assessment method should carefully be chosen based on the simulation modality. Simulation models should be validated, and a model with appropriate fidelity should be chosen according to the microsurgical skill being taught. Assessment should move from traditional simple subjective evaluations of trainee performance to validated tools. Future studies should assess the transferability of skills gained during simulation training to the real-life setting. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Content and face validity of a comprehensive robotic skills training program for general surgery, urology, and gynecology.

PubMed

Dulan, Genevieve; Rege, Robert V; Hogg, Deborah C; Gilberg-Fisher, Kristine K; Tesfay, Seifu T; Scott, Daniel J

2012-04-01

The authors previously developed a comprehensive, proficiency-based robotic training curriculum that aimed to address 23 unique skills identified via task deconstruction of robotic operations. The purpose of this study was to determine the content and face validity of this curriculum. Expert robotic surgeons (n = 12) rated each deconstructed skill regarding relevance to robotic operations, were oriented to the curricular components, performed 3 to 5 repetitions on the 9 exercises, and rated each exercise. In terms of content validity, experts rated all 23 deconstructed skills as highly relevant (4.5 on a 5-point scale). Ratings for the 9 inanimate exercises indicated moderate to thorough measurement of designated skills. For face validity, experts indicated that each exercise effectively measured relevant skills (100% agreement) and was highly effective for training and assessment (4.5 on a 5-point scale). These data indicate that the 23 deconstructed skills accurately represent the appropriate content for robotic skills training and strongly support content and face validity for this curriculum. Copyright © 2012. Published by Elsevier Inc.

Validation of a novel virtual reality simulator for robotic surgery.

PubMed

Schreuder, Henk W R; Persson, Jan E U; Wolswijk, Richard G H; Ihse, Ingmar; Schijven, Marlies P; Verheijen, René H M

2014-01-01

With the increase in robotic-assisted laparoscopic surgery there is a concomitant rising demand for training methods. The objective was to establish face and construct validity of a novel virtual reality simulator (dV-Trainer, Mimic Technologies, Seattle, WA) for the use in training of robot-assisted surgery. A comparative cohort study was performed. Participants (n = 42) were divided into three groups according to their robotic experience. To determine construct validity, participants performed three different exercises twice. Performance parameters were measured. To determine face validity, participants filled in a questionnaire after completion of the exercises. Experts outperformed novices in most of the measured parameters. The most discriminative parameters were "time to complete" and "economy of motion" (P < 0.001). The training capacity of the simulator was rated 4.6 ± 0.5 SD on a 5-point Likert scale. The realism of the simulator in general, visual graphics, movements of instruments, interaction with objects, and the depth perception were all rated as being realistic. The simulator is considered to be a very useful training tool for residents and medical specialist starting with robotic surgery. Face and construct validity for the dV-Trainer could be established. The virtual reality simulator is a useful tool for training robotic surgery.

Validation of a Novel Virtual Reality Simulator for Robotic Surgery

PubMed Central

Schreuder, Henk W. R.; Persson, Jan E. U.; Wolswijk, Richard G. H.; Ihse, Ingmar; Schijven, Marlies P.; Verheijen, René H. M.

2014-01-01

Objective. With the increase in robotic-assisted laparoscopic surgery there is a concomitant rising demand for training methods. The objective was to establish face and construct validity of a novel virtual reality simulator (dV-Trainer, Mimic Technologies, Seattle, WA) for the use in training of robot-assisted surgery. Methods. A comparative cohort study was performed. Participants (n = 42) were divided into three groups according to their robotic experience. To determine construct validity, participants performed three different exercises twice. Performance parameters were measured. To determine face validity, participants filled in a questionnaire after completion of the exercises. Results. Experts outperformed novices in most of the measured parameters. The most discriminative parameters were “time to complete” and “economy of motion” (P < 0.001). The training capacity of the simulator was rated 4.6 ± 0.5 SD on a 5-point Likert scale. The realism of the simulator in general, visual graphics, movements of instruments, interaction with objects, and the depth perception were all rated as being realistic. The simulator is considered to be a very useful training tool for residents and medical specialist starting with robotic surgery. Conclusions. Face and construct validity for the dV-Trainer could be established. The virtual reality simulator is a useful tool for training robotic surgery. PMID:24600328

A Novel Multiple Choice Question Generation Strategy: Alternative Uses for Controlled Vocabulary Thesauri in Biomedical-Sciences Education.

PubMed

Lopetegui, Marcelo A; Lara, Barbara A; Yen, Po-Yin; Çatalyürek, Ümit V; Payne, Philip R O

2015-01-01

Multiple choice questions play an important role in training and evaluating biomedical science students. However, the resource intensive nature of question generation limits their open availability, reducing their contribution to evaluation purposes mainly. Although applied-knowledge questions require a complex formulation process, the creation of concrete-knowledge questions (i.e., definitions, associations) could be assisted by the use of informatics methods. We envisioned a novel and simple algorithm that exploits validated knowledge repositories and generates concrete-knowledge questions by leveraging concepts' relationships. In this manuscript we present the development and validation of a prototype which successfully produced meaningful concrete-knowledge questions, opening new applications for existing knowledge repositories, potentially benefiting students of all biomedical sciences disciplines.

On the validity and generality of transfer effects in cognitive training research.

PubMed

Noack, Hannes; Lövdén, Martin; Schmiedek, Florian

2014-11-01

Evaluation of training effectiveness is a long-standing problem of cognitive intervention research. The interpretation of transfer effects needs to meet two criteria, generality and specificity. We introduce each of the two, and suggest ways of implementing them. First, the scope of the construct of interest (e.g., working memory) defines the expected generality of transfer effects. Given that the constructs of interest are typically defined at the latent level, data analysis should also be conducted at the latent level. Second, transfer should be restricted to measures that are theoretically related to the trained construct. Hence, the construct of interest also determines the specificity of expected training effects; to test for specificity, study designs should aim at convergent and discriminant validity. We evaluate the recent cognitive training literature in relation to both criteria. We conclude that most studies do not use latent factors for transfer assessment, and do not test for convergent and discriminant validity.

Initial Feasibility and Validity of a Prospective Memory Training Program in a Substance Use Treatment Population

PubMed Central

Sweeney, Mary M.; Rass, Olga; Johnson, Patrick S.; Strain, Eric C.; Berry, Meredith S.; Vo, Hoa T.; Fishman, Marc J.; Munro, Cynthia A.; Rebok, George W.; Mintzer, Miriam Z.; Johnson, Matthew W.

2016-01-01

Individuals with substance use disorders have shown deficits in the ability to implement future intentions, called prospective memory. Deficits in prospective memory and working memory, a critical underlying component of prospective memory, likely contribute to substance use treatment failures. Thus, improvement of prospective memory and working memory in substance use patients is an innovative target for intervention. We sought to develop a feasible and valid prospective memory training program that incorporates working memory training and may serve as a useful adjunct to substance use disorder treatment. We administered a single session of the novel prospective memory and working memory training program to participants (n = 22; 13 male; 9 female) enrolled in outpatient substance use disorder treatment and correlated performance to existing measures of prospective memory and working memory. Generally accurate prospective memory performance in a single session suggests feasibility in a substance use treatment population. However, training difficulty should be increased to avoid ceiling effects across repeated sessions. Consistent with existing literature, we observed superior performance on event-based relative to time-based prospective memory tasks. Performance on the prospective memory and working memory training components correlated with validated assessments of prospective memory and working memory, respectively. Correlations between novel memory training program performance and established measures suggest that our training engages appropriate cognitive processes. Further, differential event- and time-based prospective memory task performance suggests internal validity of our training. These data support development of this intervention as an adjunctive therapy for substance use disorders. PMID:27690506

Training Tools for Nontechnical Skills for Surgeons-A Systematic Review.

PubMed

Wood, Thomas Charles; Raison, Nicholas; Haldar, Shreya; Brunckhorst, Oliver; McIlhenny, Craig; Dasgupta, Prokar; Ahmed, Kamran

Development of nontechnical skills for surgeons has been recognized as an important factor in surgical care. Training tools for this specific domain are being created and validated to maximize the surgeon's nontechnical ability. This systematic review aims to outline, address, and recommend these training tools. A full and comprehensive literature search, using a systematic format, was performed on ScienceDirect and PubMed, with data extraction occurring in line with specified inclusion criteria. Systematic review was performed fully at King's College London. A total of 84 heterogeneous articles were used in this review. Further, 23 training tools including scoring systems, training programs, and mixtures of the two for a range of specialities were identified in the literature. Most can be applied to surgery overall, although some tools target specific specialities (such as neurosurgery). Interrater reliability, construct, content, and face validation statuses were variable according to the specific tool in question. Study results pertaining to nontechnical skill training tools have thus far been universally positive, but further studies are required for those more recently developed and less extensively used tools. Recommendations can be made for individual training tools based on their level of validation and for their target audience. Based on the number of studies performed and their status of validity, NOTSS and Oxford NOTECHS II can be considered the gold standard for individual- and team-based nontechnical skills training, respectively, especially when used in conjunction with a training program. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Initial feasibility and validity of a prospective memory training program in a substance use treatment population.

PubMed

Sweeney, Mary M; Rass, Olga; Johnson, Patrick S; Strain, Eric C; Berry, Meredith S; Vo, Hoa T; Fishman, Marc J; Munro, Cynthia A; Rebok, George W; Mintzer, Miriam Z; Johnson, Matthew W

2016-10-01

Individuals with substance use disorders have shown deficits in the ability to implement future intentions, called prospective memory. Deficits in prospective memory and working memory, a critical underlying component of prospective memory, likely contribute to substance use treatment failures. Thus, improvement of prospective memory and working memory in substance use patients is an innovative target for intervention. We sought to develop a feasible and valid prospective memory training program that incorporates working memory training and may serve as a useful adjunct to substance use disorder treatment. We administered a single session of the novel prospective memory and working memory training program to participants (n = 22; 13 men, 9 women) enrolled in outpatient substance use disorder treatment and correlated performance to existing measures of prospective memory and working memory. Generally accurate prospective memory performance in a single session suggests feasibility in a substance use treatment population. However, training difficulty should be increased to avoid ceiling effects across repeated sessions. Consistent with existing literature, we observed superior performance on event-based relative to time-based prospective memory tasks. Performance on the prospective memory and working memory training components correlated with validated assessments of prospective memory and working memory, respectively. Correlations between novel memory training program performance and established measures suggest that our training engages appropriate cognitive processes. Further, differential event- and time-based prospective memory task performance suggests internal validity of our training. These data support the development of this intervention as an adjunctive therapy for substance use disorders. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Educating psychotherapy supervisors.

PubMed

Watkins, C Edward

2012-01-01

What do we know clinically and empirically about the education of psychotherapy supervisors? In this paper, I attempt to address that question by: (1) reviewing briefly current thinking about psychotherapy supervisor training; and (2) examining the available research where supervisor training and supervision have been studied. The importance of such matters as training format and methods, supervision topics for study, supervisor development, and supervisor competencies are considered, and some prototypical, competency-based supervisor training programs that hold educational promise are identified and described. Twenty supervisor training studies are critiqued, and their implications for practice and research are examined. Based on this review of training programs and research, the following conclusions are drawn: (1) the clinical validity of supervisor education appears to be strong, solid, and sound, (2) although research suggests that supervisor training can have value in stimulating the development of supervisor trainees and better preparing them for the supervisory role, any such base of empirical support or validity should be regarded as tentative at best; and (3) the most formidable challenge for psychotherapy supervisor education may well be correcting the imbalance that currently exists between clinical and empirical validity and "raising the bar" on the rigor, relevance, and replicability of future supervisor training research.

Performance-based comparison of neonatal intubation training outcomes: simulator and live animal.

PubMed

Andreatta, Pamela B; Klotz, Jessica J; Dooley-Hash, Suzanne L; Hauptman, Joe G; Biddinger, Bea; House, Joseph B

2015-02-01

The purpose of this article was to establish psychometric validity evidence for competency assessment instruments and to evaluate the impact of 2 forms of training on the abilities of clinicians to perform neonatal intubation. To inform the development of assessment instruments, we conducted comprehensive task analyses including each performance domain associated with neonatal intubation. Expert review confirmed content validity. Construct validity was established using the instruments to differentiate between the intubation performance abilities of practitioners (N = 294) with variable experience (novice through expert). Training outcomes were evaluated using a quasi-experimental design to evaluate performance differences between 294 subjects randomly assigned to 1 of 2 training groups. The training intervention followed American Heart Association Pediatric Advanced Life Support and Neonatal Resuscitation Program protocols with hands-on practice using either (1) live feline or (2) simulated feline models. Performance assessment data were captured before and directly following the training. All data were analyzed using analysis of variance with repeated measures and statistical significance set at P < .05. Content validity, reliability, and consistency evidence were established for each assessment instrument. Construct validity for each assessment instrument was supported by significantly higher scores for subjects with greater levels of experience, as compared with those with less experience (P = .000). Overall, subjects performed significantly better in each assessment domain, following the training intervention (P = .000). After controlling for experience level, there were no significant differences among the cognitive, performance, and self-efficacy outcomes between clinicians trained with live animal model or simulator model. Analysis of retention scores showed that simulator trained subjects had significantly higher performance scores after 18 weeks (P = .01) and 52 weeks (P = .001) and cognitive scores after 52 weeks (P = .001). The results of this study demonstrate the feasibility of using valid, reliable assessment instruments to assess clinician competency and self-efficacy in the performance of neonatal intubation. We demonstrated the relative equivalency of live animal and simulation-based models as tools to support acquisition of neonatal intubation skills. Retention of performance abilities was greater for subjects trained using the simulator, likely because it afforded greater opportunity for repeated practice. Outcomes in each assessment area were influenced by the previous intubation experience of participants. This suggests that neonatal intubation training programs could be tailored to the level of provider experience to make efficient use of time and educational resources. Future research focusing on the uses of assessment in the applied clinical environment, as well as identification of optimal training cycles for performance retention, is merited.

Failure of a systemic lupus erythematosus response index developed from clinical trial data: lessons examined and learned.

PubMed

Forbess, L J; Bresee, C; Wallace, D J; Weisman, M H

2017-08-01

Background Our primary goal was to create an outcome change score index similar to a standard rheumatoid arthritis (RA) model utilizing real-world data in systemic lupus erythematosus (SLE) patients that occurred during their phase 3 trials with a Food and Drug Administration-approved drug. Methods We utilized raw data from trials of belimumab for the treatment of SLE. Data were split 80/20 into training/validation sets. Index variables present in a majority of patients and with face validity were selected. Variables were scored for each patient as percentage improvement from baseline after one year. The percentage of placebo- and drug-treated patients considered improved after the application of various criteria was ascertained. Logistic regression was employed to determine the ability of the new index to predict treatment assignment. Results A total of 1693 subjects had data for analyses. Eight variables were chosen: arthritis, rash, physician global assessment, fatigue, anti-double stranded DNA antibodies, C3, C4 and C-reactive protein. In the training dataset, ≥20% improvement in ≥4 of eight variables produced the largest difference between placebo- and drug-treated patients (22.1%) with an acceptable rate of improved placebo-treated patients (25%). This resulted in an odds ratio for belimumab (10 mg/kg) vs placebo of 2.7 (95% CI: 2.0-3.6; p < 0.001). However, in the validate dataset the odds ratio was not significant at 1.3 (95% CI: 0.8-2.2; p = 0.863). Conclusions The index created from training data did not achieve statistical significance when tested in the validation set. We have speculated why this happened. Is the lack of success of therapeutics for SLE caused by ineffective medications, study design and outcome instruments that fail to inform us, or is the heterogeneity of the disease too daunting? The lessons learned here can help direct future endeavors intended to improve SLE outcome instruments.

Validation of the Federal Aviation Administration Air Traffic Control Specialist Pre-Training Screen.

DOT National Transportation Integrated Search

1994-02-01

Two formal validation studies of the Air Traffic Control Specialist Pre Training Screen (ATCS/PTS), a 5 day computer administered test battery, are described. The ATCS/PTS was designed to replace the 9 week US Federal Aviation Administration (FAA) Ac...

Prospective validation of pathologic complete response models in rectal cancer: Transferability and reproducibility.

PubMed

van Soest, Johan; Meldolesi, Elisa; van Stiphout, Ruud; Gatta, Roberto; Damiani, Andrea; Valentini, Vincenzo; Lambin, Philippe; Dekker, Andre

2017-09-01

Multiple models have been developed to predict pathologic complete response (pCR) in locally advanced rectal cancer patients. Unfortunately, validation of these models normally omit the implications of cohort differences on prediction model performance. In this work, we will perform a prospective validation of three pCR models, including information whether this validation will target transferability or reproducibility (cohort differences) of the given models. We applied a novel methodology, the cohort differences model, to predict whether a patient belongs to the training or to the validation cohort. If the cohort differences model performs well, it would suggest a large difference in cohort characteristics meaning we would validate the transferability of the model rather than reproducibility. We tested our method in a prospective validation of three existing models for pCR prediction in 154 patients. Our results showed a large difference between training and validation cohort for one of the three tested models [Area under the Receiver Operating Curve (AUC) cohort differences model: 0.85], signaling the validation leans towards transferability. Two out of three models had a lower AUC for validation (0.66 and 0.58), one model showed a higher AUC in the validation cohort (0.70). We have successfully applied a new methodology in the validation of three prediction models, which allows us to indicate if a validation targeted transferability (large differences between training/validation cohort) or reproducibility (small cohort differences). © 2017 American Association of Physicists in Medicine.

Prediction of plant lncRNA by ensemble machine learning classifiers.

PubMed

Simopoulos, Caitlin M A; Weretilnyk, Elizabeth A; Golding, G Brian

2018-05-02

In plants, long non-protein coding RNAs are believed to have essential roles in development and stress responses. However, relative to advances on discerning biological roles for long non-protein coding RNAs in animal systems, this RNA class in plants is largely understudied. With comparatively few validated plant long non-coding RNAs, research on this potentially critical class of RNA is hindered by a lack of appropriate prediction tools and databases. Supervised learning models trained on data sets of mostly non-validated, non-coding transcripts have been previously used to identify this enigmatic RNA class with applications largely focused on animal systems. Our approach uses a training set comprised only of empirically validated long non-protein coding RNAs from plant, animal, and viral sources to predict and rank candidate long non-protein coding gene products for future functional validation. Individual stochastic gradient boosting and random forest classifiers trained on only empirically validated long non-protein coding RNAs were constructed. In order to use the strengths of multiple classifiers, we combined multiple models into a single stacking meta-learner. This ensemble approach benefits from the diversity of several learners to effectively identify putative plant long non-coding RNAs from transcript sequence features. When the predicted genes identified by the ensemble classifier were compared to those listed in GreeNC, an established plant long non-coding RNA database, overlap for predicted genes from Arabidopsis thaliana, Oryza sativa and Eutrema salsugineum ranged from 51 to 83% with the highest agreement in Eutrema salsugineum. Most of the highest ranking predictions from Arabidopsis thaliana were annotated as potential natural antisense genes, pseudogenes, transposable elements, or simply computationally predicted hypothetical protein. Due to the nature of this tool, the model can be updated as new long non-protein coding transcripts are identified and functionally verified. This ensemble classifier is an accurate tool that can be used to rank long non-protein coding RNA predictions for use in conjunction with gene expression studies. Selection of plant transcripts with a high potential for regulatory roles as long non-protein coding RNAs will advance research in the elucidation of long non-protein coding RNA function.

Development of a Child Abuse Checklist to Evaluate Prehospital Provider Performance.

PubMed

Alphonso, Aimee; Auerbach, Marc; Bechtel, Kirsten; Bilodeau, Kyle; Gawel, Marcie; Koziel, Jeannette; Whitfill, Travis; Tiyyagura, Gunjan Kamdar

2017-01-01

To develop and provide validity evidence for a performance checklist to evaluate the child abuse screening behaviors of prehospital providers. Checklist Development: We developed the first iteration of the checklist after review of the relevant literature and on the basis of the authors' clinical experience. Next, a panel of six content experts participated in three rounds of Delphi review to reach consensus on the final checklist items. Checklist Validation: Twenty-eight emergency medical services (EMS) providers (16 EMT-Basics, 12 EMT-Paramedics) participated in a standardized simulated case of physical child abuse to an infant followed by one-on-one semi-structured qualitative interviews. Three reviewers scored the videotaped performance using the final checklist. Light's kappa and Cronbach's alpha were calculated to assess inter-rater reliability (IRR) and internal consistency, respectively. The correlation of successful child abuse screening with checklist task completion and with participant characteristics were compared using Pearson's chi squared test to gather evidence for construct validity. The Delphi review process resulted in a final checklist that included 24 items classified with trichotomous scoring (done, not done, or not applicable). The overall IRR of the three raters was 0.70 using Light's kappa, indicating substantial agreement. Internal consistency of the checklist was low, with an overall Cronbach's alpha of 0.61. Of 28 participants, only 14 (50%) successfully screened for child abuse in simulation. Participants who successfully screened for child abuse did not differ significantly from those who failed to screen in terms of training level, past experience with child abuse reporting, or self-reported confidence in detecting child abuse (all p > 0.30). Of all 24 tasks, only the task of exposing the infant significantly correlated with successful detection of child abuse (p < 0.05). We developed a child abuse checklist that demonstrated strong content validity and substantial inter-rater reliability, but successful item completion did not correlate with other markers of provider experience. The validated instrument has important potential for training, continuing education, and research for prehospital providers at all levels of training.

An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs

PubMed Central

Craigon, Peter J.; Blythe, Simon A.; England, Gary C. W.; Asher, Lucy

2017-01-01

Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5–8, 8–12 and 5–12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting the training outcome of individual working dogs. PMID:28614347

The Imperial Paediatric Emergency Training Toolkit (IPETT) for use in paediatric emergency training: development and evaluation of feasibility and validity.

PubMed

Lambden, Simon; DeMunter, Claudine; Dowson, Anne; Cooper, Mehrengise; Gautama, Sanjay; Sevdalis, Nick

2013-06-01

To develop and test the feasibility, reliability, and validity of a practical toolkit for the assessment and feedback of skills required to manage paediatric emergencies in critical care settings. The Imperial Paediatric Emergency Training Toolkit (IPETT) was developed based on current evidence-base and expert input. IPETT assesses both technical and non-technical skills. The technical component covers skills in the areas of clinical assessment, airway and breathing, cardiovascular, and drugs. The non-technical component is based on the validated NOTECHS tool and covers communication and interaction, cooperation and team skills, leadership and managerial skills, and decision-making. The reliability (internal consistency), content validity (inter-correlations between different skills) and concurrent validity (correlations between global technical and non-technical scores) of IPETT were prospectively evaluated in 45 simulated paediatric crises carried out in a PICU with anaesthetic and paediatric trainees (N=52). Non-parametric analyses were carried out. Significance was set at P<0.05. Cronbach alpha reliability coefficients were overall acceptable for the technical (alpha range=0.638-0.810) and good for the non-technical (alpha range=0.701-0.899) component of IPETT. The median inter-skill correlation was rho=0.564 and rho=0.549 for the technical and non-technical components, respectively. These indicate good content validity, as the skills were inter-related but not redundant. We also demonstrate a correlation between the global technical and non-technical scores (rho=0.471) - all Ps<0.05 during the assessments. IPETT offers a psychometrically viable and feasible to use tool in the context of paediatric emergencies training. This study shows that assessment of technical and non-technical skills in combination may offer a more clinically relevant model for training in paediatric emergencies. Further validation should aim to demonstrate skill retention over time and skill transfer from simulation-based training to real emergencies. Copyright © 2013. Published by Elsevier Ireland Ltd.

Constructing Agent Model for Virtual Training Systems

NASA Astrophysics Data System (ADS)

Murakami, Yohei; Sugimoto, Yuki; Ishida, Toru

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.

Decoding the attended speech stream with multi-channel EEG: implications for online, daily-life applications

NASA Astrophysics Data System (ADS)

Mirkovic, Bojana; Debener, Stefan; Jaeger, Manuela; De Vos, Maarten

2015-08-01

Objective. Recent studies have provided evidence that temporal envelope driven speech decoding from high-density electroencephalography (EEG) and magnetoencephalography recordings can identify the attended speech stream in a multi-speaker scenario. The present work replicated the previous high density EEG study and investigated the necessary technical requirements for practical attended speech decoding with EEG. Approach. Twelve normal hearing participants attended to one out of two simultaneously presented audiobook stories, while high density EEG was recorded. An offline iterative procedure eliminating those channels contributing the least to decoding provided insight into the necessary channel number and optimal cross-subject channel configuration. Aiming towards the future goal of near real-time classification with an individually trained decoder, the minimum duration of training data necessary for successful classification was determined by using a chronological cross-validation approach. Main results. Close replication of the previously reported results confirmed the method robustness. Decoder performance remained stable from 96 channels down to 25. Furthermore, for less than 15 min of training data, the subject-independent (pre-trained) decoder performed better than an individually trained decoder did. Significance. Our study complements previous research and provides information suggesting that efficient low-density EEG online decoding is within reach.

Transfer Learning for Class Imbalance Problems with Inadequate Data.

PubMed

Al-Stouhi, Samir; Reddy, Chandan K

2016-07-01

A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

Adoption and correlates of Postgraduate Hospital Educational Environment Measure (PHEEM) in the evaluation of learning environments - A systematic review.

PubMed

Chan, Christopher Yi Wen; Sum, Min Yi; Lim, Wee Shiong; Chew, Nicholas Wuen Ming; Samarasekera, Dujeepa D; Sim, Kang

2016-12-01

The Postgraduate Hospital Educational Environment Measure (PHEEM) is a highly reliable and valid instrument to measure the educational environment during post graduate medical training. This review extends earlier reports by evaluating the extant adoption of PHEEM in various international clinical training sites, and its significant correlations in order to expand our understanding on the use of PHEEM and facilitate future applications and research. A systematic literature review was conducted on all articles between 2005 and October 2015 that adopted and reported data using the PHEEM. Overall 30 studies were included, encompassing data from 14 countries internationally. Notable differences in the PHEEM scores were found between different levels of training, disciplines, and clinical training sites. Common strengths and weaknesses in learning environments were observed and there were significant correlations between PHEEM scores and In-Training Exam (ITE) performance (positive correlation) and level of burnout (negative correlation), respectively. PHEEM is widely adopted in different learning settings, and is a useful tool to identify the strengths and weaknesses of an educational environment. Future research can examine other correlates of PHEEM and longitudinal changes in interventional studies.

Could situational judgement tests be used for selection into dental foundation training?

PubMed

Patterson, F; Ashworth, V; Mehra, S; Falcon, H

2012-07-13

To pilot and evaluate a machine-markable situational judgement test (SJT) designed to select candidates into UK dental foundation training. Single centre pilot study. UK postgraduate deanery in 2010. Seventy-four candidates attending interview for dental foundation training in Oxford and Wessex Deaneries volunteered to complete the situational judgement test. The situational judgement test was developed to assess relevant professional attributes for dentistry (for example, empathy and integrity) in a machine-markable format. Test content was developed by subject matter experts working with experienced psychometricians. Evaluation of psychometric properties of the pilot situational judgement test (for example, reliability, validity and fairness). Scores in the dental foundation training selection process (short-listing and interviews) were used to examine criterion-related validity. Candidates completed an evaluation questionnaire to examine candidate reactions and face validity of the new test. Forty-six candidates were female and 28 male; mean age was 23.5-years-old (range 22-32). Situational judgement test scores were normally distributed and the test showed good internal reliability when corrected for test length (α = 0.74). Situational judgement test scores positively correlated with the management, leadership and professionalism interview (N = 50; r = 0.43, p <0.01) but not with the clinical skills interview, providing initial evidence of criterion-related validity as the situational judgement test is designed to test non-cognitive professional attributes beyond clinical knowledge. Most candidates perceived the situational judgement test as relevant to dentistry, appropriate for their training level, and fair. This initial pilot study suggests that a situational judgement test is an appropriate and innovative method to measure professional attributes (eg empathy and integrity) for selection into foundation training. Further research will explore the long-term predictive validity of the situational judgement test once candidates have entered training.

Validation of virtual reality as a tool to understand and prevent child pedestrian injury.

PubMed

Schwebel, David C; Gaines, Joanna; Severson, Joan

2008-07-01

In recent years, virtual reality has emerged as an innovative tool for health-related education and training. Among the many benefits of virtual reality is the opportunity for novice users to engage unsupervised in a safe environment when the real environment might be dangerous. Virtual environments are only useful for health-related research, however, if behavior in the virtual world validly matches behavior in the real world. This study was designed to test the validity of an immersive, interactive virtual pedestrian environment. A sample of 102 children and 74 adults was recruited to complete simulated road-crossings in both the virtual environment and the identical real environment. In both the child and adult samples, construct validity was demonstrated via significant correlations between behavior in the virtual and real worlds. Results also indicate construct validity through developmental differences in behavior; convergent validity by showing correlations between parent-reported child temperament and behavior in the virtual world; internal reliability of various measures of pedestrian safety in the virtual world; and face validity, as measured by users' self-reported perception of realism in the virtual world. We discuss issues of generalizability to other virtual environments, and the implications for application of virtual reality to understanding and preventing pediatric pedestrian injuries.

Convergent validity evidence for the Pain and Discomfort Scale (PADS) for pain assessment among adults with intellectual disability

PubMed Central

Shinde, Satomi K.; Danov, Stacy; Chen, Chin-Chih; Clary, Jamie; Harper, Vicki; Bodfish, James W.; Symons, Frank J.

2014-01-01

Objectives The main aim of the study was to generate initial convergent validity evidence for the Pain and Discomfort Scale (PADS) for use with non-verbal adults with intellectual disabilities (ID). Methods Forty-four adults with intellectual disability (mean age = 46, 52 % male) were evaluated using a standardized sham-controlled and blinded sensory testing protocol, from which FACS and PADS scores were tested for (1) sensitivity to an array of calibrated sensory stimuli, (2) specificity (active vs. sham trials), and (3) concordance. Results The primary findings were that participants were reliably coded using both FACS and PADS approaches as being reactive to the sensory stimuli (FACS: F[2, 86] = 4.71, P < .05, PADS: F[2, 86] = 21.49, P < .05) (sensitivity evidence), not reactive during the sham stimulus trials (FACS: F[1, 43]= 3.77, p = .06, PADS: F[1, 43] = 5.87, p = .02) (specificity evidence), and there were significant (r = .41 – .51, p < .01) correlations between PADS and FACS (convergent validity evidence). Discussion FACS is an objective coding platform for facial expression. It requires intensive training and resources for scoring. As such it may be limited for clinical application. PADS was designed for clinical application. PADS scores were comparable to FACS scores under controlled evaluation conditions providing partial convergent validity evidence for its use. PMID:24135902

Evaluation of the educational impact of the WHO Essential Newborn Care course in Zambia.

PubMed

McClure, E M; Carlo, W A; Wright, L L; Chomba, E; Uxa, F; Lincetto, O; Bann, C

2007-08-01

To evaluate the effectiveness of the World Health Organization (WHO) Essential Newborn Care (ENC) course in improving knowledge and skills of nurse midwives in low-risk delivery clinics in a developing country. The investigators identified the content specifications of the training material, developed both written and performance evaluations and administered the evaluations both before and after training clinical nurse midwives in Zambia. Based on these evaluations, both the knowledge and skills of the nurse midwives improved significantly following the course (from a mean of 65% correct pretraining to 84% correct post-training and from 65% to 77% correct on the performance and written evaluations, respectively). The ENC course written evaluation was validated and both tools allowed evaluation of the ENC course training. We found significant improvements in trainees' knowledge and skills in essential newborn care following the WHO ENC course; however, lack of basic resources may have limited the application of the ENC guidelines. Implementation of the ENC course should be undertaken in consideration with the local conditions available for newborn care.

Validation and Use of a Predictive Modeling Tool: Employing Scientific Findings to Improve Responsible Conduct of Research Education.

PubMed

Mulhearn, Tyler J; Watts, Logan L; Todd, E Michelle; Medeiros, Kelsey E; Connelly, Shane; Mumford, Michael D

2017-01-01

Although recent evidence suggests ethics education can be effective, the nature of specific training programs, and their effectiveness, varies considerably. Building on a recent path modeling effort, the present study developed and validated a predictive modeling tool for responsible conduct of research education. The predictive modeling tool allows users to enter ratings in relation to a given ethics training program and receive instantaneous evaluative information for course refinement. Validation work suggests the tool's predicted outcomes correlate strongly (r = 0.46) with objective course outcomes. Implications for training program development and refinement are discussed.

Comparison of the applicability domain of a quantitative structure-activity relationship for estrogenicity with a large chemical inventory.

PubMed

Netzeva, Tatiana I; Gallegos Saliner, Ana; Worth, Andrew P

2006-05-01

The aim of the present study was to illustrate that it is possible and relatively straightforward to compare the domain of applicability of a quantitative structure-activity relationship (QSAR) model in terms of its physicochemical descriptors with a large inventory of chemicals. A training set of 105 chemicals with data for relative estrogenic gene activation, obtained in a recombinant yeast assay, was used to develop the QSAR. A binary classification model for predicting active versus inactive chemicals was developed using classification tree analysis and two descriptors with a clear physicochemical meaning (octanol-water partition coefficient, or log Kow, and the number of hydrogen bond donors, or n(Hdon)). The model demonstrated a high overall accuracy (90.5%), with a sensitivity of 95.9% and a specificity of 78.1%. The robustness of the model was evaluated using the leave-many-out cross-validation technique, whereas the predictivity was assessed using an artificial external test set composed of 12 compounds. The domain of the QSAR training set was compared with the chemical space covered by the European Inventory of Existing Commercial Chemical Substances (EINECS), as incorporated in the CDB-EC software, in the log Kow / n(Hdon) plane. The results showed that the training set and, therefore, the applicability domain of the QSAR model covers a small part of the physicochemical domain of the inventory, even though a simple method for defining the applicability domain (ranges in the descriptor space) was used. However, a large number of compounds are located within the narrow descriptor window.

Recent advancements in medical simulation: patient-specific virtual reality simulation.

PubMed

Willaert, Willem I M; Aggarwal, Rajesh; Van Herzeele, Isabelle; Cheshire, Nicholas J; Vermassen, Frank E

2012-07-01

Patient-specific virtual reality simulation (PSVR) is a new technological advancement that allows practice of upcoming real operations and complements the established role of VR simulation as a generic training tool. This review describes current developments in PSVR and draws parallels with other high-stake industries, such as aviation, military, and sports. A review of the literature was performed using PubMed and Internet search engines to retrieve data relevant to PSVR in medicine. All reports pertaining to PSVR were included. Reports on simulators that did not incorporate a haptic interface device were excluded from the review. Fifteen reports described 12 simulators that enabled PSVR. Medical procedures in the field of laparoscopy, vascular surgery, orthopedics, neurosurgery, and plastic surgery were included. In all cases, source data was two-dimensional CT or MRI data. Face validity was most commonly reported. Only one (vascular) simulator had undergone face, content, and construct validity. Of the 12 simulators, 1 is commercialized and 11 are prototypes. Five simulators have been used in conjunction with real patient procedures. PSVR is a promising technological advance within medicine. The majority of simulators are still in the prototype phase. As further developments unfold, the validity of PSVR will have to be examined much like generic VR simulation for training purposes. Nonetheless, similar to the aviation, military, and sport industries, operative performance and patient safety may be enhanced by the application of this novel technology.

EEG-neurofeedback for optimising performance. II: creativity, the performing arts and ecological validity.

PubMed

Gruzelier, John H

2014-07-01

As a continuation of a review of evidence of the validity of cognitive/affective gains following neurofeedback in healthy participants, including correlations in support of the gains being mediated by feedback learning (Gruzelier, 2014a), the focus here is on the impact on creativity, especially in the performing arts including music, dance and acting. The majority of research involves alpha/theta (A/T), sensory-motor rhythm (SMR) and heart rate variability (HRV) protocols. There is evidence of reliable benefits from A/T training with advanced musicians especially for creative performance, and reliable benefits from both A/T and SMR training for novice music performance in adults and in a school study with children with impact on creativity, communication/presentation and technique. Making the SMR ratio training context ecologically relevant for actors enhanced creativity in stage performance, with added benefits from the more immersive training context. A/T and HRV training have benefitted dancers. The neurofeedback evidence adds to the rapidly accumulating validation of neurofeedback, while performing arts studies offer an opportunity for ecological validity in creativity research for both creative process and product. Copyright © 2013 Elsevier Ltd. All rights reserved.

Training Guide for Observation and Interviewing in Marine Corps Task Analysis. Training Manual 3

DTIC Science & Technology

1975-08-01

McGraw- Hill Book Co., 1954. This is a comprehensive text that treats theory and sta- tistical operations in psychological testing . Chapter 14 deals...with reliability and validity of measures. -44- Reliabilitv and Validity (cont’d.) Cronbach, L., ESSENTIALS OF PSYCHOLOGICAL TESTING , 2nd ed., New...Commandant of the Marine Corps (Code RD) And Monitored By Personnel and Training Research Programs Psychological Sciences Division Office of Naval

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training

PubMed Central

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R.

2015-01-01

Background. Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. Methods. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Results. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. Conclusion. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines. PMID:26417378

A Novel Application of Eddy Current Braking for Functional Strength Training during Gait

PubMed Central

Washabaugh, Edward P.; Claflin, Edward S.; Gillespie, R. Brent; Krishnan, Chandramouli

2016-01-01

Functional strength training is becoming increasingly popular when rehabilitating individuals with neurological injury such as stroke or cerebral palsy. Typically, resistance during walking is provided using cable robots or weights that are secured to the distal shank of the subject. However, there exists no device that is wearable and capable of providing resistance across the joint, allowing over ground gait training. In this study, we created a lightweight and wearable device using eddy current braking to provide resistance to the knee. We then validated the device by having subjects wear it during a walking task through varying resistance levels. Electromyography and kinematics were collected to assess the biomechanical effects of the device on the wearer. We found that eddy current braking provided resistance levels suitable for functional strength training of leg muscles in a package that is both lightweight and wearable. Applying resistive forces at the knee joint during gait resulted in significant increases in muscle activation of many of the muscles tested. A brief period of training also resulted in significant aftereffects once the resistance was removed. These results support the feasibility of the device for functional strength training during gait. Future research is warranted to test the clinical potential of the device in an injured population. PMID:26817456

Review of Modelling Techniques for In Vivo Muscle Force Estimation in the Lower Extremities during Strength Training.

PubMed

Schellenberg, Florian; Oberhofer, Katja; Taylor, William R; Lorenzetti, Silvio

2015-01-01

Knowledge of the musculoskeletal loading conditions during strength training is essential for performance monitoring, injury prevention, rehabilitation, and training design. However, measuring muscle forces during exercise performance as a primary determinant of training efficacy and safety has remained challenging. In this paper we review existing computational techniques to determine muscle forces in the lower limbs during strength exercises in vivo and discuss their potential for uptake into sports training and rehabilitation. Muscle forces during exercise performance have almost exclusively been analysed using so-called forward dynamics simulations, inverse dynamics techniques, or alternative methods. Musculoskeletal models based on forward dynamics analyses have led to considerable new insights into muscular coordination, strength, and power during dynamic ballistic movement activities, resulting in, for example, improved techniques for optimal performance of the squat jump, while quasi-static inverse dynamics optimisation and EMG-driven modelling have helped to provide an understanding of low-speed exercises. The present review introduces the different computational techniques and outlines their advantages and disadvantages for the informed usage by nonexperts. With sufficient validation and widespread application, muscle force calculations during strength exercises in vivo are expected to provide biomechanically based evidence for clinicians and therapists to evaluate and improve training guidelines.

A Novel Application of Eddy Current Braking for Functional Strength Training During Gait.

PubMed

Washabaugh, Edward P; Claflin, Edward S; Gillespie, R Brent; Krishnan, Chandramouli

2016-09-01

Functional strength training is becoming increasingly popular when rehabilitating individuals with neurological injury such as stroke or cerebral palsy. Typically, resistance during walking is provided using cable robots or weights that are secured to the distal shank of the subject. However, there exists no device that is wearable and capable of providing resistance across the joint, allowing over ground gait training. In this study, we created a lightweight and wearable device using eddy current braking to provide resistance to the knee. We then validated the device by having subjects wear it during a walking task through varying resistance levels. Electromyography and kinematics were collected to assess the biomechanical effects of the device on the wearer. We found that eddy current braking provided resistance levels suitable for functional strength training of leg muscles in a package that is both lightweight and wearable. Applying resistive forces at the knee joint during gait resulted in significant increases in muscle activation of many of the muscles tested. A brief period of training also resulted in significant aftereffects once the resistance was removed. These results support the feasibility of the device for functional strength training during gait. Future research is warranted to test the clinical potential of the device in an injured population.

A model of four hierarchical levels to train Chinese residents' teaching skills for "practice-based learning and improvement" competency.

PubMed

Yang, Ying-Ying; Yang, Ling-Yu; Hsu, Hui-Chi; Huang, Chia-Chang; Huang, Chin-Chou; Kirby, Ralph; Cheng, Hao Min; Chang, Ching-Chi; Chuang, Chiao-Lin; Liang, Jen-Feng; Lin, Chun-Chi; Lee, Wei-Shin; Ho, Shung-Tai; Lee, Fa-Yauh

2015-01-01

The current study focused on validating a protocol for training and auditing the resident's practice-based learning and improvement (PBLI) and quality improvement (QI) competencies for primary care. Twelve second-year (R2), 12 first-year (R1) and 12 postgraduate year-1 residents were enrolled into group A, B and C, respectively, as trainees. After three training protocols had been completed, a writing test, self-assessed questionnaire and mini-OSTE and end-of-rotation assessment were used in auditing the PBLI competency, performance and teaching ability of trainees. Baseline expert-assessed PBLI and QI knowledge application tool writing scores were low for the R1 and R2 residents. After three training protocols, PBLI and QI proficiencies, performance and teaching abilities were improved to similar levels cross the three training levels of residents based on the expert-assessed writing test-audited assessments and on the faculty and standardized clerk-assessed end-of-rotation-/mini-OSTE-audited assessments. The different four-level hierarchical protocols used to teach group A, B and C were equally beneficial and fitted their needs; namely the different levels of the trainees. Specifically, each level was able to augment their PBLI and QI proficiency. This educational intervention helps medical institutions to train residents as PBLI instructors.

Discovery and validation of gene classifiers for endocrine-disrupting chemicals in zebrafish (danio rerio)

PubMed Central

2012-01-01

Background Development and application of transcriptomics-based gene classifiers for ecotoxicological applications lag far behind those of biomedical sciences. Many such classifiers discovered thus far lack vigorous statistical and experimental validations. A combination of genetic algorithm/support vector machines and genetic algorithm/K nearest neighbors was used in this study to search for classifiers of endocrine-disrupting chemicals (EDCs) in zebrafish. Searches were conducted on both tissue-specific and tissue-combined datasets, either across the entire transcriptome or within individual transcription factor (TF) networks previously linked to EDC effects. Candidate classifiers were evaluated by gene set enrichment analysis (GSEA) on both the original training data and a dedicated validation dataset. Results Multi-tissue dataset yielded no classifiers. Among the 19 chemical-tissue conditions evaluated, the transcriptome-wide searches yielded classifiers for six of them, each having approximately 20 to 30 gene features unique to a condition. Searches within individual TF networks produced classifiers for 15 chemical-tissue conditions, each containing 100 or fewer top-ranked gene features pooled from those of multiple TF networks and also unique to each condition. For the training dataset, 10 out of 11 classifiers successfully identified the gene expression profiles (GEPs) of their targeted chemical-tissue conditions by GSEA. For the validation dataset, classifiers for prochloraz-ovary and flutamide-ovary also correctly identified the GEPs of corresponding conditions while no classifier could predict the GEP from prochloraz-brain. Conclusions The discrepancies in the performance of these classifiers were attributed in part to varying data complexity among the conditions, as measured to some degree by Fisher’s discriminant ratio statistic. This variation in data complexity could likely be compensated by adjusting sample size for individual chemical-tissue conditions, thus suggesting a need for a preliminary survey of transcriptomic responses before launching a full scale classifier discovery effort. Classifier discovery based on individual TF networks could yield more mechanistically-oriented biomarkers. GSEA proved to be a flexible and effective tool for application of gene classifiers but a similar and more refined algorithm, connectivity mapping, should also be explored. The distribution characteristics of classifiers across tissues, chemicals, and TF networks suggested a differential biological impact among the EDCs on zebrafish transcriptome involving some basic cellular functions. PMID:22849515

In silico target prediction for elucidating the mode of action of herbicides including prospective validation.

PubMed

Chiddarwar, Rucha K; Rohrer, Sebastian G; Wolf, Antje; Tresch, Stefan; Wollenhaupt, Sabrina; Bender, Andreas

2017-01-01

The rapid emergence of pesticide resistance has given rise to a demand for herbicides with new mode of action (MoA). In the agrochemical sector, with the availability of experimental high throughput screening (HTS) data, it is now possible to utilize in silico target prediction methods in the early discovery phase to suggest the MoA of a compound via data mining of bioactivity data. While having been established in the pharmaceutical context, in the agrochemical area this approach poses rather different challenges, as we have found in this work, partially due to different chemistry, but even more so due to different (usually smaller) amounts of data, and different ways of conducting HTS. With the aim to apply computational methods for facilitating herbicide target identification, 48,000 bioactivity data against 16 herbicide targets were processed to train Laplacian modified Naïve Bayesian (NB) classification models. The herbicide target prediction model ("HerbiMod") is an ensemble of 16 binary classification models which are evaluated by internal, external and prospective validation sets. In addition to the experimental inactives, 10,000 random agrochemical inactives were included in the training process, which showed to improve the overall balanced accuracy of our models up to 40%. For all the models, performance in terms of balanced accuracy of≥80% was achieved in five-fold cross validation. Ranking target predictions was addressed by means of z-scores which improved predictivity over using raw scores alone. An external testset of 247 compounds from ChEMBL and a prospective testset of 394 compounds from BASF SE tested against five well studied herbicide targets (ACC, ALS, HPPD, PDS and PROTOX) were used for further validation. Only 4% of the compounds in the external testset lied in the applicability domain and extrapolation (and correct prediction) was hence impossible, which on one hand was surprising, and on the other hand illustrated the utilization of using applicability domains in the first place. However, performance better than 60% in balanced accuracy was achieved on the prospective testset, where all the compounds fell within the applicability domain, and which hence underlines the possibility of using target prediction also in the area of agrochemicals. Copyright © 2016 Elsevier Inc. All rights reserved.

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

Development and Validity of a Silicone Renal Tumor Model for Robotic Partial Nephrectomy Training.

PubMed

Monda, Steven M; Weese, Jonathan R; Anderson, Barrett G; Vetter, Joel M; Venkatesh, Ramakrishna; Du, Kefu; Andriole, Gerald L; Figenshau, Robert S

2018-04-01

To provide a training tool to address the technical challenges of robot-assisted laparoscopic partial nephrectomy, we created silicone renal tumor models using 3-dimensional printed molds of a patient's kidney with a mass. In this study, we assessed the face, content, and construct validity of these models. Surgeons of different training levels completed 4 simulations on silicone renal tumor models. Participants were surveyed on the usefulness and realism of the model as a training tool. Performance was measured using operation-specific metrics, self-reported operative demands (NASA Task Load Index [NASA TLX]), and blinded expert assessment (Global Evaluative Assessment of Robotic Surgeons [GEARS]). Twenty-four participants included attending urologists, endourology fellows, urology residents, and medical students. Post-training surveys of expert participants yielded mean results of 79.2 on the realism of the model's overall feel and 90.2 on the model's overall usefulness for training. Renal artery clamp times and GEARS scores were significantly better in surgeons further in training (P ≤.005 and P ≤.025). Renal artery clamp times, preserved renal parenchyma, positive margins, NASA TLX, and GEARS scores were all found to improve across trials (P <.001, P = .025, P = .024, P ≤.020, and P ≤.006, respectively). Face, content, and construct validity were demonstrated in the use of a silicone renal tumor model in a cohort of surgeons of different training levels. Expert participants deemed the model useful and realistic. Surgeons of higher training levels performed better than less experienced surgeons in various study metrics, and improvements within individuals were observed over sequential trials. Future studies should aim to assess model predictive validity, namely, the association between model performance improvements and improvements in live surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

Can training improve the quality of inferences made by raters in competency modeling? A quasi-experiment.

PubMed

Lievens, Filip; Sanchez, Juan I

2007-05-01

A quasi-experiment was conducted to investigate the effects of frame-of-reference training on the quality of competency modeling ratings made by consultants. Human resources consultants from a large consulting firm were randomly assigned to either a training or a control condition. The discriminant validity, interrater reliability, and accuracy of the competency ratings were significantly higher in the training group than in the control group. Further, the discriminant validity and interrater reliability of competency inferences were highest among an additional group of trained consultants who also had competency modeling experience. Together, these results suggest that procedural interventions such as rater training can significantly enhance the quality of competency modeling. 2007 APA, all rights reserved

[The evaluation of nursing graduates' scientific reasoning and oral and written communication].

PubMed

Demandes, Ingrid; Latrach, Cecilia A; Febre, Naldy Pamela; Muñoz, Claudia; Torres, Pamela; Retamal, Jessica

2012-08-01

This descriptive, cross-sectional study was performed in Santiago de Chile, with the objective to evaluate the scientific reasoning and the oral and written communication of nursing graduates. The sample consisted of 37 nursing graduates who participated in the three stages of the study: I) creation and validation of the instrument; II) training the faculty participating in the study to apply the instrument uniformly; and III) application of the instrument and data analysis. The data show different percentages regarding this competency, with the predominance of scientific reasoning (83.16%), followed by oral and written communication (78.37%). In conclusion, this study demonstrates the value for nursing schools to implement a formal evaluation that allows for determining the profile of nursing graduates, guaranteeing the quality of their training and education.

Derivation & validation of glycosylated haemoglobin (HbA1c) cut-off value as a diagnostic test for type 2 diabetes in south Indian population

PubMed Central

Mohan, Alladi; Reddy, S. Aparna; Sachan, Alok; Sarma, K.V.S.; Kumar, D. Prabath; Panchagnula, Mahesh V.; Rao, P.V.L.N. Srinivasa; Kumar, B. Siddhartha; Krishnaprasanthi, P.

2016-01-01

Background & Objectives: Glycosylated haemoglobin (HbA1c) has been in use for more than a decade, as a diagnostic test for type 2 diabetes. Validity of HbA1c needs to be established in the ethnic population in which it is intended to be used. The objective of this study was to derive and validate a HbA1c cut-off value for the diagnosis of type 2 diabetes in the ethnic population of Rayalaseema area of south India. Methods: In this cross-sectional study, consecutive patients suspected to have type 2 diabetes underwent fasting plasma glucose (FPG) and 2 h post-load plasma glucose (2 h-PG) measurements after a 75 g glucose load and HbA1c estimation. They were classified as having diabetes as per the American Diabetes Association criteria [(FPG ≥7 mmol/l (≥126 mg/dl) and/or 2 h-PG ≥11.1 mmol/l (≥200 mg/dl)]. In the training data set (n = 342), optimum cut-off value of HbA1c for defining type 2 diabetes was derived by receiver-operator characteristic (ROC) curve method using oral glucose tolerance test results as gold standard. This cut-off was validated in a validation data set (n = 341). Results: On applying HbA1c cut-off value of >6.3 per cent (45 mmol/mol) to the training data set, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for diagnosing type 2 diabetes were calculated to be 90.6, 85.2, 80.8 and 93.0 per cent, respectively. When the same cut-off value was applied to the validation data set, sensitivity, specificity, PPV and NPV were 88.8, 81.9, 74.0 and 92.7 per cent, respectively, although the latter were consistently smaller than the proportions for the training data set, the differences being not significant. Interpretation & conclusions: HbA1c >6.3 per cent (45 mmol/mol) appears to be the optimal cut-off value for the diagnosis of type 2 diabetes applicable to the ethnic population of Rayalaseema area of Andhra Pradesh state in south India. PMID:27934801

Validation of the train energy and dynamics simulator (TEDS).

DOT National Transportation Integrated Search

2015-01-01

FRA has developed Train Energy and Dynamics Simulator (TEDS) based upon a longitudinal train dynamics and operations : simulation model which allows users to conduct safety and risk evaluations, incident investigations, studies of train operations, :...

A succinct rating scale for radiology report quality

PubMed Central

Yang, Chengwu; Ouyang, Tao; Peterson, Christine M; Sarwani, Nabeel I; Tappouni, Rafel; Bruno, Michael

2014-01-01

Context: Poorly written radiology reports are common among residents and are a significant challenge for radiology education. While training may improve report quality, a professionally developed reliable and valid scale to measure report quality does not exist. Objectives: To develop a measurement tool for report quality, the quality of report scale, with rigorous validation through empirical data. Methods: A research team of an experienced psychometrician and six senior radiologists conducted qualitative and quantitative studies. Five items were identified for the quality of report scale, each measuring a distinct aspect of report quality. Two dedicated training sessions were designed and implemented to help residents generate high-quality reports. In a blinded fashion, the quality of report scale was applied to 804 randomly selected reports issued before (n = 403) and after (n = 401) training. Full-scale psychometrical assessments were implemented onto the quality of report scale’s item- and scale-scores from the reports. The quality of report scale scores were correlated with report professionalism and attendings’ preference and were compared pre-/post-training. Results: The quality of report scale showed sound psychometrical properties, with high validity and reliability. Reports with higher quality of report scale score were more professional and preferable by attendings. Training improved the quality of report scale score, empirically validating the quality of report scale further. Conclusion: While succinct and practitioner friendly, the quality of report scale is a reliable and valid measure of radiology report quality and has the potential to be easily adapted to other fields such as pathology, where similar training would be beneficial. PMID:26770756

[Effect of high-intensity interval training on the reduction of glycosylated hemoglobin in type-2 diabetic adult patients].

PubMed

Aguilera Eguía, Raúl Alberto; Russell Guzmán, Javier Antonio; Soto Muñoz, Marcelo Enrique; Villegas González, Bastián Eduardo; Poblete Aro, Carlos Emilio; Ibacache Palma, Alejandro

2015-03-05

Type 2 diabetes mellitus is one of the major non-communicable chronic diseases in the world. Its prevalence in Chile is significant, and complications associated with this disease involve great costs, which is why prevention and treatment of this condition are essential. Physical exercise is an effective means for prevention and treatment of type 2 diabetes mellitus. The emergence of new forms of physical training, such as "high intensity interval training", presents novel therapeutic alternatives for patients and health care professionals. To assess the validity and applicability of the results regarding the effectiveness of high intensity interval training in reducing glycosylated hemoglobin in adult patients with type 2 diabetes mellitus and answer the following question: In subjects with type 2 diabetes, can the method of high intensity interval training compared to moderate intensity exercise decrease glycosylated hemoglobin? We performed a critical analysis of the article "Feasibility and preliminary effectiveness of high intensity interval training in type 2 diabetes". We found no significant differences in the amount of glycosylated hemoglobin between groups of high intensity interval training and moderate-intensity exercise upon completion of the study (p>0.05). In adult patients with type 2 diabetes mellitus, high intensity interval training does not significantly improve glycosylated hemoglobin levels. Despite this, the high intensity interval training method shows as much improvement in body composition and physical condition as the moderate intensity exercise program.

European validation of The Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis from the perspective of patients with osteoarthritis of the knee or hip.

PubMed

Weigl, Martin; Wild, Heike

2017-09-15

To validate the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis from the patient perspective in Europe. This multicenter cross-sectional study involved 375 patients with knee or hip osteoarthritis. Trained health professionals completed the Comprehensive Core Set, and patients completed the Short-Form 36 questionnaire. Content validity was evaluated by calculating prevalences of impairments in body function and structures, limitations in activities and participation and environmental factors, which were either barriers or facilitators. Convergent construct validity was evaluated by correlating the International Classification of Functioning, Disability and Health categories with the Short-Form 36 Physical Component Score and the SF-36 Mental Component Score in a subgroup of 259 patients. The prevalences of all body function, body structure and activities and participation categories were >40%, >32% and >20%, respectively, and all environmental factors were relevant for >16% of patients. Few categories showed relevant differences between knee and hip osteoarthritis. All body function categories and all but two activities and participation categories showed significant correlations with the Physical Component Score. Body functions from the ICF chapter Mental Functions showed higher correlations with the Mental Component Score than with the Physical Component Score. This study supports the validity of the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis. Implications for Rehabilitation Comprehensive International Classification of Functioning, Disability and Health Core Sets were developed as practical tools for application in multidisciplinary assessments. The validity of the Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis in this study supports its application in European patients with osteoarthritis. The differences in results between this Europe validation study and a previous Singaporean validation study underscore the need to validate the International Classification of Functioning, Disability and Health Core Sets in different regions of the world.

Transfer of Training.

ERIC Educational Resources Information Center

1996

This document consists of three papers presented at a symposium on transfer of training moderated by Gene Roth at the 1996 conference of the Academy of Human Resource Development (AHRD). "Validation of a Transfer Climate Instrument" (Reid A. Bates et al.) reports a study that attempted to validate Rouiller and Goldstein's (1993) eight-factor…

Culture Training: Validation Evidence for the Culture Assimilator.

ERIC Educational Resources Information Center

Mitchell, Terence R.; And Others

The culture assimilator, a programed self-instructional approach to culture training, is described and a series of laboratory experiments and field studies validating the culture assimilator are reviewed. These studies show that the culture assimilator is an effective method of decreasing some of the stress experienced when one works with people…

77 FR 71473 - Agency Information Collection Activities: Requests for Comments; Clearance of Renewed Approval of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-30

... validating and maintaining the effectiveness of air carrier training program curriculum content. DATES... training. AQP is continuously validated through the collection and analysis of trainee performance. Data collection and analysis processes ensure that the certificate holder provides performance information on its...

Non-parametric directionality analysis - Extension for removal of a single common predictor and application to time series.

PubMed

Halliday, David M; Senik, Mohd Harizal; Stevenson, Carl W; Mason, Rob

2016-08-01

The ability to infer network structure from multivariate neuronal signals is central to computational neuroscience. Directed network analyses typically use parametric approaches based on auto-regressive (AR) models, where networks are constructed from estimates of AR model parameters. However, the validity of using low order AR models for neurophysiological signals has been questioned. A recent article introduced a non-parametric approach to estimate directionality in bivariate data, non-parametric approaches are free from concerns over model validity. We extend the non-parametric framework to include measures of directed conditional independence, using scalar measures that decompose the overall partial correlation coefficient summatively by direction, and a set of functions that decompose the partial coherence summatively by direction. A time domain partial correlation function allows both time and frequency views of the data to be constructed. The conditional independence estimates are conditioned on a single predictor. The framework is applied to simulated cortical neuron networks and mixtures of Gaussian time series data with known interactions. It is applied to experimental data consisting of local field potential recordings from bilateral hippocampus in anaesthetised rats. The framework offers a non-parametric approach to estimation of directed interactions in multivariate neuronal recordings, and increased flexibility in dealing with both spike train and time series data. The framework offers a novel alternative non-parametric approach to estimate directed interactions in multivariate neuronal recordings, and is applicable to spike train and time series data. Copyright © 2016 Elsevier B.V. All rights reserved.

A consensus-based framework for design, validation, and implementation of simulation-based training curricula in surgery.

PubMed

Zevin, Boris; Levy, Jeffrey S; Satava, Richard M; Grantcharov, Teodor P

2012-10-01

Simulation-based training can improve technical and nontechnical skills in surgery. To date, there is no consensus on the principles for design, validation, and implementation of a simulation-based surgical training curriculum. The aim of this study was to define such principles and formulate them into an interoperable framework using international expert consensus based on the Delphi method. Literature was reviewed, 4 international experts were queried, and consensus conference of national and international members of surgical societies was held to identify the items for the Delphi survey. Forty-five international experts in surgical education were invited to complete the online survey by ranking each item on a Likert scale from 1 to 5. Consensus was predefined as Cronbach's α ≥0.80. Items that 80% of experts ranked as ≥4 were included in the final framework. Twenty-four international experts with training in general surgery (n = 11), orthopaedic surgery (n = 2), obstetrics and gynecology (n = 3), urology (n = 1), plastic surgery (n = 1), pediatric surgery (n = 1), otolaryngology (n = 1), vascular surgery (n = 1), military (n = 1), and doctorate-level educators (n = 2) completed the iterative online Delphi survey. Consensus among participants was achieved after one round of the survey (Cronbach's α = 0.91). The final framework included predevelopment analysis; cognitive, psychomotor, and team-based training; curriculum validation evaluation and improvement; and maintenance of training. The Delphi methodology allowed for determination of international expert consensus on the principles for design, validation, and implementation of a simulation-based surgical training curriculum. These principles were formulated into a framework that can be used internationally across surgical specialties as a step-by-step guide for the development and validation of future simulation-based training curricula. Copyright © 2012 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Construct and concurrent validity of a Nintendo Wii video game made for training basic laparoscopic skills.

PubMed

Jalink, M B; Goris, J; Heineman, E; Pierie, J P E N; ten Cate Hoedemaker, H O

2014-02-01

Virtual reality (VR) laparoscopic simulators have been around for more than 10 years and have proven to be cost- and time-effective in laparoscopic skills training. However, most simulators are, in our experience, considered less interesting by residents and are often poorly accessible. Consequently, these devices are rarely used in actual training. In an effort to make a low-cost and more attractive simulator, a custom-made Nintendo Wii game was developed. This game could ultimately be used to train the same basic skills as VR laparoscopic simulators ought to. Before such a video game can be implemented into a surgical training program, it has to be validated according to international standards. The main goal of this study was to test construct and concurrent validity of the controls of a prototype of the game. In this study, the basic laparoscopic skills of experts (surgeons, urologists, and gynecologists, n = 15) were compared to those of complete novices (internists, n = 15) using the Wii Laparoscopy (construct validity). Scores were also compared to the Fundamentals of Laparoscopy (FLS) Peg Transfer test, an already established assessment method for measuring basic laparoscopic skills (concurrent validity). Results showed that experts were 111 % faster (P = 0.001) on the Wii Laparoscopy task than novices. Also, scores of the FLS Peg Transfer test and the Wii Laparoscopy showed a significant, high correlation (r = 0.812, P < 0.001). The prototype setup of the Wii Laparoscopy possesses solid construct and concurrent validity.

A novel classifier based on three preoperative tumor markers predicting the cancer-specific survival of gastric cancer (CEA, CA19-9 and CA72-4).

PubMed

Guo, Jing; Chen, Shangxiang; Li, Shun; Sun, Xiaowei; Li, Wei; Zhou, Zhiwei; Chen, Yingbo; Xu, Dazhi

2018-01-12

Several studies have highlighted the prognostic value of the individual and the various combinations of the tumor markers for gastric cancer (GC). Our study was designed to assess establish a new novel model incorporating carcino-embryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4). A total of 1,566 GC patients (Primary cohort) between Jan 2000 and July 2013 were analyzed. The Primary cohort was randomly divided into Training set (n=783) and Validation set (n=783). A three-tumor marker classifier was developed in the Training set and validated in the Validation set by multivariate regression and risk-score analysis. We have identified a three-tumor marker classifier (including CEA, CA19-9 and CA72-4) for the cancer specific survival (CSS) of GC (p<0.001). Consistent results were obtained in the both Training set and Validation set. Multivariate analysis showed that the classifier was an independent predictor of GC (All p value <0.001 in the Training set, Validation set and Primary cohort). Furthermore, when the leave-one-out approach was performed, the classifier showed superior predictive value to the individual or two of them (with the highest AUC (Area Under Curve); 0.618 for the Training set, and 0.625 for the Validation set), which ascertained its predictive value. Our three-tumor marker classifier is closely associated with the CSS of GC and may serve as a novel model for future decisions concerning treatments.

Might telesonography be a new useful diagnostic tool aboard merchant ships? A pilot study.

PubMed

Nikolić, Nebojsa; Mozetić, Vladimir; Modrcin, Bob; Jaksić, Slaven

2006-01-01

Developments of new, ultra-light diagnostic ultrasound systems (UTS) and modern satellite telecommunication networks are opening new potential applications for diagnostic sonography. One such area is maritime medicine. It is our belief that ship officers can be trained to use diagnostic ultrasound systems with the aim to generate ultrasound images of sufficient quality to be interpreted by medical professionals qualified to read sonograms. To test our thesis we included lectures and hands on scanning practice to the current maritime medicine curriculum at the Faculty of Maritime Studies at the University of Rijeka. Following the didactic and practical training all participating students examined several patients, some with pathology some without. Images obtained by students were then submitted for interpretation to a qualified physician (specialist of general surgery trained in UTS) who was unaware of the patient's pathology. In total, 37 students performed 37 examinations and made 45 ultrasound images, on 3 patients. In this paper, results on this pilot study are presented. It is possible to teach ship officers to produce diagnostically usable ultrasound pictures aboard ships at sea. But before reaching final conclusion about applicability of telesonography on board merchant ships, further studies are necessary, that would include studies of economic feasibility, and on validity of introducing such a diagnostic tool to the maritime medical practice.

Comparative assessment of three standardized robotic surgery training methods.

PubMed

Hung, Andrew J; Jayaratna, Isuru S; Teruya, Kara; Desai, Mihir M; Gill, Inderbir S; Goh, Alvin C

2013-10-01

To evaluate three standardized robotic surgery training methods, inanimate, virtual reality and in vivo, for their construct validity. To explore the concept of cross-method validity, where the relative performance of each method is compared. Robotic surgical skills were prospectively assessed in 49 participating surgeons who were classified as follows: 'novice/trainee': urology residents, previous experience <30 cases (n = 38) and 'experts': faculty surgeons, previous experience ≥30 cases (n = 11). Three standardized, validated training methods were used: (i) structured inanimate tasks; (ii) virtual reality exercises on the da Vinci Skills Simulator (Intuitive Surgical, Sunnyvale, CA, USA); and (iii) a standardized robotic surgical task in a live porcine model with performance graded by the Global Evaluative Assessment of Robotic Skills (GEARS) tool. A Kruskal-Wallis test was used to evaluate performance differences between novices and experts (construct validity). Spearman's correlation coefficient (ρ) was used to measure the association of performance across inanimate, simulation and in vivo methods (cross-method validity). Novice and expert surgeons had previously performed a median (range) of 0 (0-20) and 300 (30-2000) robotic cases, respectively (P < 0.001). Construct validity: experts consistently outperformed residents with all three methods (P < 0.001). Cross-method validity: overall performance of inanimate tasks significantly correlated with virtual reality robotic performance (ρ = -0.7, P < 0.001) and in vivo robotic performance based on GEARS (ρ = -0.8, P < 0.0001). Virtual reality performance and in vivo tissue performance were also found to be strongly correlated (ρ = 0.6, P < 0.001). We propose the novel concept of cross-method validity, which may provide a method of evaluating the relative value of various forms of skills education and assessment. We externally confirmed the construct validity of each featured training tool. © 2013 BJU International.

Pervasive Sound Sensing: A Weakly Supervised Training Approach.

PubMed

Kelly, Daniel; Caulfield, Brian

2016-01-01

Modern smartphones present an ideal device for pervasive sensing of human behavior. Microphones have the potential to reveal key information about a person's behavior. However, they have been utilized to a significantly lesser extent than other smartphone sensors in the context of human behavior sensing. We postulate that, in order for microphones to be useful in behavior sensing applications, the analysis techniques must be flexible and allow easy modification of the types of sounds to be sensed. A simplification of the training data collection process could allow a more flexible sound classification framework. We hypothesize that detailed training, a prerequisite for the majority of sound sensing techniques, is not necessary and that a significantly less detailed and time consuming data collection process can be carried out, allowing even a nonexpert to conduct the collection, labeling, and training process. To test this hypothesis, we implement a diverse density-based multiple instance learning framework, to identify a target sound, and a bag trimming algorithm, which, using the target sound, automatically segments weakly labeled sound clips to construct an accurate training set. Experiments reveal that our hypothesis is a valid one and results show that classifiers, trained using the automatically segmented training sets, were able to accurately classify unseen sound samples with accuracies comparable to supervised classifiers, achieving an average F -measure of 0.969 and 0.87 for two weakly supervised datasets.

Developing effective health and safety training materials for workers in beryllium-using industries.

PubMed

Mayer, A S; Brazile, W J; Erb, S A; Barker, E A; Miller, C M; Mroz, M M; Maier, L A; Van Dyke, M V

2013-07-01

Despite reduced workplace exposures, beryllium sensitization and chronic beryllium disease still occur. Effective health and safety training is needed. Through an Occupational Safety and Health Administration (OSHA) Targeted Topic Training grant and company partners, we developed a training program. Evaluation and validation included knowledge and training reaction assessments and training impact survey. We describe herein the iterative, five-pronged approach: (1) needs assessment; (2) materials development; (3) pilot-testing, evaluation, and material revisions; (4) worker training; and (5) evaluation and validation. Mean posttraining test score increased 14% (82% to 96%; P < 0.005) and were unchanged at 90-day follow-up (94%; P = 0.744). In addition, 49% reported making changes in work practices. The use of a five-pronged training program was effective and well received and resulted in improved work practices. These materials are available on the OSHA Web site.

Assessing students' communication skills: validation of a global rating.

PubMed

Scheffer, Simone; Muehlinghaus, Isabel; Froehmel, Annette; Ortwein, Heiderose

2008-12-01

Communication skills training is an accepted part of undergraduate medical programs nowadays. In addition to learning experiences its importance should be emphasised by performance-based assessment. As detailed checklists have been shown to be not well suited for the assessment of communication skills for different reasons, this study aimed to validate a global rating scale. A Canadian instrument was translated to German and adapted to assess students' communication skills during an end-of-semester-OSCE. Subjects were second and third year medical students at the reformed track of the Charité-Universitaetsmedizin Berlin. Different groups of raters were trained to assess students' communication skills using the global rating scale. Validity testing included concurrent validity and construct validity: Judgements of different groups of raters were compared to expert ratings as a defined gold standard. Furthermore, the amount of agreement between scores obtained with this global rating scale and a different instrument for assessing communication skills was determined. Results show that communication skills can be validly assessed by trained non-expert raters as well as standardised patients using this instrument.

Optimal SVM parameter selection for non-separable and unbalanced datasets.

PubMed

Jiang, Peng; Missoum, Samy; Chen, Zhao

2014-10-01

This article presents a study of three validation metrics used for the selection of optimal parameters of a support vector machine (SVM) classifier in the case of non-separable and unbalanced datasets. This situation is often encountered when the data is obtained experimentally or clinically. The three metrics selected in this work are the area under the ROC curve (AUC), accuracy, and balanced accuracy. These validation metrics are tested using computational data only, which enables the creation of fully separable sets of data. This way, non-separable datasets, representative of a real-world problem, can be created by projection onto a lower dimensional sub-space. The knowledge of the separable dataset, unknown in real-world problems, provides a reference to compare the three validation metrics using a quantity referred to as the "weighted likelihood". As an application example, the study investigates a classification model for hip fracture prediction. The data is obtained from a parameterized finite element model of a femur. The performance of the various validation metrics is studied for several levels of separability, ratios of unbalance, and training set sizes.

Replicability of sight word training and phonics training in poor readers: a randomised controlled trial

PubMed Central

Kohnen, S; Jones, K; Eve, P; Banales, E; Larsen, L; Castles, A

2015-01-01

Given the importance of effective treatments for children with reading impairment, paired with growing concern about the lack of scientific replication in psychological science, the aim of this study was to replicate a quasi-randomised trial of sight word and phonics training using a randomised controlled trial (RCT) design. One group of poor readers (N = 41) did 8 weeks of phonics training (i.e., phonological decoding) and then 8 weeks of sight word training (i.e., whole-word recognition). A second group did the reverse order of training. Sight word and phonics training each had a large and significant valid treatment effect on trained irregular words and word reading fluency. In addition, combined sight word and phonics training had a moderate and significant valid treatment effect on nonword reading accuracy and fluency. These findings demonstrate the reliability of both phonics and sight word training in treating poor readers in an era where the importance of scientific reliability is under close scrutiny. PMID:26019992

One-Shot Learning of Human Activity With an MAP Adapted GMM and Simplex-HMM.

PubMed

Rodriguez, Mario; Orrite, Carlos; Medrano, Carlos; Makris, Dimitrios

2016-05-10

This paper presents a novel activity class representation using a single sequence for training. The contribution of this representation lays on the ability to train an one-shot learning recognition system, useful in new scenarios where capturing and labeling sequences is expensive or impractical. The method uses a universal background model of local descriptors obtained from source databases available on-line and adapts it to a new sequence in the target scenario through a maximum a posteriori adaptation. Each activity sample is encoded in a sequence of normalized bag of features and modeled by a new hidden Markov model formulation, where the expectation-maximization algorithm for training is modified to deal with observations consisting in vectors in a unit simplex. Extensive experiments in recognition have been performed using one-shot learning over the public datasets Weizmann, KTH, and IXMAS. These experiments demonstrate the discriminative properties of the representation and the validity of application in recognition systems, achieving state-of-the-art results.

Validation of a novel venous duplex ultrasound objective structured assessment of technical skills for the assessment of venous reflux.

PubMed

Jaffer, Usman; Normahani, Pasha; Lackenby, Kimberly; Aslam, Mohammed; Standfield, Nigel J

2015-01-01

Duplex ultrasound measurement of reflux time is central to the diagnosis of venous incompetence. We have developed an assessment tool for Duplex measurement of venous reflux for both simulator and patient-based training. A novel assessment tool, Venous Duplex Ultrasound Assessment of Technical Skills (V-DUOSATS), was developed. A modified DUOSATS was used for simulator training. Participants of varying skill level were invited to viewed an instructional video and were allowed ample time to familiarize with the Duplex equipment. Attempts made by the participants were recorded and independently assessed by 3 expert assessors and 5 novice assessors using the modified V-DUOSATS. "Global" assessment was also done by expert assessors on a 4-point Likert scale. Content, construct, and concurrent validities as well as reliability were evaluated. Content and construct validity as well as reliability were demonstrated. Receiver operator characteristic analysis-established cut points of 19/22 and 21/30 were most appropriate for simulator and patient-based assessment, respectively. We have validated a novel assessment tool for Duplex venous reflux measurement. Further work is required to establish transference validity of simulator training to improve skill in scanning patients. We have developed and validated V-DUOSATS for simulator training. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Balance versus resistance training on postural control in patients with Parkinson's disease: a randomized controlled trial.

PubMed

Santos, Suhaila M; da Silva, Rubens A; Terra, Marcelle B; Almeida, Isabela A; de Melo, Lúcio B; Ferraz, Henrique B

2017-04-01

Evidences have shown that physiotherapy programs may improve the balance of individuals with Parkinson's disease (PD), although it is not clear which specific exercise program is better. The aim of this study was to compare the effectiveness of balance versus resistance training on postural control measures in PD patients. Randomized controlled trial. The study was conducted in a physiotherapy outpatient clinic of a university hospital. A total of 40 PD participants were randomly divided into two groups: balance training (BT) and resistance training (RT). The BT group focused on balance training, functional independence and gait while the RT group performed resistance exercises emphasizing the lower limbs and trunk, both supervised by trained physiotherapists. Therapy sessions were held twice a week (at 60 minutes), totaling 24 sessions. The primary outcome was evaluated by force platform with center of pressure sway measures in different balance conditions and the secondary outcome was evaluated by Balance Evaluation Systems Test (BESTest) scale to determine the effects of the intervention on postural control. Significant improvement of postural control (pre vs. post 15.1 vs. 9.6 cm2) was only reported in favor of BT group (d=1.17) for one-legged stand condition on force platform. The standardized mean difference between groups was significantly (P<0.02), with 36% of improvement for BT vs. 0.07% for RT on this condition. Significant improvement (P<0.05) was also observed in favor of BT (in mean 3.2%) for balance gains in some BESTest scores, when compared to RT group (-0.98%). Postural control in Parkinson's disease is improved when training by a directional and specific balance program than a resistance training program. Balance training is superior to resistance training in regard to improving postural control of individuals with PD. Gold standard instruments (high in cost and difficult to access) were used to assess balance, as well as scales with clinical applicability (low cost, easily acceptable, applicable and valid), which can guide the management of physiotherapists both in their decision-making and in clinical practice.

Implementation and Analysis of ISM 2.4 GHz Wireless Sensor Network Systems in Judo Training Venues

PubMed Central

Lopez-Iturri, Peio; Aguirre, Erik; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2016-01-01

In this work, the performance of ISM 2.4 GHz Wireless Sensor Networks (WSNs) deployed in judo training venues is analyzed. Judo is a very popular martial art, which is practiced by thousands of people not only at the competition level, but also as part of physical education programs at different school levels. There is a great variety of judo training venues, and each one has specific morphological aspects, making them unique scenarios in terms of radio propagation due to the presence of furniture, columns, equipment and the presence of human beings, which is a major issue as the person density within this kind of scenarios could be high. Another key aspect is the electromagnetic interference created by other wireless systems, such as WiFi or other WSNs, which make the radio planning a complex task in terms of coexistence. In order to analyze the impact of these features on the radio propagation and the performance of WSNs, an in-house developed 3D ray launching algorithm has been used. The obtained simulation results have been validated with a measurement campaign carried out in the sport facilities of the Public University of Navarre. The analysis is completed with the inclusion of an application designed to monitor biological constants of judokas, aimed to improve their training procedures. The application, that allows the simultaneous monitoring of multiple judokas (collective workouts) minimizing the efforts of the coach and medical supervisor, is based on commercial off-the-shelf products. The presented assessment of the presence of interfering wireless systems and the presence of human beings within judo training venues shows that an in-depth radio planning is required as these issues can have a great impact in the overall performance of a ISM 2.4 GHz WSN, affecting negatively the potential applications supported by wireless channel. PMID:27509501

Implementation and Analysis of ISM 2.4 GHz Wireless Sensor Network Systems in Judo Training Venues.

PubMed

Lopez-Iturri, Peio; Aguirre, Erik; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2016-08-06

In this work, the performance of ISM 2.4 GHz Wireless Sensor Networks (WSNs) deployed in judo training venues is analyzed. Judo is a very popular martial art, which is practiced by thousands of people not only at the competition level, but also as part of physical education programs at different school levels. There is a great variety of judo training venues, and each one has specific morphological aspects, making them unique scenarios in terms of radio propagation due to the presence of furniture, columns, equipment and the presence of human beings, which is a major issue as the person density within this kind of scenarios could be high. Another key aspect is the electromagnetic interference created by other wireless systems, such as WiFi or other WSNs, which make the radio planning a complex task in terms of coexistence. In order to analyze the impact of these features on the radio propagation and the performance of WSNs, an in-house developed 3D ray launching algorithm has been used. The obtained simulation results have been validated with a measurement campaign carried out in the sport facilities of the Public University of Navarre. The analysis is completed with the inclusion of an application designed to monitor biological constants of judokas, aimed to improve their training procedures. The application, that allows the simultaneous monitoring of multiple judokas (collective workouts) minimizing the efforts of the coach and medical supervisor, is based on commercial off-the-shelf products. The presented assessment of the presence of interfering wireless systems and the presence of human beings within judo training venues shows that an in-depth radio planning is required as these issues can have a great impact in the overall performance of a ISM 2.4 GHz WSN, affecting negatively the potential applications supported by wireless channel.

Training Objectives, Transfer, Validation and Evaluation: A Sri Lankan Study

ERIC Educational Resources Information Center

Wickramasinghe, Vathsala M.

2006-01-01

Using a stratified random sample, this paper examines the training practices of setting objectives, transfer, validation and evaluation in Sri Lanka. The paper further sets out to compare those practices across local, foreign and joint-venture companies based on the assumption that there may be significant differences across companies of different…

Validation of the Military Entrance Physical Strength Capacity Test. Technical Report 610.

ERIC Educational Resources Information Center

Myers, David C.; And Others

A battery of physical ability tests was validated using a predictive, criterion-related strategy. The battery was given to 1,003 female soldiers and 980 male soldiers before they had begun Army Basic Training. Criterion measures which represented physical competency in Basic Training (physical proficiency tests, sick call, profiles, and separation…

Training Paraprofessionals to Target Socialization in Students with ASD: Fidelity of Implementation and Social Validity

ERIC Educational Resources Information Center

Kim, Sunny; Koegel, Robert L.; Koegel, Lynn K.

2017-01-01

Although the literature suggests that it is feasible to train paraprofessionals to effectively implement social interventions for students with Autism Spectrum Disorders (ASD), there is a paucity of research that addresses the social validity of these programs. The present study replicated and extended previous research on paraprofessional…

Toward Construct Validation of a Transfer Climate Instrument. [and] Improving Positive Transfer: A Test of Relapse Prevention Training on Transfer Outcomes.

ERIC Educational Resources Information Center

Holton, Elwood F., III; And Others

1997-01-01

Includes "Toward Construct Validation of a Transfer Climate Instrument" (Holton et al.); "Improving Positive Transfer: A Test of Relapse Prevention Training on Transfer Outcomes" (Burke); "Invited Reaction: Progress or Relapse?" (Newstrom); "Invited Reaction: Theory, Research, and Practice" (Tang);…

Emotion Discrimination Using Spatially Compact Regions of Interest Extracted from Imaging EEG Activity

PubMed Central

Padilla-Buritica, Jorge I.; Martinez-Vargas, Juan D.; Castellanos-Dominguez, German

2016-01-01

Lately, research on computational models of emotion had been getting much attention due to their potential for understanding the mechanisms of emotions and their promising broad range of applications that potentially bridge the gap between human and machine interactions. We propose a new method for emotion classification that relies on features extracted from those active brain areas that are most likely related to emotions. To this end, we carry out the selection of spatially compact regions of interest that are computed using the brain neural activity reconstructed from Electroencephalography data. Throughout this study, we consider three representative feature extraction methods widely applied to emotion detection tasks, including Power spectral density, Wavelet, and Hjorth parameters. Further feature selection is carried out using principal component analysis. For validation purpose, these features are used to feed a support vector machine classifier that is trained under the leave-one-out cross-validation strategy. Obtained results on real affective data show that incorporation of the proposed training method in combination with the enhanced spatial resolution provided by the source estimation allows improving the performed accuracy of discrimination in most of the considered emotions, namely: dominance, valence, and liking. PMID:27489541

Non-invasive fetal sex determination by maternal plasma sequencing and application in X-linked disorder counseling.

PubMed

Pan, Xiaoyu; Zhang, Chunlei; Li, Xuchao; Chen, Shengpei; Ge, Huijuan; Zhang, Yanyan; Chen, Fang; Jiang, Hui; Jiang, Fuman; Zhang, Hongyun; Wang, Wei; Zhang, Xiuqing

2014-12-01

To develop a fetal sex determination method based on maternal plasma sequencing (MPS), assess its performance and potential use in X-linked disorder counseling. 900 cases of MPS data from a previous study were reviewed, in which 100 and 800 cases were used as training and validation set, respectively. The percentage of uniquely mapped sequencing reads on Y chromosome was calculated and used to classify male and female cases. Eight pregnant women who are carriers of Duchenne muscular dystrophy (DMD) mutations were recruited, whose plasma were subjected to multiplex sequencing and fetal sex determination analysis. In the training set, a sensitivity of 96% and false positive rate of 0% for male cases detection were reached in our method. The blinded validation results showed 421 in 423 male cases and 374 in 377 female cases were successfully identified, revealing sensitivity and specificity of 99.53% and 99.20% for fetal sex determination, at as early as 12 gestational weeks. Fetal sex for all eight DMD genetic counseling cases were correctly identified, which were confirmed by amniocentesis. Based on MPS, high accuracy of non-invasive fetal sex determination can be achieved. This method can potentially be used for prenatal genetic counseling.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

‘My Virtual Dream’: Collective Neurofeedback in an Immersive Art Environment

PubMed Central

Kovacevic, Natasha; Ritter, Petra; Tays, William; Moreno, Sylvain; McIntosh, Anthony Randal

2015-01-01

While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored. Motivated to overcome this limitation, we conducted a large-scale experiment with electroencephalography (EEG) based brain-computer interface (BCI) technology as part of an immersive multi-media science-art installation. Data from 523 participants were collected in a single night. The exploratory experiment was designed as a collective computer game where players manipulated mental states of relaxation and concentration with neurofeedback targeting modulation of relative spectral power in alpha and beta frequency ranges. Besides validating robust time-of-night effects, gender differences and distinct spectral power patterns for the two mental states, our results also show differences in neurofeedback learning outcome. The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min). Moreover, we found that participants' baseline brain activity predicted subsequent neurofeedback beta training, indicating state-dependent learning. Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions. PMID:26154513

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valencia, Antoni; Prous, Josep; Mora, Oscar

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less

Validation and cross-cultural pilot testing of compliance with standard precautions scale: self-administered instrument for clinical nurses.

PubMed

Lam, Simon C

2014-05-01

To perform detailed psychometric testing of the compliance with standard precautions scale (CSPS) in measuring compliance with standard precautions of clinical nurses and to conduct cross-cultural pilot testing and assess the relevance of the CSPS on an international platform. A cross-sectional and correlational design with repeated measures. Nursing students from a local registered nurse training university, nurses from different hospitals in Hong Kong, and experts in an international conference. The psychometric properties of the CSPS were evaluated via internal consistency, 2-week and 3-month test-retest reliability, concurrent validation, and construct validation. The cross-cultural pilot testing and relevance check was examined by experts on infection control from various developed and developing regions. Among 453 participants, 193 were nursing students, 165 were enrolled nurses, and 95 were registered nurses. The results showed that the CSPS had satisfactory reliability (Cronbach α = 0.73; intraclass correlation coefficient, 0.79 for 2-week test-retest and 0.74 for 3-month test-retest) and validity (optimum correlation with criterion measure; r = 0.76, P < .001; satisfactory results on known-group method and hypothesis testing). A total of 19 experts from 16 countries assured that most of the CSPS findings were relevant and globally applicable. The CSPS demonstrated satisfactory results on the basis of the standard international criteria on psychometric testing, which ascertained the reliability and validity of this instrument in measuring the compliance of clinical nurses with standard precautions. The cross-cultural pilot testing further reinforced the instrument's relevance and applicability in most developed and developing regions.

Correcting Evaluation Bias of Relational Classifiers with Network Cross Validation

DTIC Science & Technology

2010-01-01

classi- fication algorithms: simple random resampling (RRS), equal-instance random resampling (ERS), and network cross-validation ( NCV ). The first two... NCV procedure that eliminates overlap between test sets altogether. The procedure samples for k disjoint test sets that will be used for evaluation...propLabeled ∗ S) nodes from train Pool in f erenceSet =network − trainSet F = F ∪ < trainSet, test Set, in f erenceSet > end for output: F NCV addresses

Assessing lesbian, gay, and bisexual affirmative training in couple and family therapy: establishing the validity of the Faculty Version of the Affirmative Training Inventory.

PubMed

McGeorge, Christi R; Carlson, Thomas S; Toomey, Russell B

2015-01-01

This study established the validity and factor structure of the Faculty Version of the Affirmative Training Inventory (ATI-F), which assesses faculty members' perceptions of the level of lesbian, gay, and bisexual (LGB) affirmative training that occurs in clinical programs. Additionally, this study examined the latent associations among the subscales of the ATI-F and three convergent validity items utilizing a sample of 117 faculty members from accredited family therapy programs. The findings provide empirical support for the relationship between including classroom content on LGB affirmative therapy and faculty members' beliefs about LGB individuals and relationships. Specifically, faculty members who report more positive beliefs about LGB clients appear to be more likely to include LGB affirmative therapy content in the courses they teach. © 2013 American Association for Marriage and Family Therapy.

Integrated Process Modeling-A Process Validation Life Cycle Companion.

PubMed

Zahel, Thomas; Hauer, Stefan; Mueller, Eric M; Murphy, Patrick; Abad, Sandra; Vasilieva, Elena; Maurer, Daniel; Brocard, Cécile; Reinisch, Daniela; Sagmeister, Patrick; Herwig, Christoph

2017-10-17

During the regulatory requested process validation of pharmaceutical manufacturing processes, companies aim to identify, control, and continuously monitor process variation and its impact on critical quality attributes (CQAs) of the final product. It is difficult to directly connect the impact of single process parameters (PPs) to final product CQAs, especially in biopharmaceutical process development and production, where multiple unit operations are stacked together and interact with each other. Therefore, we want to present the application of Monte Carlo (MC) simulation using an integrated process model (IPM) that enables estimation of process capability even in early stages of process validation. Once the IPM is established, its capability in risk and criticality assessment is furthermore demonstrated. IPMs can be used to enable holistic production control strategies that take interactions of process parameters of multiple unit operations into account. Moreover, IPMs can be trained with development data, refined with qualification runs, and maintained with routine manufacturing data which underlines the lifecycle concept. These applications will be shown by means of a process characterization study recently conducted at a world-leading contract manufacturing organization (CMO). The new IPM methodology therefore allows anticipation of out of specification (OOS) events, identify critical process parameters, and take risk-based decisions on counteractions that increase process robustness and decrease the likelihood of OOS events.

Validation of computer simulation training for esophagogastroduodenoscopy: Pilot study.

PubMed

Sedlack, Robert E

2007-08-01

Little is known regarding the value of esophagogastroduodenoscopy (EGD) simulators in education. The purpose of the present paper was to validate the use of computer simulation in novice EGD training. In phase 1, expert endoscopists evaluated various aspects of simulation fidelity as compared to live endoscopy. Additionally, computer-recorded performance metrics were assessed by comparing the recorded scores from users of three different experience levels. In phase 2, the transfer of simulation-acquired skills to the clinical setting was assessed in a two-group, randomized pilot study. The setting was a large gastroenterology (GI) Fellowship training program; in phase 1, 21 subjects (seven expert, intermediate and novice endoscopist), made up the three experience groups. In phase 2, eight novice GI fellows were involved in the two-group, randomized portion of the study examining the transfer of simulation skills to the clinical setting. During the initial validation phase, each of the 21 subjects completed two standardized EDG scenarios on a computer simulator and their performance scores were recorded for seven parameters. Following this, staff participants completed a questionnaire evaluating various aspects of the simulator's fidelity. Finally, four novice GI fellows were randomly assigned to receive 6 h of simulator-augmented training (SAT group) in EGD prior to beginning 1 month of patient-based EGD training. The remaining fellows experienced 1 month of patient-based training alone (PBT group). Results of the seven measured performance parameters were compared between three groups of varying experience using a Wilcoxon ranked sum test. The staffs' simulator fidelity survey used a 7-point Likert scale (1, very unrealistic; 4, neutral; 7, very realistic) for each of the parameters examined. During the second phase of this study, supervising staff rated both SAT and PBT fellows' patient-based performance daily. Scoring in each skill was completed using a 7-point Likert scale (1, strongly disagree; 4, neutral; 7, strongly agree). Median scores were compared between groups using the Wilcoxon ranked sum test. Staff evaluations of fidelity found that only two of the parameters examined (anatomy and scope maneuverability) had a significant degree of realism. The remaining areas were felt to be limited in their fidelity. Of the computer-recorded performance scores, only the novice group could be reliably identified from the other two experience groups. In the clinical application phase, the median Patient Discomfort ratings were superior in the PBT group (6; interquartile range [IQR], 5-6) as compared to the SAT group (5; IQR, 4-6; P = 0.015). PBT fellows' ratings were also superior in Sedation, Patient Discomfort, Independence and Competence during various phases of the evaluation. At no point were SAT fellows rated higher than the PBT group in any of the parameters examined. This EGD simulator has limitations to the degree of fidelity and can differentiate only novice endoscopists from other levels of experience. Finally, skills learned during EGD simulation training do not appear to translate well into patient-based endoscopy skills. These findings suggest against a key element of validity for the use of this computer simulator in novice EGD training.

A serious game can be a valid method to train clinical decision-making in surgery.

PubMed

Graafland, Maurits; Vollebergh, Maarten F; Lagarde, Sjoerd M; van Haperen, M; Bemelman, Willem A; Schijven, Marlies P

2014-12-01

A serious game was developed to train surgical residents in clinical decision-making regarding biliary tract disease. Serious or applied gaming is a novel educational approach to postgraduate training, combining training and assessment of clinical decision-making in a fun and challenging way. Although interest for serious games in medicine is rising, evidence on its validity is lacking. This study investigates face, content, and construct validity of this serious game. Experts structurally validated the game's medical content. Subsequently, 41 participants played the game. Decision scores and decision speed were compared among surgeons, surgical residents, interns, and medical students, determining the game's discriminatory ability between different levels of expertise. After playing, participants completed a questionnaire on the game's perceived realism and teaching ability. Surgeons solved more cases correctly (mean 77 %) than surgical residents (67 %), interns (60 %), master-degree students (50 %), and bachelor-degree students (39 % (p < 0.01). Trainees performed significantly better in their second play session than in the first (median 72 vs. 48 %, p = 0.00). Questionnaire results showed that educators and surgical trainees found the game both realistic and useful for surgical training. The majority perceived the game as fun (91.2 %), challenging (85.3 %), and would recommend the game to educate their colleagues (81.8 %). This serious game showed clear discriminatory ability between different levels of expertise in biliary tract disease management and clear teaching capability. It was perceived as appealing and realistic. Serious gaming has the potential to increase adherence to training programs in surgical residency training and medical school.

Cascade Back-Propagation Learning in Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2003-01-01

The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.

The Training Evaluation Inventory (TEI)--Evaluation of Training Design and Measurement of Training Outcomes for Predicting Training Success

ERIC Educational Resources Information Center

Ritzmann, Sandrina; Hagemann, Vera; Kluge, Annette

2014-01-01

Training evaluation in research and organisational contexts is vital to ensure informed decisions regarding the value of training. The present study describes the development of a valid and reliable training evaluation inventory (TEI), as it does not exist so far. The objectives were a) to construct an instrument that is theoretically and…

Improved military air traffic controller selection methods as measured by subsequent training performance.

PubMed

Carretta, Thomas R; King, Raymond E

2008-01-01

Over the past decade, the U.S. military has conducted several studies to evaluate determinants of enlisted air traffic controller (ATC) performance. Research has focused on validation of the Armed Services Vocational Aptitude Battery (ASVAB) and has shown it to be a good predictor of training performance. Despite this, enlisted ATC training and post-training attrition is higher than desirable, prompting interest in alternate selection methods to augment current procedures. The current study examined the utility of the FAA Air Traffic Selection and Training (AT-SAT) battery for incrementing the predictiveness of the ASVAB versus several enlisted ATC training criteria. Subjects were 448 USAF enlisted ATC students who were administered the ASVAB and FAA AT-SAT subtests and subsequently graduated or were eliminated from apprentice-level training. Training criteria were a dichotomous graduation/elimination training score, average ATC fundamentals course score, and FAA certified tower operator test score. Results confirmed the predictive validity of the ASVAB and showed that one of the AT-SAT subtests resembling a low-fidelity ATC work sample significantly improved prediction of training performance beyond the ASVAB alone. Results suggested training attrition could be reduced by raising the current ASVAB minimum qualifying score. However, this approach may make it difficult to identify sufficient numbers of trainees and lead to adverse impact. Although the AT-SAT ATC work sample subtest showed incremental validity to the ASVAB, its length (95 min) may be problematic in operational testing. Recommendations are made for additional studies to address issues affecting operational implementation.

Development of Weeds Density Evaluation System Based on RGB Sensor

NASA Astrophysics Data System (ADS)

Solahudin, M.; Slamet, W.; Wahyu, W.

2018-05-01

Weeds are plant competitors which potentially reduce the yields due to competition for sunlight, water and soil nutrients. Recently, for chemical-based weed control, site-specific weed management that accommodates spatial and temporal diversity of weeds attack in determining the appropriate dose of herbicide based on Variable Rate Technology (VRT) is preferable than traditional approach with single dose herbicide application. In such application, determination of the level of weed density is an important task. Several methods have been studied to evaluate the density of weed attack. The objective of this study is to develop a system that is able to evaluate weed density based on RGB (Red, Green, and Blue) sensors. RGB sensor was used to acquire the RGB values of the surface of the field. An artificial neural network (ANN) model was then used for determining the weed density. In this study the ANN model was trained with 280 training data (70%), 60 validation data (15%), and 60 testing data (15%). Based on the field test, using the proposed method the weed density could be evaluated with an accuracy of 83.75%.

Three-dimensional (3D) printed endovascular simulation models: a feasibility study.

PubMed

Mafeld, Sebastian; Nesbitt, Craig; McCaslin, James; Bagnall, Alan; Davey, Philip; Bose, Pentop; Williams, Rob

2017-02-01

Three-dimensional (3D) printing is a manufacturing process in which an object is created by specialist printers designed to print in additive layers to create a 3D object. Whilst there are initial promising medical applications of 3D printing, a lack of evidence to support its use remains a barrier for larger scale adoption into clinical practice. Endovascular virtual reality (VR) simulation plays an important role in the safe training of future endovascular practitioners, but existing VR models have disadvantages including cost and accessibility which could be addressed with 3D printing. This study sought to evaluate the feasibility of 3D printing an anatomically accurate human aorta for the purposes of endovascular training. A 3D printed model was successfully designed and printed and used for endovascular simulation. The stages of development and practical applications are described. Feedback from 96 physicians who answered a series of questions using a 5 point Likert scale is presented. Initial data supports the value of 3D printed endovascular models although further educational validation is required.

Complete de-Dopplerization and acoustic holography for external noise of a high-speed train.

PubMed

Yang, Diange; Wen, Junjie; Miao, Feng; Wang, Ziteng; Gu, Xiaoan; Lian, Xiaomin

2016-09-01

Identification and measurement of moving sound sources are the bases for vehicle noise control. Acoustic holography has been applied in successfully identifying the moving sound source since the 1990s. However, due to the high demand for the accuracy of holographic data, currently the maximum velocity achieved by acoustic holography is just above 100 km/h. The objective of this study was to establish a method based on the complete Morse acoustic model to restore the measured signal in high-speed situations, and to propose a far-field acoustic holography method applicable for high-speed moving sound sources. Simulated comparisons of the proposed far-field acoustic holography with complete Morse model, the acoustic holography with simplified Morse model and traditional delay-and-sum beamforming were conducted. Experiments with a high-speed train running at the speed of 278 km/h validated the proposed far-field acoustic holography. This study extended the applications of acoustic holography to high-speed situations and established the basis for quantitative measurements of far-field acoustic holography.

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Development and validation of a knowledge test for health professionals regarding lifestyle modification.

PubMed

Talip, Whadi-ah; Steyn, Nelia P; Visser, Marianne; Charlton, Karen E; Temple, Norman

2003-09-01

We wanted to develop and validate a test that assesses the knowledge and practices of health professionals (HPs) with regard to the role of nutrition, physical activity, and smoking cessation (lifestyle modification) in chronic diseases of lifestyle. A descriptive cross-sectional validation study was carried out. The validation design consisted of two phases, namely 1) test planning and development and 2) test evaluation. The study sample consisted of five groups of HPs: dietitians, dietetic interns, general practitioners, medical students, and nurses. The overall response rate was 58%, resulting in a sample size of 186 participants. A test was designed to evaluate the knowledge and practices of HPs. The test was first evaluated by an expert group to ensure content, construct, and face validity. Thereafter, the questionnaire was tested on five groups of HPs to test for criterion validity. Internal consistency was evaluated by Cronbach's alpha. An expert panel ensured content, construct, and face validity of the test. Groups with the most training and exposure to nutrition (dietitians and dietetic interns) had the highest group mean score, ranging from 61% to 88%, whereas those with limited nutrition training (general practitioners, medical students, and nurses) had significantly lower scores, ranging from 26% to 80%. This result demonstrated criterion validity. Internal consistency of the overall test demonstrated a Cronbach's alpha of 0.99. Most HPs identified the mass media as their main source of information on lifestyle modification. These HPs also identified lack of time, lack of patient compliance, and lack of knowledge as barriers that prevent them from providing counseling on lifestyle modification. The results of this study showed that this test instrument identifies groups of health professionals with adequate training (knowledge) in lifestyle modification and those who require further training (knowledge).

Clerkship maturity: does the idea of training clinical skills work?

PubMed

Stosch, Christoph; Joachim, Alexander; Ascher, Johannes

2011-01-01

With the reformed curriculum "4C", the Medical Faculty of the University of Cologne has started to systematically plan practical skills training, for which Clerkship Maturity is the first step. The key guidelines along which the curriculum was development were developed by experts. This approach has now been validated. Both students and teachers were asked to fill in a questionnaire regarding preclinical practical skills training to confirm the concept of Clerkship Maturity. The Cologne training program Clerkship Maturity can be validated empirically overall through the activities of the students awaiting the clerkship framework and through the evaluation by the medical staff providing the training. The subjective ratings of the advantages of the training by the students leave room for improvement. Apart from minor improvements to the program, the most likely solution providing sustainable results will involve an over-regional strategy for establishing skills training planned as part of the curriculum.

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools.

PubMed

McManus, I C; Dewberry, Chris; Nicholson, Sandra; Dowell, Jonathan S

2013-11-14

Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools

PubMed Central

2013-01-01

Background Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. Methods A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. Results UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. Conclusions This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general. PMID:24229380

Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation.

PubMed

van Stiphout, Ruud G P M; Valentini, Vincenzo; Buijsen, Jeroen; Lammering, Guido; Meldolesi, Elisa; van Soest, Johan; Leccisotti, Lucia; Giordano, Alessandro; Gambacorta, Maria A; Dekker, Andre; Lambin, Philippe

2014-11-01

To develop and externally validate a predictive model for pathologic complete response (pCR) for locally advanced rectal cancer (LARC) based on clinical features and early sequential (18)F-FDG PETCT imaging. Prospective data (i.a. THUNDER trial) were used to train (N=112, MAASTRO Clinic) and validate (N=78, Università Cattolica del S. Cuore) the model for pCR (ypT0N0). All patients received long-course chemoradiotherapy (CRT) and surgery. Clinical parameters were age, gender, clinical tumour (cT) stage and clinical nodal (cN) stage. PET parameters were SUVmax, SUVmean, metabolic tumour volume (MTV) and maximal tumour diameter, for which response indices between pre-treatment and intermediate scan were calculated. Using multivariate logistic regression, three probability groups for pCR were defined. The pCR rates were 21.4% (training) and 23.1% (validation). The selected predictive features for pCR were cT-stage, cN-stage, response index of SUVmean and maximal tumour diameter during treatment. The models' performances (AUC) were 0.78 (training) and 0.70 (validation). The high probability group for pCR resulted in 100% correct predictions for training and 67% for validation. The model is available on the website www.predictcancer.org. The developed predictive model for pCR is accurate and externally validated. This model may assist in treatment decisions during CRT to select complete responders for a wait-and-see policy, good responders for extra RT boost and bad responders for additional chemotherapy. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Crew station research and development facility training for the light helicopter demonstration/validation program

NASA Technical Reports Server (NTRS)

Matsumoto, Joy Hamerman; Rogers, Steven; Mccauley, Michael; Salinas, AL

1992-01-01

The U.S. Army Crew Station Research and Development Branch (CSRDB) of the Aircraft Simulation Division (AVSCOM) was tasked by the Light Helicopter Program Manager (LH-PM) to provide training to Army personnel in advanced aircraft simulation technology. The purpose of this training was to prepare different groups of pilots to support and evaluate two contractor simulation efforts during the Demonstration/Validation (DEM/VAL) phase of the LH program. The personnel in the CSRDB developed mission oriented training programs to accomplish the objectives, conduct the programs, and provide guidance to army personnel and support personnel throughout the DEM/VAL phase.

Predicting intention to attend and actual attendance at a universal parent-training programme: a comparison of social cognition models.

PubMed

Thornton, Sarah; Calam, Rachel

2011-07-01

The predictive validity of the Health Belief Model (HBM) and the Theory of Planned Behaviour (TPB) were examined in relation to 'intention to attend' and 'actual attendance' at a universal parent-training intervention for parents of children with behavioural difficulties. A validation and reliability study was conducted to develop two questionnaires (N = 108 parents of children aged 4-7).These questionnaires were then used to investigate the predictive validity of the two models in relation to 'intention to attend' and 'actual attendance' at a parent-training intervention ( N = 53 parents of children aged 4-7). Both models significantly predicted 'intention to attend a parent-training group'; however, the TPB accounted for more variance in the outcome variable compared to the HBM. Preliminary investigations highlighted that attendees were more likely to intend to attend the groups, have positive attitudes towards the groups, perceive important others as having positive attitudes towards the groups, and report elevated child problem behaviour scores. These findings provide useful information regarding the belief-based factors that affect attendance at universal parent-training groups. Possible interventions aimed at increasing 'intention to attend' and 'actual attendance' at parent-training groups are discussed.

Reverse lactate threshold: a novel single-session approach to reliable high-resolution estimation of the anaerobic threshold.

PubMed

Dotan, Raffy

2012-06-01

The multisession maximal lactate steady-state (MLSS) test is the gold standard for anaerobic threshold (AnT) estimation. However, it is highly impractical, requires high fitness level, and suffers additional shortcomings. Existing single-session AnT-estimating tests are of compromised validity, reliability, and resolution. The presented reverse lactate threshold test (RLT) is a single-session, AnT-estimating test, aimed at avoiding the pitfalls of existing tests. It is based on the novel concept of identifying blood lactate's maximal appearance-disappearance equilibrium by approaching the AnT from higher, rather than from lower exercise intensities. Rowing, cycling, and running case data (4 recreational and competitive athletes, male and female, aged 17-39 y) are presented. Subjects performed the RLT test and, on a separate session, a single 30-min MLSS-type verification test at the RLT-determined intensity. The RLT and its MLSS verification exhibited exceptional agreement at 0.5% discrepancy or better. The RLT's training sensitivity was demonstrated by a case of 2.5-mo training regimen following which the RLT's 15-W improvement was fully MLSS-verified. The RLT's test-retest reliability was examined in 10 trained and untrained subjects. Test 2 differed from test 1 by only 0.3% with an intraclass correlation of 0.997. The data suggest RLT to accurately and reliably estimate AnT (as represented by MLSS verification) with high resolution and in distinctly different sports and to be sensitive to training adaptations. Compared with MLSS, the single-session RLT is highly practical and its lower fitness requirements make it applicable to athletes and untrained individuals alike. Further research is needed to establish RLT's validity and accuracy in larger samples.

A Matlab Program for Textural Classification Using Neural Networks

NASA Astrophysics Data System (ADS)

Leite, E. P.; de Souza, C.

2008-12-01

A new MATLAB code that provides tools to perform classification of textural images for applications in the Geosciences is presented. The program, here coined TEXTNN, comprises the computation of variogram maps in the frequency domain for specific lag distances in the neighborhood of a pixel. The result is then converted back to spatial domain, where directional or ominidirectional semivariograms are extracted. Feature vectors are built with textural information composed of the semivariance values at these lag distances and, moreover, with histogram measures of mean, standard deviation and weighted fill-ratio. This procedure is applied to a selected group of pixels or to all pixels in an image using a moving window. A feed- forward back-propagation Neural Network can then be designed and trained on feature vectors of predefined classes (training set). The training phase minimizes the mean-squared error on the training set. Additionally, at each iteration, the mean-squared error for every validation is assessed and a test set is evaluated. The program also calculates contingency matrices, global accuracy and kappa coefficient for the three data sets, allowing a quantitative appraisal of the predictive power of the Neural Network models. The interpreter is able to select the best model obtained from a k-fold cross-validation or to use a unique split-sample data set for classification of all pixels in a given textural image. The code is opened to the geoscientific community and is very flexible, allowing the experienced user to modify it as necessary. The performance of the algorithms and the end-user program were tested using synthetic images, orbital SAR (RADARSAT) imagery for oil seepage detection, and airborne, multi-polarimetric SAR imagery for geologic mapping. The overall results proved very promising.

Training and Assessment of Hysteroscopic Skills: A Systematic Review.

PubMed

Savran, Mona Meral; Sørensen, Stine Maya Dreier; Konge, Lars; Tolsgaard, Martin G; Bjerrum, Flemming

2016-01-01

The aim of this systematic review was to identify studies on hysteroscopic training and assessment. PubMed, Excerpta Medica, the Cochrane Library, and Web of Science were searched in January 2015. Manual screening of references and citation tracking were also performed. Studies on hysteroscopic educational interventions were selected without restrictions on study design, populations, language, or publication year. A qualitative data synthesis including the setting, study participants, training model, training characteristics, hysteroscopic skills, assessment parameters, and study outcomes was performed by 2 authors working independently. Effect sizes were calculated when possible. Overall, 2 raters independently evaluated sources of validity evidence supporting the outcomes of the hysteroscopy assessment tools. A total of 25 studies on hysteroscopy training were identified, of which 23 were performed in simulated settings. Overall, 10 studies used virtual-reality simulators and reported effect sizes for technical skills ranging from 0.31 to 2.65; 12 used inanimate models and reported effect sizes for technical skills ranging from 0.35 to 3.19. One study involved live animal models; 2 studies were performed in clinical settings. The validity evidence supporting the assessment tools used was low. Consensus between the 2 raters on the reported validity evidence was high (94%). This systematic review demonstrated large variations in the effect of different tools for hysteroscopy training. The validity evidence supporting the assessment of hysteroscopic skills was limited. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Face and construct validity of a computer-based virtual reality simulator for ERCP.

PubMed

Bittner, James G; Mellinger, John D; Imam, Toufic; Schade, Robert R; Macfadyen, Bruce V

2010-02-01

Currently, little evidence supports computer-based simulation for ERCP training. To determine face and construct validity of a computer-based simulator for ERCP and assess its perceived utility as a training tool. Novice and expert endoscopists completed 2 simulated ERCP cases by using the GI Mentor II. Virtual Education and Surgical Simulation Laboratory, Medical College of Georgia. Outcomes included times to complete the procedure, reach the papilla, and use fluoroscopy; attempts to cannulate the papilla, pancreatic duct, and common bile duct; and number of contrast injections and complications. Subjects assessed simulator graphics, procedural accuracy, difficulty, haptics, overall realism, and training potential. Only when performance data from cases A and B were combined did the GI Mentor II differentiate novices and experts based on times to complete the procedure, reach the papilla, and use fluoroscopy. Across skill levels, overall opinions were similar regarding graphics (moderately realistic), accuracy (similar to clinical ERCP), difficulty (similar to clinical ERCP), overall realism (moderately realistic), and haptics. Most participants (92%) claimed that the simulator has definite training potential or should be required for training. Small sample size, single institution. The GI Mentor II demonstrated construct validity for ERCP based on select metrics. Most subjects thought that the simulated graphics, procedural accuracy, and overall realism exhibit face validity. Subjects deemed it a useful training tool. Study repetition involving more participants and cases may help confirm results and establish the simulator's ability to differentiate skill levels based on ERCP-specific metrics.

Brain Training in Children and Adolescents: Is It Scientifically Valid?

PubMed

Rossignoli-Palomeque, Teresa; Perez-Hernandez, Elena; González-Marqués, Javier

2018-01-01

Background: Brain training products are becoming increasingly popular for children and adolescents. Despite the marketing aimed at their use in the general population, these products may provide more benefits for specific neurologically impaired populations. A review of Brain Training (BT) products analyzing their efficacy while considering the methodological limitations of supporting research is required for practical applications. Method: searches were made of the PubMed database (until March 2017) for studies including: (1) empirical data on the use of brain training for children or adolescents and any effects on near transfer (NT) and/or far transfer (FT) and/or neuroplasticity, (2) use of brain training for cognitive training purposes, (3) commercially available training applications, (4) computer-based programs for children developed since the 1990s, and (5) relevant printed and peer-reviewed material. Results: Database searches yielded a total of 16,402 references, of which 70 met the inclusion criteria for the review. We classified programs in terms of neuroplasticity, near and far transfer, and long-term effects and their applied methodology. Regarding efficacy, only 10 studies (14.2%) have been found that support neuroplasticity, and the majority of brain training platforms claimed to be based on such concepts without providing any supporting scientific data. Thirty-six studies (51.4%) have shown far transfer (7 of them are non-independent) and only 11 (15.7%) maintained far transfer at follow-up. Considering the methodology, 40 studies (68.2%) were not randomized and controlled; for those randomized, only 9 studies (12.9%) were double-blind, and only 13 studies (18.6%) included active controls in their trials. Conclusion: Overall, few independent studies have found far transfer and long-term effects. The majority of independent results found only near transfer. There is a lack of double-blind randomized trials which include an active control group as well as a passive control to properly control for contaminant variables. Based on our results, Brain Training Programs as commercially available products are not as effective as first expected or as they promise in their advertisements.

Brain Training in Children and Adolescents: Is It Scientifically Valid?

PubMed Central

Rossignoli-Palomeque, Teresa; Perez-Hernandez, Elena; González-Marqués, Javier

2018-01-01

Background: Brain training products are becoming increasingly popular for children and adolescents. Despite the marketing aimed at their use in the general population, these products may provide more benefits for specific neurologically impaired populations. A review of Brain Training (BT) products analyzing their efficacy while considering the methodological limitations of supporting research is required for practical applications. Method: searches were made of the PubMed database (until March 2017) for studies including: (1) empirical data on the use of brain training for children or adolescents and any effects on near transfer (NT) and/or far transfer (FT) and/or neuroplasticity, (2) use of brain training for cognitive training purposes, (3) commercially available training applications, (4) computer-based programs for children developed since the 1990s, and (5) relevant printed and peer-reviewed material. Results: Database searches yielded a total of 16,402 references, of which 70 met the inclusion criteria for the review. We classified programs in terms of neuroplasticity, near and far transfer, and long-term effects and their applied methodology. Regarding efficacy, only 10 studies (14.2%) have been found that support neuroplasticity, and the majority of brain training platforms claimed to be based on such concepts without providing any supporting scientific data. Thirty-six studies (51.4%) have shown far transfer (7 of them are non-independent) and only 11 (15.7%) maintained far transfer at follow-up. Considering the methodology, 40 studies (68.2%) were not randomized and controlled; for those randomized, only 9 studies (12.9%) were double-blind, and only 13 studies (18.6%) included active controls in their trials. Conclusion: Overall, few independent studies have found far transfer and long-term effects. The majority of independent results found only near transfer. There is a lack of double-blind randomized trials which include an active control group as well as a passive control to properly control for contaminant variables. Based on our results, Brain Training Programs as commercially available products are not as effective as first expected or as they promise in their advertisements. PMID:29780336

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty.

PubMed

Ren, Anna N; Neher, Robert E; Bell, Tyler; Grimm, James

2018-06-01

Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable. Copyright © 2018 Elsevier Inc. All rights reserved.

Basic psychometric properties of the transfer assessment instrument (version 3.0).

PubMed

Tsai, Chung-Ying; Rice, Laura A; Hoelmer, Claire; Boninger, Michael L; Koontz, Alicia M

2013-12-01

To refine the Transfer Assessment Instrument (TAI 2.0), develop a training program for the TAI, and analyze the basic psychometric properties of the TAI 3.0, including reliability, standard error of measurement (SEM), minimal detectable change (MDC), and construct validity. Repeated measures. A winter sports clinic for disabled veterans. Wheelchair users (N=41) who perform sitting-pivot or standing-pivot transfers. Not applicable. TAI version 3.0, intraclass correlation coefficients, SEMs, and MDCs for reliable measurement of raters' responses. Spearman correlation coefficient, 1-way analysis of variance, and independent t tests to evaluate construct validity. TAI 3.0 had acceptable to high levels of reliability (range, .74-.88). The SEMs for part 1, part 2, and final scores ranged from .45 to .75. The MDC was 1.5 points on the 10-point scale for the final score. There were weak correlations (ρ range, -.13 to .25; P>.11) between TAI final scores and subjects' characteristics (eg, sex, body mass index, age, type of disability, length of wheelchair use, grip and elbow strength, sitting balance). With comprehensive training, the refined TAI 3.0 yields high reliability among raters of different clinical backgrounds and experience. TAI 3.0 was unbiased toward certain physical characteristics that may influence transfer. TAI fills a void in the field by providing a quantitative measurement of transfers and a tool that can be used to detect problems and guide transfer training. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Validation of a Novel Laparoscopic Adjustable Gastric Band Simulator

PubMed Central

Sankaranarayanan, Ganesh; Adair, James D.; Halic, Tansel; Gromski, Mark A.; Lu, Zhonghua; Ahn, Woojin; Jones, Daniel B.; De, Suvranu

2011-01-01

Background Morbid obesity accounts for more than 90,000 deaths per year in the United States. Laparoscopic adjustable gastric banding (LAGB) is the second most common weight loss procedure performed in the US and the most common in Europe and Australia. Simulation in surgical training is a rapidly advancing field that has been adopted by many to prepare surgeons for surgical techniques and procedures. Study Aim The aim of our study was to determine face, construct and content validity for a novel virtual reality laparoscopic adjustable gastric band simulator. Methods Twenty-eight subjects were categorized into two groups (Expert and Novice), determined by their skill level in laparoscopic surgery. Experts consisted of subjects who had at least four years of laparoscopic training and operative experience. Novices consisted of subjects with medical training, but with less than four years of laparoscopic training. The subjects performed the virtual reality laparoscopic adjustable band surgery simulator. They were automatically scored, according to various tasks. The subjects then completed a questionnaire to evaluate face and content validity. Results On a 5-point Likert scale (1 – lowest score, 5 – highest score), the mean score for visual realism was 4.00 ± 0.67 and the mean score for realism of the interface and tool movements was 4.07 ± 0.77 [Face Validity]. There were significant differences in the performance of the two subject groups (Expert and Novice), based on total scores (p<0.001) [Construct Validity]. Mean scores for utility of the simulator, as addressed by the Expert group, was 4.50 ± 0.71 [Content Validity]. Conclusion We created a virtual reality laparoscopic adjustable gastric band simulator. Our initial results demonstrate excellent face, construct and content validity findings. To our knowledge, this is the first virtual reality simulator with haptic feedback for training residents and surgeons in the laparoscopic adjustable gastric banding procedure. PMID:20734069

Validation of a novel laparoscopic adjustable gastric band simulator.

PubMed

Sankaranarayanan, Ganesh; Adair, James D; Halic, Tansel; Gromski, Mark A; Lu, Zhonghua; Ahn, Woojin; Jones, Daniel B; De, Suvranu

2011-04-01

Morbid obesity accounts for more than 90,000 deaths per year in the United States. Laparoscopic adjustable gastric banding (LAGB) is the second most common weight loss procedure performed in the US and the most common in Europe and Australia. Simulation in surgical training is a rapidly advancing field that has been adopted by many to prepare surgeons for surgical techniques and procedures. The aim of our study was to determine face, construct, and content validity for a novel virtual reality laparoscopic adjustable gastric band simulator. Twenty-eight subjects were categorized into two groups (expert and novice), determined by their skill level in laparoscopic surgery. Experts consisted of subjects who had at least 4 years of laparoscopic training and operative experience. Novices consisted of subjects with medical training but with less than 4 years of laparoscopic training. The subjects used the virtual reality laparoscopic adjustable band surgery simulator. They were automatically scored according to various tasks. The subjects then completed a questionnaire to evaluate face and content validity. On a 5-point Likert scale (1 = lowest score, 5 = highest score), the mean score for visual realism was 4.00 ± 0.67 and the mean score for realism of the interface and tool movements was 4.07 ± 0.77 (face validity). There were significant differences in the performances of the two subject groups (expert and novice) based on total scores (p < 0.001) (construct validity). Mean score for utility of the simulator, as addressed by the expert group, was 4.50 ± 0.71 (content validity). We created a virtual reality laparoscopic adjustable gastric band simulator. Our initial results demonstrate excellent face, construct, and content validity findings. To our knowledge, this is the first virtual reality simulator with haptic feedback for training residents and surgeons in the laparoscopic adjustable gastric banding procedure.

Development and validation of an artificial wetlab training system for the lumbar discectomy.

PubMed

Adermann, Jens; Geissler, Norman; Bernal, Luis E; Kotzsch, Susanne; Korb, Werner

2014-09-01

An initial research indicated that realistic haptic simulators with an adapted training concept are needed to enhance the training for spinal surgery. A cognitive task analysis (CTA) was performed to define a realistic and helpful scenario-based simulation. Based on the results a simulator for lumbar discectomy was developed. Additionally, a realistic training operating room was built for a pilot. The results were validated. The CTA showed a need for realistic scenario-based training in spine surgery. The developed simulator consists of synthetic bone structures, synthetic soft tissue and an advanced bleeding system. Due to the close interdisciplinary cooperation of surgeons between engineers and psychologists, the iterative multicentre validation showed that the simulator is visually and haptically realistic. The simulator offers integrated sensors for the evaluation of the traction being used and the compression during surgery. The participating surgeons in the pilot workshop rated the simulator and the training concept as very useful for the improvement of their surgical skills. In the context of the present work a precise definition for the simulator and training concept was developed. The additional implementation of sensors allows the objective evaluation of the surgical training by the trainer. Compared to other training simulators and concepts, the high degree of objectivity strengthens the acceptance of the feedback. The measured data of the nerve root tension and the compression of the dura can be used for intraoperative control and a detailed postoperative evaluation.

Predicting hydrofacies and hydraulic conductivity from direct-push data using a data-driven relevance vector machine approach: Motivations, algorithms, and application

NASA Astrophysics Data System (ADS)

Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso

2015-01-01

The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.

Spectral signature verification using statistical analysis and text mining

NASA Astrophysics Data System (ADS)

DeCoster, Mallory E.; Firpi, Alexe H.; Jacobs, Samantha K.; Cone, Shelli R.; Tzeng, Nigel H.; Rodriguez, Benjamin M.

2016-05-01

In the spectral science community, numerous spectral signatures are stored in databases representative of many sample materials collected from a variety of spectrometers and spectroscopists. Due to the variety and variability of the spectra that comprise many spectral databases, it is necessary to establish a metric for validating the quality of spectral signatures. This has been an area of great discussion and debate in the spectral science community. This paper discusses a method that independently validates two different aspects of a spectral signature to arrive at a final qualitative assessment; the textual meta-data and numerical spectral data. Results associated with the spectral data stored in the Signature Database1 (SigDB) are proposed. The numerical data comprising a sample material's spectrum is validated based on statistical properties derived from an ideal population set. The quality of the test spectrum is ranked based on a spectral angle mapper (SAM) comparison to the mean spectrum derived from the population set. Additionally, the contextual data of a test spectrum is qualitatively analyzed using lexical analysis text mining. This technique analyzes to understand the syntax of the meta-data to provide local learning patterns and trends within the spectral data, indicative of the test spectrum's quality. Text mining applications have successfully been implemented for security2 (text encryption/decryption), biomedical3 , and marketing4 applications. The text mining lexical analysis algorithm is trained on the meta-data patterns of a subset of high and low quality spectra, in order to have a model to apply to the entire SigDB data set. The statistical and textual methods combine to assess the quality of a test spectrum existing in a database without the need of an expert user. This method has been compared to other validation methods accepted by the spectral science community, and has provided promising results when a baseline spectral signature is present for comparison. The spectral validation method proposed is described from a practical application and analytical perspective.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

PubMed Central

Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister

2017-01-01

Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications. PMID:28787438

The Use of IMMUs in a Water Environment: Instrument Validation and Application of 3D Multi-Body Kinematic Analysis in Medicine and Sport

PubMed Central

Mangia, Anna Lisa; Cortesi, Matteo; Fantozzi, Silvia; Giovanardi, Andrea; Borra, Davide; Gatta, Giorgio

2017-01-01

The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic field in the swimming pool and to identify the best volume for experimental test acquisition with a mean dynamic orientation error lower than 5°. Successively, the gait and the swimming analyses were explored in terms of spatiotemporal and joint kinematics variables. The extraction of only spatiotemporal parameters highlighted several critical issues and the joint kinematic information has shown to be an added value for both rehabilitative and sport training purposes. Furthermore, 3D joint kinematics applied using the IMMUs provided similar quantitative information than that of more expensive and bulky systems but with a simpler and faster setup preparation, a lower time consuming processing phase, as well as the possibility to record and analyze a higher number of strides/strokes without limitations imposed by the cameras. PMID:28441739

The Use of IMMUs in a Water Environment: Instrument Validation and Application of 3D Multi-Body Kinematic Analysis in Medicine and Sport.

PubMed

Mangia, Anna Lisa; Cortesi, Matteo; Fantozzi, Silvia; Giovanardi, Andrea; Borra, Davide; Gatta, Giorgio

2017-04-22

The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic field in the swimming pool and to identify the best volume for experimental test acquisition with a mean dynamic orientation error lower than 5°. Successively, the gait and the swimming analyses were explored in terms of spatiotemporal and joint kinematics variables. The extraction of only spatiotemporal parameters highlighted several critical issues and the joint kinematic information has shown to be an added value for both rehabilitative and sport training purposes. Furthermore, 3D joint kinematics applied using the IMMUs provided similar quantitative information than that of more expensive and bulky systems but with a simpler and faster setup preparation, a lower time consuming processing phase, as well as the possibility to record and analyze a higher number of strides/strokes without limitations imposed by the cameras.

Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing

PubMed Central

Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant

2016-01-01

Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876

Text Classification for Organizational Researchers

PubMed Central

Kobayashi, Vladimer B.; Mol, Stefan T.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable. Techniques from text mining facilitate the automatic assignment of text strings to categories, making classification expedient, fast, and reliable, which creates potential for its application in organizational research. The purpose of this article is to familiarize organizational researchers with text mining techniques from machine learning and statistics. We describe the text classification process in several roughly sequential steps, namely training data preparation, preprocessing, transformation, application of classification techniques, and validation, and provide concrete recommendations at each step. To help researchers develop their own text classifiers, the R code associated with each step is presented in a tutorial. The tutorial draws from our own work on job vacancy mining. We end the article by discussing how researchers can validate a text classification model and the associated output. PMID:29881249

Face, Content, and Construct Validations of Endoscopic Needle Injection Simulator for Transurethral Bulking Agent in Treatment of Stress Urinary Incontinence.

PubMed

Farhan, Bilal; Soltani, Tandis; Do, Rebecca; Perez, Claudia; Choi, Hanul; Ghoniem, Gamal

2018-05-02

Endoscopic injection of urethral bulking agents is an office procedure that is used to treat stress urinary incontinence secondary to internal sphincteric deficiency. Validation studies important part of simulator evaluation and is considered important step to establish the effectiveness of simulation-based training. The endoscopic needle injection (ENI) simulator has not been formally validated, although it has been used widely at University of California, Irvine. We aimed to assess the face, content, and construct validity of the UC, Irvine ENI simulator. Dissected female porcine bladders were mounted in a modified Hysteroscopy Diagnostic Trainer. Using routine endoscopic equipment for this procedure with video monitoring, 6 urologists (experts group) and 6 urology trainee (novice group) completed urethral bulking agents injections on a total of 12 bladders using ENI simulator. Face and content validities were assessed by using structured quantitative survey which rating the realism. Construct validity was assessed by comparing the performance, time of the procedure, and the occlusive (anatomical and functional) evaluations between the experts and novices. Trainees also completed a postprocedure feedback survey. Effective injections were evaluated by measuring the retrograde urethral opening pressure, visual cystoscopic coaptation, and postprocedure gross anatomic examination. All 12 participants felt the simulator was a good training tool and should be used as essential part of urology training (face validity). ENI simulator showed good face and content validity with average score varies between the experts and the novices was 3.9/5 and 3.8/5, respectively. Content validity evaluation showed that most aspects of the simulator were adequately realistic (mean Likert scores 3.9-3.8/5). However, the bladder does not bleed, and sometimes thin. Experts significantly outperformed novices (p < 001) across all measure of performance therefore establishing construct validity. The ENI simulator shows face, content and construct validities, although few aspects of simulator were not very realistic (e.g., bleeding).This study provides a base for the future formal validation for this simulator and for continuing use of this simulator in endourology training. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Face and content validity of Xperience™ Team Trainer: bed-side assistant training simulator for robotic surgery.

PubMed

Sessa, Luca; Perrenot, Cyril; Xu, Song; Hubert, Jacques; Bresler, Laurent; Brunaud, Laurent; Perez, Manuela

2018-03-01

In robotic surgery, the coordination between the console-side surgeon and bed-side assistant is crucial, more than in standard surgery or laparoscopy where the surgical team works in close contact. Xperience™ Team Trainer (XTT) is a new optional component for the dv-Trainer ® platform and simulates the patient-side working environment. We present preliminary results for face, content, and the workload imposed regarding the use of the XTT virtual reality platform for the psychomotor and communication skills training of the bed-side assistant in robot-assisted surgery. Participants were categorized into "Beginners" and "Experts". They tested a series of exercises (Pick & Place Laparoscopic Demo, Pick & Place 2 and Team Match Board 1) and completed face validity questionnaires. "Experts" assessed content validity on another questionnaire. All the participants completed a NASA Task Load Index questionnaire to assess the workload imposed by XTT. Twenty-one consenting participants were included (12 "Beginners" and 9 "Experts"). XTT was shown to possess face and content validity, as evidenced by the rankings given on the simulator's ease of use and realism parameters and on the simulator's usefulness for training. Eight out of nine "Experts" judged the visualization of metrics after the exercises useful. However, face validity has shown some weaknesses regarding interactions and instruments. Reasonable workload parameters were registered. XTT demonstrated excellent face and content validity with acceptable workload parameters. XTT could become a useful tool for robotic surgery team training.

Ventilation tube insertion simulation: a literature review and validity assessment of five training models.

PubMed

Mahalingam, S; Awad, Z; Tolley, N S; Khemani, S

2016-08-01

The objective of this study was to identify and investigate the face and content validity of ventilation tube insertion (VTI) training models described in the literature. A review of literature was carried out to identify articles describing VTI simulators. Feasible models were replicated and assessed by a group of experts. Postgraduate simulation centre. Experts were defined as surgeons who had performed at least 100 VTI on patients. Seventeen experts were participated ensuring sufficient statistical power for analysis. A standardised 18-item Likert-scale questionnaire was used. This addressed face validity (realism), global and task-specific content (suitability of the model for teaching) and curriculum recommendation. The search revealed eleven models, of which only five had associated validity data. Five models were found to be feasible to replicate. None of the tested models achieved face or global content validity. Only one model achieved task-specific validity, and hence, there was no agreement on curriculum recommendation. The quality of simulation models is moderate and there is room for improvement. There is a need for new models to be developed or existing ones to be refined in order to construct a more realistic training platform for VTI simulation. © 2015 John Wiley & Sons Ltd.

Face, content, and construct validity of four, inanimate training exercises using the da Vinci ® Si surgical system configured with Single-Site ™ instrumentation.

PubMed

Jarc, Anthony M; Curet, Myriam

2015-08-01

Validated training exercises are essential tools for surgeons as they develop technical skills to use robot-assisted minimally invasive surgical systems. The purpose of this study was to show face, content, and construct validity of four, inanimate training exercises using the da Vinci (®) Si surgical system configured with Single-Site (™) instrumentation. New (N = 21) and experienced (N = 6) surgeons participated in the study. New surgeons (11 Gynecology [GYN] and 10 General Surgery [GEN]) had not completed any da Vinci Single-Site cases but may have completed multiport cases using the da Vinci system. They participated in this study prior to attending a certification course focused on da Vinci Single-Site instrumentation. Experienced surgeons (5 GYN and 1 GEN) had completed at least 25 da Vinci Single-Site cases. The surgeons completed four inanimate training exercises and then rated them with a questionnaire. Raw metrics and overall normalized scores were computed using both video recordings and kinematic data collected from the surgical system. The experienced surgeons significantly outperformed new surgeons for many raw metrics and the overall normalized scores derived from video review (p < 0.05). Only one exercise did not achieve a significant difference between new and experienced surgeons (p = 0.08) when calculating an overall normalized score using both video and advanced metrics derived from kinematic data. Both new and experienced surgeons rated the training exercises as appearing, to train and measure technical skills used during da Vinci Single-Site surgery and actually testing the technical skills used during da Vinci Single-Site surgery. In summary, the four training exercises showed face, content, and construct validity. Improved overall scores could be developed using additional metrics not included in this study. The results suggest that the training exercises could be used in an overall training curriculum aimed at developing proficiency in technical skills for surgeons new to da Vinci Single-Site instrumentation.

Classification of postural profiles among mouth-breathing children by learning vector quantization.

PubMed

Mancini, F; Sousa, F S; Hummel, A D; Falcão, A E J; Yi, L C; Ortolani, C F; Sigulem, D; Pisa, I T

2011-01-01

Mouth breathing is a chronic syndrome that may bring about postural changes. Finding characteristic patterns of changes occurring in the complex musculoskeletal system of mouth-breathing children has been a challenge. Learning vector quantization (LVQ) is an artificial neural network model that can be applied for this purpose. The aim of the present study was to apply LVQ to determine the characteristic postural profiles shown by mouth-breathing children, in order to further understand abnormal posture among mouth breathers. Postural training data on 52 children (30 mouth breathers and 22 nose breathers) and postural validation data on 32 children (22 mouth breathers and 10 nose breathers) were used. The performance of LVQ and other classification models was compared in relation to self-organizing maps, back-propagation applied to multilayer perceptrons, Bayesian networks, naive Bayes, J48 decision trees, k, and k-nearest-neighbor classifiers. Classifier accuracy was assessed by means of leave-one-out cross-validation, area under ROC curve (AUC), and inter-rater agreement (Kappa statistics). By using the LVQ model, five postural profiles for mouth-breathing children could be determined. LVQ showed satisfactory results for mouth-breathing and nose-breathing classification: sensitivity and specificity rates of 0.90 and 0.95, respectively, when using the training dataset, and 0.95 and 0.90, respectively, when using the validation dataset. The five postural profiles for mouth-breathing children suggested by LVQ were incorporated into application software for classifying the severity of mouth breathers' abnormal posture.

Validity and reliability of the session-RPE method for quantifying training load in karate athletes.

PubMed

Tabben, M; Tourny, C; Haddad, M; Chaabane, H; Chamari, K; Coquart, J B

2015-04-24

To test the construct validity and reliability of the session rating of perceived exertion (sRPE) method by examining the relationship between RPE and physiological parameters (heart rate: HR and blood lactate concentration: [La --] ) and the correlations between sRPE and two HR--based methods for quantifying internal training load (Banister's method and Edwards's method) during karate training camp. Eighteen elite karate athletes: ten men (age: 24.2 ± 2.3 y, body mass: 71.2 ± 9.0 kg, body fat: 8.2 ± 1.3% and height: 178 ± 7 cm) and eight women (age: 22.6 ± 1.2 y, body mass: 59.8 ± 8.4 kg, body fat: 20.2 ± 4.4%, height: 169 ± 4 cm) were included in the study. During training camp, subjects participated in eight karate--training sessions including three training modes (4 tactical--technical, 2 technical--development, and 2 randori training), during which RPE, HR, and [La -- ] were recorded. Significant correlations were found between RPE and physiological parameters (percentage of maximal HR: r = 0.75, 95% CI = 0.64--0.86; [La --] : r = 0.62, 95% CI = 0.49--0.75; P < 0.001). Moreover, individual sRPE was significantly correlated with two HR--based methods for quantifying internal training load ( r = 0.65--0.95; P < 0.001). The sRPE method showed the high reliability of the same intensity across training sessions (Cronbach's α = 0.81, 95% CI = 0.61--0.92). This study demonstrates that the sRPE method is valid for quantifying internal training load and intensity in karate.

The internal validity of arthroscopic simulators and their effectiveness in arthroscopic education.

PubMed

Slade Shantz, Jesse Alan; Leiter, Jeff R S; Gottschalk, Tania; MacDonald, Peter Benjamin

2014-01-01

The purpose of this systematic review was to identify standard procedures for the validation of arthroscopic simulators and determine whether simulators improve the surgical skills of users. Arthroscopic simulator validation studies and randomized trials assessing the effectiveness of arthroscopic simulators in education were identified from online databases, as well as, grey literature and reference lists. Only validation studies and randomized trials were included for review. Study heterogeneity was calculated and where appropriate, study results were combined employing a random effects model. Four hundred and thirteen studies were reviewed. Thirteen studies met the inclusion criteria assessing the construct validity of simulators. A pooled analysis of internal validation studies determined that simulators could discriminate between novice and experts, but not between novice and intermediate trainees on time of completion of a simulated task. Only one study assessed the utility of a knee simulator in training arthroscopic skills directly and demonstrated that the skill level of simulator-trained residents was greater than non-simulator-trained residents. Excessive heterogeneity exists in the literature to determine the internal and transfer validity of arthroscopic simulators currently available. Evidence suggests that simulators can discriminate between novice and expert users, but discrimination between novice and intermediate trainees in surgical education should be paramount. International standards for the assessment of arthroscopic simulator validity should be developed to increase the use and effectiveness of simulators in orthopedic surgery.

Twenty cultural and learning principles to guide the development of pharmacy curriculum in Pacific Island countries.

PubMed

Brown, Andrew N; McCormack, Coralie

2014-01-01

A lack of education capacity to support the development of medical supply management competency is a major issue affecting Pacific Islands countries (PICs). Limited human resources and underdeveloped medicines supply management competency are two significant impediments to reaching the health-related Millennium Development Goals in many countries in this rural and remote region. Two recent review publications have provided relevant background documenting factors affecting learning and teaching. These articles have presented available information regarding competency and training requirements for health personnel involved in essential medicine supply management in the region. This background research has provided a platform from which tangible principles can be developed to aid educators and professionals in PICs in the development and delivery of appropriate pharmacy curriculum. Specifically the aim of the present article is to identify culturally meaningful learning and teaching principles to guide the development and delivery of pharmaceutical curriculum in PICs. Subsequently, this information will be applied to develop and trial new pedagogical approaches to the training of health personnel involved in essential medicines supply management, to improve medicine availability for patients in their own environment. This article forms part of a wider research project involving the United Nations Population Fund Suva subregional office, the University of Canberra, Ministry of Health officials and health personnel within identified PICs. Two previous reviews, investigating Pacific culture, learning approaches, and training requirements affecting pharmaceutical personnel, were synthesised into a set of principles that could be applied to the development of pharmaceutical curriculum. These principles were validated through focus groups of health personnel using action research methods. An initial set of 16 principles was developed from the synthesis of the two reviews. These principles were reviewed by two focus groups held in Fiji and the Solomon Islands to produce a set of 20 validated principles. These validated principles can be grouped under the headings of learning theory, structure and design, and learning and teaching methods. The 20 principles outlined in this article will be used to develop and trial culturally relevant training approaches for the development of medicine management competencies for various cadres of health personnel in PICs. These principles provide a practical framework for educators and health professionals to apply to health-based education and training in the Pacific, with potential application to other rural and remote environments.

Face validation of the Virtual Electrosurgery Skill Trainer (VEST©).

PubMed

Sankaranarayanan, Ganesh; Li, Baichun; Miller, Amie; Wakily, Hussna; Jones, Stephanie B; Schwaitzberg, Steven; Jones, Daniel B; De, Suvranu; Olasky, Jaisa

2016-02-01

Electrosurgery is a modality that is widely used in surgery, whose use has resulted in injuries, OR fires and even death. The SAGES has established the FUSE program to address the knowledge gap in the proper and safe usage of electrosurgical devices. Complementing it, we have developed the Virtual Electrosurgery Skill Trainer (VEST(©)), which is designed to train subjects in both cognitive and motor skills necessary to safely operate electrosurgical devices. The objective of this study is to asses the face validity of the VEST(©) simulator. Sixty-three subjects were recruited at the 2014 SAGES Learning Center. They all completed the monopolar electrosurgery module on the VEST(©) simulator. At the end of the study, subjects assessed the face validity with questions that were scored on a 5-point Likert scale. The subjects were divided into two groups; FUSE experience (n = 15) and no FUSE experience (n = 48). The median score for both the groups was 4 or higher on all questions and 5 on questions on effectiveness of VEST(©) in aiding learning electrosurgery fundamentals. Questions on using the simulator in their own skills lab and recommending it to their peers also scored at 5. Mann-Whitney U test showed no significant difference (p > 0.05) indicating a general agreement. 46% of the respondents preferred VEST compared with 52% who preferred animal model and 2% preferred both for training in electrosurgery. This study demonstrated the face validity of the VEST(©) simulator. High scores showed that the simulator was visually realistic and reproduced lifelike tissue effects and the features were adequate enough to provide high realism. The self-learning instructional material was also found to be very useful in learning the fundamentals of electrosurgery. Adding more modules would increase the applicability of the VEST(©) simulator.

Validation of a virtual reality-based robotic surgical skills curriculum.

PubMed

Connolly, Michael; Seligman, Johnathan; Kastenmeier, Andrew; Goldblatt, Matthew; Gould, Jon C

2014-05-01

The clinical application of robotic-assisted surgery (RAS) is rapidly increasing. The da Vinci Surgical System™ is currently the only commercially available RAS system. The skills necessary to perform robotic surgery are unique from those required for open and laparoscopic surgery. A validated laparoscopic surgical skills curriculum (fundamentals of laparoscopic surgery or FLS™) has transformed the way surgeons acquire laparoscopic skills. There is a need for a similar skills training and assessment tool specific for robotic surgery. Based on previously published data and expert opinion, we developed a robotic skills curriculum. We sought to evaluate this curriculum for evidence of construct validity (ability to discriminate between users of different skill levels). Four experienced surgeons (>20 RAS) and 20 novice surgeons (first-year medical students with no surgical or RAS experience) were evaluated. The curriculum comprised five tasks utilizing the da Vinci™ Skills Simulator (Pick and Place, Camera Targeting 2, Peg Board 2, Matchboard 2, and Suture Sponge 3). After an orientation to the robot and a period of acclimation in the simulator, all subjects completed three consecutive repetitions of each task. Computer-derived performance metrics included time, economy of motion, master work space, instrument collisions, excessive force, distance of instruments out of view, drops, missed targets, and overall scores (a composite of all metrics). Experienced surgeons significantly outperformed novice surgeons in most metrics. Statistically significant differences were detected for each task in regards to mean overall scores and mean time (seconds) to completion. The curriculum we propose is a valid method of assessing and distinguishing robotic surgical skill levels on the da Vinci Si™ Surgical System. Further study is needed to establish proficiency levels and to demonstrate that training on the simulator with the proposed curriculum leads to improved robotic surgical performance in the operating room.

Face Validation of the Virtual Electrosurgery Skill Trainer (VEST©)

PubMed Central

Sankaranarayanan, Ganesh; Li, Baichun; Miller, Amie; Wakily, Hussna; Jones, Stephanie B.; Schwaitzberg, Steven; Jones, Daniel B.; De, Suvranu; Olasky, Jaisa

2015-01-01

Background Electrosurgery is a modality that is widely used in surgery, whose use has resulted in injuries, OR fires and even death. The SAGES has established the FUSE program to address the knowledge gap in the proper and safe usage of electrosurgical devices. Complementing it, we have developed the Virtual Electrosurgery Skill Trainer (VEST©), which is designed to train subjects in both cognitive and motor skills necessary to safely operate electrosurgical devices. The objective of this study is to asses the face validity of the VEST© simulator. Methods Sixty-three subjects were recruited at the 2014 SAGES Learning Center. They all completed the monopolar electrosurgery module on the VEST© simulator. At the end of the study, subjects assessed the face validity with questions that were scored on a 5-point Likert scale. Results The subjects were divided into two groups; FUSE experience (n = 15) and no FUSE experience (n = 48). The median score for both the groups was 4 or higher on all questions and 5 on questions on effectiveness of VEST© in aiding learning electrosurgery fundamentals. Questions on using the simulator in their own skills lab and recommending it to their peers also scored at 5. Mann-Whitney U test showed no significant difference (p > 0.05) indicating a general agreement. 46 % of the respondents preferred VEST compared to 52 % who preferred animal model and 2 % preferred both for training in electrosurgery. Conclusion This study demonstrated the face validity of the VEST © simulator. High scores showed that the simulator was visually realistic and reproduced lifelike tissue effects and the features were adequate enough to provide high realism. The self-learning instructional material was also found to be very useful in learning the fundamentals of electrosurgery. Adding more modules would increase the applicability of the VEST© simulator. PMID:26092003

Fire detection from hyperspectral data using neural network approach

NASA Astrophysics Data System (ADS)

Piscini, Alessandro; Amici, Stefania

2015-10-01

This study describes an application of artificial neural networks for the recognition of flaming areas using hyper- spectral remote sensed data. Satellite remote sensing is considered an effective and safe way to monitor active fires for environmental and people safeguarding. Neural networks are an effective and consolidated technique for the classification of satellite images. Moreover, once well trained, they prove to be very fast in the application stage for a rapid response. At flaming temperature, thanks to its low excitation energy (about 4.34 eV), potassium (K) ionize with a unique doublet emission features. This emission features can be detected remotely providing a detection map of active fire which allows in principle to separate flaming from smouldering areas of vegetation even in presence of smoke. For this study a normalised Advanced K Band Difference (AKBD) has been applied to airborne hyper spectral sensor covering a range of 400-970 nm with resolution 2.9 nm. A back propagation neural network was used for the recognition of active fires affecting the hyperspectral image. The network was trained using all channels of sensor as inputs, and the corresponding AKBD indexes as target output. In order to evaluate its generalization capabilities, the neural network was validated on two independent data sets of hyperspectral images, not used during neural network training phase. The validation results for the independent data-sets had an overall accuracy round 100% for both image and a few commission errors (0.1%), therefore demonstrating the feasibility of estimating the presence of active fires using a neural network approach. Although the validation of the neural network classifier had a few commission errors, the producer accuracies were lower due to the presence of omission errors. Image analysis revealed that those false negatives lie in "smoky" portion fire fronts, and due to the low intensity of the signal. The proposed method can be considered effective both in terms of classification accuracy and generalization capability. In particular our approach proved to be robust in the rejection of false positives, often corresponding to noisy or smoke pixels, whose presence in hyperspectral images can often undermine the performance of traditional classification algorithms. In order to improve neural network performance, future activities will include also the exploiting of hyperspectral images in the shortwave infrared region of the electromagnetic spectrum, covering wavelengths from 1400 to 2500 nm, which include significant emitted radiance from fire.

A machine learning approach to triaging patients with chronic obstructive pulmonary disease

PubMed Central

Qirko, Klajdi; Smith, Ted; Corcoran, Ethan; Wysham, Nicholas G.; Bazaz, Gaurav; Kappel, George; Gerber, Anthony N.

2017-01-01

COPD patients are burdened with a daily risk of acute exacerbation and loss of control, which could be mitigated by effective, on-demand decision support tools. In this study, we present a machine learning-based strategy for early detection of exacerbations and subsequent triage. Our application uses physician opinion in a statistically and clinically comprehensive set of patient cases to train a supervised prediction algorithm. The accuracy of the model is assessed against a panel of physicians each triaging identical cases in a representative patient validation set. Our results show that algorithm accuracy and safety indicators surpass all individual pulmonologists in both identifying exacerbations and predicting the consensus triage in a 101 case validation set. The algorithm is also the top performer in sensitivity, specificity, and ppv when predicting a patient’s need for emergency care. PMID:29166411

An over-view of robot assisted surgery curricula and the status of their validation.

PubMed

Fisher, Rebecca A; Dasgupta, Prokar; Mottrie, Alex; Volpe, Alessandro; Khan, Mohammed S; Challacombe, Ben; Ahmed, Kamran

2015-01-01

Robotic surgery is a rapidly expanding field. Thus far training for robotic techniques has been unstructured and the requirements are variable across various regions. Several projects are currently underway to develop a robotic surgery curriculum and are in various stages of validation. We aimed to outline the structures of available curricula, their process of development, validation status and current utilization. We undertook a literature review of papers including the MeSH terms "Robotics" and "Education". When we had an overview of curricula in development, we searched recent conference abstracts to gain up to date information. The main curricula are the FRS, the FSRS, the Canadian BSTC and the ERUS initiative. They are in various stages of validation and offer a mixture of theoretical and practical training, using both physical and simulated models. Whilst the FSRS is based on tasks on the RoSS virtual reality simulator, FRS and BSTC are designed for use on simulators and the robot itself. The ERUS curricula benefits from a combination of dry lab, wet lab and virtual reality components, which may allow skills to be more transferable to the OR as tasks are completed in several formats. Finally, the ERUS curricula includes the OR modular training programme as table assistant and console surgeon. Curricula are a crucial step in global standardisation of training and certification of surgeons for robotic surgical procedures. Many curricula are in early stages of development and more work is needed in development and validation of these programmes before training can be standardised. Copyright © 2014 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Development and implementation of centralized simulation training: evaluation of feasibility, acceptability and construct validity.

PubMed

Shamim Khan, Mohammad; Ahmed, Kamran; Gavazzi, Andrea; Gohil, Rishma; Thomas, Libby; Poulsen, Johan; Ahmed, Munir; Jaye, Peter; Dasgupta, Prokar

2013-03-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: A competent urologist should not only have effective technical skills, but also other attributes that would make him/her a complete surgeon. These include team-working, communication and decision-making skills. Although evidence for effectiveness of simulation exists for individual simulators, there is a paucity of evidence for utility and effectiveness of these simulators in training programmes that aims to combine technical and non-technical skills training. This article explains the process of development and validation of a centrally coordinated simulation program (Participants - South-East Region Specialist Registrars) under the umbrella of the British Association for Urological Surgeons (BAUS) and the London Deanery. This program incorporated training of both technical (synthetic, animal and virtual reality models) and non-technical skills (simulated operating theatres). To establish the feasibility and acceptability of a centralized, simulation-based training-programme. Simulation is increasingly establishing its role in urological training, with two areas that are relevant to urologists: (i) technical skills and (ii) non-technical skills. For this London Deanery supported pilot Simulation and Technology enhanced Learning Initiative (STeLI) project, we developed a structured multimodal simulation training programme. The programme incorporated: (i) technical skills training using virtual-reality simulators (Uro-mentor and Perc-mentor [Symbionix, Cleveland, OH, USA], Procedicus MIST-Nephrectomy [Mentice, Gothenburg, Sweden] and SEP Robotic simulator [Sim Surgery, Oslo, Norway]); bench-top models (synthetic models for cystocopy, transurethral resection of the prostate, transurethral resection of bladder tumour, ureteroscopy); and a European (Aalborg, Denmark) wet-lab training facility; as well as (ii) non-technical skills/crisis resource management (CRM), using SimMan (Laerdal Medical Ltd, Orpington, UK) to teach team-working, decision-making and communication skills. The feasibility, acceptability and construct validity of these training modules were assessed using validated questionnaires, as well as global and procedure/task-specific rating scales. In total 33, three specialist registrars of different grades and five urological nurses participated in the present study. Construct-validity between junior and senior trainees was significant. Of the participants, 90% rated the training models as being realistic and easy to use. In total 95% of the participants recommended the use of simulation during surgical training, 95% approved the format of the teaching by the faculty and 90% rated the sessions as well organized. A significant number of trainees (60%) would like to have easy access to a simulation facility to allow more practice and enhancement of their skills. A centralized simulation programme that provides training in both technical and non-technical skills is feasible. It is expected to improve the performance of future surgeons in a simulated environment and thus improve patient safety. © 2012 BJU International.

A GPU Simulation Tool for Training and Optimisation in 2D Digital X-Ray Imaging.

PubMed

Gallio, Elena; Rampado, Osvaldo; Gianaria, Elena; Bianchi, Silvio Diego; Ropolo, Roberto

2015-01-01

Conventional radiology is performed by means of digital detectors, with various types of technology and different performance in terms of efficiency and image quality. Following the arrival of a new digital detector in a radiology department, all the staff involved should adapt the procedure parameters to the properties of the detector, in order to achieve an optimal result in terms of correct diagnostic information and minimum radiation risks for the patient. The aim of this study was to develop and validate a software capable of simulating a digital X-ray imaging system, using graphics processing unit computing. All radiological image components were implemented in this application: an X-ray tube with primary beam, a virtual patient, noise, scatter radiation, a grid and a digital detector. Three different digital detectors (two digital radiography and a computed radiography systems) were implemented. In order to validate the software, we carried out a quantitative comparison of geometrical and anthropomorphic phantom simulated images with those acquired. In terms of average pixel values, the maximum differences were below 15%, while the noise values were in agreement with a maximum difference of 20%. The relative trends of contrast to noise ratio versus beam energy and intensity were well simulated. Total calculation times were below 3 seconds for clinical images with pixel size of actual dimensions less than 0.2 mm. The application proved to be efficient and realistic. Short calculation times and the accuracy of the results obtained make this software a useful tool for training operators and dose optimisation studies.

Skills Acquisition in Plantain Flour Processing Enterprises: A Validation of Training Modules for Senior Secondary Schools

ERIC Educational Resources Information Center

Udofia, Nsikak-Abasi; Nlebem, Bernard S.

2013-01-01

This study was to validate training modules that can help provide requisite skills for Senior Secondary school students in plantain flour processing enterprises for self-employment and to enable them pass their examination. The study covered Rivers State. Purposive sampling technique was used to select a sample size of 205. Two sets of structured…

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

PubMed Central

Stikic, Maja; Berka, Chris; Levendowski, Daniel J.; Rubio, Roberto F.; Tan, Veasna; Korszen, Stephanie; Barba, Douglas; Wurzer, David

2014-01-01

The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make “deadly force decisions” in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments. PMID:25414629

An application in identifying high-risk populations in alternative tobacco product use utilizing logistic regression and CART: a heuristic comparison.

PubMed

Lei, Yang; Nollen, Nikki; Ahluwahlia, Jasjit S; Yu, Qing; Mayo, Matthew S

2015-04-09

Other forms of tobacco use are increasing in prevalence, yet most tobacco control efforts are aimed at cigarettes. In light of this, it is important to identify individuals who are using both cigarettes and alternative tobacco products (ATPs). Most previous studies have used regression models. We conducted a traditional logistic regression model and a classification and regression tree (CART) model to illustrate and discuss the added advantages of using CART in the setting of identifying high-risk subgroups of ATP users among cigarettes smokers. The data were collected from an online cross-sectional survey administered by Survey Sampling International between July 5, 2012 and August 15, 2012. Eligible participants self-identified as current smokers, African American, White, or Latino (of any race), were English-speaking, and were at least 25 years old. The study sample included 2,376 participants and was divided into independent training and validation samples for a hold out validation. Logistic regression and CART models were used to examine the important predictors of cigarettes + ATP users. The logistic regression model identified nine important factors: gender, age, race, nicotine dependence, buying cigarettes or borrowing, whether the price of cigarettes influences the brand purchased, whether the participants set limits on cigarettes per day, alcohol use scores, and discrimination frequencies. The C-index of the logistic regression model was 0.74, indicating good discriminatory capability. The model performed well in the validation cohort also with good discrimination (c-index = 0.73) and excellent calibration (R-square = 0.96 in the calibration regression). The parsimonious CART model identified gender, age, alcohol use score, race, and discrimination frequencies to be the most important factors. It also revealed interesting partial interactions. The c-index is 0.70 for the training sample and 0.69 for the validation sample. The misclassification rate was 0.342 for the training sample and 0.346 for the validation sample. The CART model was easier to interpret and discovered target populations that possess clinical significance. This study suggests that the non-parametric CART model is parsimonious, potentially easier to interpret, and provides additional information in identifying the subgroups at high risk of ATP use among cigarette smokers.

25 CFR 26.32 - What constitutes a complete Job Training Program application?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false What constitutes a complete Job Training Program... JOB PLACEMENT AND TRAINING PROGRAM Training Services § 26.32 What constitutes a complete Job Training Program application? A request for training includes: (a) Intake and application data; (b) Feasible...

Risk Prediction of New Adjacent Vertebral Fractures After PVP for Patients with Vertebral Compression Fractures: Development of a Prediction Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhong, Bin-Yan; He, Shi-Cheng; Zhu, Hai-Dong

PurposeWe aim to determine the predictors of new adjacent vertebral fractures (AVCFs) after percutaneous vertebroplasty (PVP) in patients with osteoporotic vertebral compression fractures (OVCFs) and to construct a risk prediction score to estimate a 2-year new AVCF risk-by-risk factor condition.Materials and MethodsPatients with OVCFs who underwent their first PVP between December 2006 and December 2013 at Hospital A (training cohort) and Hospital B (validation cohort) were included in this study. In training cohort, we assessed the independent risk predictors and developed the probability of new adjacent OVCFs (PNAV) score system using the Cox proportional hazard regression analysis. The accuracy ofmore » this system was then validated in both training and validation cohorts by concordance (c) statistic.Results421 patients (training cohort: n = 256; validation cohort: n = 165) were included in this study. In training cohort, new AVCFs after the first PVP treatment occurred in 33 (12.9%) patients. The independent risk factors were intradiscal cement leakage and preexisting old vertebral compression fracture(s). The estimated 2-year absolute risk of new AVCFs ranged from less than 4% in patients with neither independent risk factors to more than 45% in individuals with both factors.ConclusionsThe PNAV score is an objective and easy approach to predict the risk of new AVCFs.« less

Rational selection of training and test sets for the development of validated QSAR models

NASA Astrophysics Data System (ADS)

Golbraikh, Alexander; Shen, Min; Xiao, Zhiyan; Xiao, Yun-De; Lee, Kuo-Hsiung; Tropsha, Alexander

2003-02-01

Quantitative Structure-Activity Relationship (QSAR) models are used increasingly to screen chemical databases and/or virtual chemical libraries for potentially bioactive molecules. These developments emphasize the importance of rigorous model validation to ensure that the models have acceptable predictive power. Using k nearest neighbors ( kNN) variable selection QSAR method for the analysis of several datasets, we have demonstrated recently that the widely accepted leave-one-out (LOO) cross-validated R2 (q2) is an inadequate characteristic to assess the predictive ability of the models [Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Mod. 20, 269-276, (2002)]. Herein, we provide additional evidence that there exists no correlation between the values of q 2 for the training set and accuracy of prediction ( R 2) for the test set and argue that this observation is a general property of any QSAR model developed with LOO cross-validation. We suggest that external validation using rationally selected training and test sets provides a means to establish a reliable QSAR model. We propose several approaches to the division of experimental datasets into training and test sets and apply them in QSAR studies of 48 functionalized amino acid anticonvulsants and a series of 157 epipodophyllotoxin derivatives with antitumor activity. We formulate a set of general criteria for the evaluation of predictive power of QSAR models.

A Standardized System of Training Intensity Guidelines for the Sports of Track and Field and Cross Country

ERIC Educational Resources Information Center

Belcher, Christopher P.; Pemberton, Cynthia Lee A.

2012-01-01

Accurate quantification of training intensity is an essential component of a training program (Rowbottom, 2000). A training program designed to optimize athlete performance abilities cannot be practically planned or implemented without a valid and reliable indication of training intensity and its effect on the physiological mechanisms of the human…

Accuracy of predicting genomic breeding values for residual feed intake in Angus and Charolais beef cattle.

PubMed

Chen, L; Schenkel, F; Vinsky, M; Crews, D H; Li, C

2013-10-01

In beef cattle, phenotypic data that are difficult and/or costly to measure, such as feed efficiency, and DNA marker genotypes are usually available on a small number of animals of different breeds or populations. To achieve a maximal accuracy of genomic prediction using the phenotype and genotype data, strategies for forming a training population to predict genomic breeding values (GEBV) of the selection candidates need to be evaluated. In this study, we examined the accuracy of predicting GEBV for residual feed intake (RFI) based on 522 Angus and 395 Charolais steers genotyped on SNP with the Illumina Bovine SNP50 Beadchip for 3 training population forming strategies: within breed, across breed, and by pooling data from the 2 breeds (i.e., combined). Two other scenarios with the training and validation data split by birth year and by sire family within a breed were also investigated to assess the impact of genetic relationships on the accuracy of genomic prediction. Three statistical methods including the best linear unbiased prediction with the relationship matrix defined based on the pedigree (PBLUP), based on the SNP genotypes (GBLUP), and a Bayesian method (BayesB) were used to predict the GEBV. The results showed that the accuracy of the GEBV prediction was the highest when the prediction was within breed and when the validation population had greater genetic relationships with the training population, with a maximum of 0.58 for Angus and 0.64 for Charolais. The within-breed prediction accuracies dropped to 0.29 and 0.38, respectively, when the validation populations had a minimal pedigree link with the training population. When the training population of a different breed was used to predict the GEBV of the validation population, that is, across-breed genomic prediction, the accuracies were further reduced to 0.10 to 0.22, depending on the prediction method used. Pooling data from the 2 breeds to form the training population resulted in accuracies increased to 0.31 and 0.43, respectively, for the Angus and Charolais validation populations. The results suggested that the genetic relationship of selection candidates with the training population has a greater impact on the accuracy of GEBV using the Illumina Bovine SNP50 Beadchip. Pooling data from different breeds to form the training population will improve the accuracy of across breed genomic prediction for RFI in beef cattle.

Nearest neighbor density ratio estimation for large-scale applications in astronomy

NASA Astrophysics Data System (ADS)

Kremer, J.; Gieseke, F.; Steenstrup Pedersen, K.; Igel, C.

2015-09-01

In astronomical applications of machine learning, the distribution of objects used for building a model is often different from the distribution of the objects the model is later applied to. This is known as sample selection bias, which is a major challenge for statistical inference as one can no longer assume that the labeled training data are representative. To address this issue, one can re-weight the labeled training patterns to match the distribution of unlabeled data that are available already in the training phase. There are many examples in practice where this strategy yielded good results, but estimating the weights reliably from a finite sample is challenging. We consider an efficient nearest neighbor density ratio estimator that can exploit large samples to increase the accuracy of the weight estimates. To solve the problem of choosing the right neighborhood size, we propose to use cross-validation on a model selection criterion that is unbiased under covariate shift. The resulting algorithm is our method of choice for density ratio estimation when the feature space dimensionality is small and sample sizes are large. The approach is simple and, because of the model selection, robust. We empirically find that it is on a par with established kernel-based methods on relatively small regression benchmark datasets. However, when applied to large-scale photometric redshift estimation, our approach outperforms the state-of-the-art.

Current status of robotic simulators in acquisition of robotic surgical skills.

PubMed

Kumar, Anup; Smith, Roger; Patel, Vipul R

2015-03-01

This article provides an overview of the current status of simulator systems in robotic surgery training curriculum, focusing on available simulators for training, their comparison, new technologies introduced in simulation focusing on concepts of training along with existing challenges and future perspectives of simulator training in robotic surgery. The different virtual reality simulators available in the market like dVSS, dVT, RoSS, ProMIS and SEP have shown face, content and construct validity in robotic skills training for novices outside the operating room. Recently, augmented reality simulators like HoST, Maestro AR and RobotiX Mentor have been introduced in robotic training providing a more realistic operating environment, emphasizing more on procedure-specific robotic training . Further, the Xperience Team Trainer, which provides training to console surgeon and bed-side assistant simultaneously, has been recently introduced to emphasize the importance of teamwork and proper coordination. Simulator training holds an important place in current robotic training curriculum of future robotic surgeons. There is a need for more procedure-specific augmented reality simulator training, utilizing advancements in computing and graphical capabilities for new innovations in simulator technology. Further studies are required to establish its cost-benefit ratio along with concurrent and predictive validity.

Leadership Perceptions of Results and Return on Investment Training Evaluations

ERIC Educational Resources Information Center

Preston, Kevin F.

2010-01-01

This study sought to validate whether the literature on high level training evaluation (level four results and level five return on investment) accurately reflected the expectations of organizational leaders regarding training evaluation reports. The researcher was interested in what high level training evaluation was being conducted at…

Vocational Education and Training in Denmark: Short Description. CEDEFOP Panorama Series.

ERIC Educational Resources Information Center

Cort, Pia

Denmark has a uniform, nationwide vocational education and training (VET) system that provides qualifications that are valid throughout the country and recognized by employers and trade unions. Initial VET (IVET) includes the following components: VET, including commercial and technical training; basic social and health care training; agricultural…

Face validity of a Wii U video game for training basic laparoscopic skills.

PubMed

Jalink, Maarten B; Goris, Jetse; Heineman, Erik; Pierie, Jean-Pierre E N; Ten Cate Hoedemaker, Henk O

2015-06-01

Although the positive effects of playing video games on basic laparoscopic skills have been studied for several years, no games are actually used in surgical training. This article discusses the face validity of the first video game and custom-made hardware, which takes advantage of these effects. Participants were recruited at the Chirurgendagen 2013 and the Society of American Gastrointestinal and Endoscopic Surgeons 2014 annual meeting. In total, 72 laparoscopic surgeons completed a demo of the game and filled in a questionnaire. On a 1-to-10 scale, the mean score for hardware realism was 7.2 and the mean score for usefulness as a training tool was 8.4. Participants did not mind the fact that the workspace does not look like an abdominal cavity, but do have some trouble with the absence of tactile feedback. We obtained face validity for both the hardware and the usefulness of Underground, a video game made for training basic laparoscopic skills. Copyright © 2015 Elsevier Inc. All rights reserved.

Energy and wear optimisation of train longitudinal dynamics and of traction and braking systems

NASA Astrophysics Data System (ADS)

Conti, R.; Galardi, E.; Meli, E.; Nocciolini, D.; Pugi, L.; Rindi, A.

2015-05-01

Traction and braking systems deeply affect longitudinal train dynamics, especially when an extensive blending phase among different pneumatic, electric and magnetic devices is required. The energy and wear optimisation of longitudinal vehicle dynamics has a crucial economic impact and involves several engineering problems such as wear of braking friction components, energy efficiency, thermal load on components, level of safety under degraded or adhesion conditions (often constrained by the current regulation in force on signalling or other safety-related subsystem). In fact, the application of energy storage systems can lead to an efficiency improvement of at least 10% while, as regards the wear reduction, the improvement due to distributed traction systems and to optimised traction devices can be quantified in about 50%. In this work, an innovative integrated procedure is proposed by the authors to optimise longitudinal train dynamics and traction and braking manoeuvres in terms of both energy and wear. The new approach has been applied to existing test cases and validated with experimental data provided by Breda and, for some components and their homologation process, the results of experimental activities derive from cooperation performed with relevant industrial partners such as Trenitalia and Italcertifer. In particular, simulation results are referred to the simulation tests performed on a high-speed train (Ansaldo Breda Emu V250) and on a tram (Ansaldo Breda Sirio Tram). The proposed approach is based on a modular simulation platform in which the sub-models corresponding to different subsystems can be easily customised, depending on the considered application, on the availability of technical data and on the homologation process of different components.

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection

PubMed Central

Gordon, Nicholas; Griffiths, Thomas; Kraemer, John D; Siedner, Mark J

2017-01-01

Background The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. Objective We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term “validation relaxation.” Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. Methods We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of “required” constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. Results The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. Conclusions A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy. PMID:28821474

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection.

PubMed

Kenny, Avi; Gordon, Nicholas; Griffiths, Thomas; Kraemer, John D; Siedner, Mark J

2017-08-18

The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term "validation relaxation." Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of "required" constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy. ©Avi Kenny, Nicholas Gordon, Thomas Griffiths, John D Kraemer, Mark J Siedner. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.08.2017.

Development, test-retest reliability, and construct validity of the resistance training skills battery.

PubMed

Lubans, David R; Smith, Jordan J; Harries, Simon K; Barnett, Lisa M; Faigenbaum, Avery D

2014-05-01

The aim of this study was to describe the development and assess test-retest reliability and construct validity of the Resistance Training Skills Battery (RTSB) for adolescents. The RTSB provides an assessment of resistance training skill competency and includes 6 exercises (i.e., body weight squat, push-up, lunge, suspended row, standing overhead press, and front support with chest touches). Scoring for each skill is based on the number of performance criteria successfully demonstrated. An overall resistance training skill quotient (RTSQ) is created by adding participants' scores for the 6 skills. Participants (44 boys and 19 girls, mean age = 14.5 ± 1.2 years) completed the RTSB on 2 occasions separated by 7 days. Participants also completed the following fitness tests, which were used to create a muscular fitness score (MFS): handgrip strength, timed push-up, and standing long jump tests. Intraclass correlation (ICC), paired samples t-tests, and typical error were used to assess test-retest reliability. To assess construct validity, gender and RTSQ were entered into a regression model predicting MFS. The rank order repeatability of the RTSQ was high (ICC = 0.88). The model explained 39% of the variance in MFS (p ≤ 0.001) and RTSQ (r = 0.40, p ≤ 0.001) was a significant predictor. This study has demonstrated the construct validity and test-retest reliability of the RTSB in a sample of adolescents. The RTSB can reliably rank participants in regards to their resistance training competency and has the necessary sensitivity to detect small changes in resistance training skill proficiency.

Assessing personal initiative among vocational training students: development and validation of a new measure.

PubMed

Balluerka, Nekane; Gorostiaga, Arantxa; Ulacia, Imanol

2014-11-14

Personal initiative characterizes people who are proactive, persistent and self-starting when facing the difficulties that arise in achieving goals. Despite its importance in the educational field there is a scarcity of measures to assess students' personal initiative. Thus, the aim of the present study was to develop a questionnaire to assess this variable in the academic environment and to validate it for adolescents and young adults. The sample comprised 244 vocational training students. The questionnaire showed a factor structure including three factors (Proactivity-Prosocial behavior, Persistence and Self-Starting) with acceptable indices of internal consistency (ranging between α = .57 and α =.73) and good convergent validity with respect to the Self-Reported Initiative scale. Evidence of external validity was also obtained based on the relationships between personal initiative and variables such as self-efficacy, enterprising attitude, responsibility and control aspirations, conscientiousness, and academic achievement. The results indicate that this new measure is very useful for assessing personal initiative among vocational training students.

Development and implementation of a virtual reality laparoscopic colorectal training curriculum.

PubMed

Wynn, Greg; Lykoudis, Panagis; Berlingieri, Pasquale

2017-12-12

Contemporary surgical training can be compromised by fewer practical opportunities. Simulation can fill this gap to optimize skills' development and progress monitoring. A structured virtual reality (VR) laparoscopic sigmoid colectomy curriculum is constructed and its validity and outcomes assessed. Parameters and thresholds were defined by analysing the performance of six expert surgeons completing the relevant module on the LAP Mentor simulator. Fourteen surgical trainees followed the curriculum, performance being recorded and analysed. Evidence of validity was assessed. Time to complete procedure, number of movements of right and left instrument, and total path length of right and left instrument movements demonstrated evidence of validity and clear learning curves, with a median of 14 attempts needed to complete the curriculum. A structured curriculum is proposed for training in laparoscopic sigmoid colectomy in a VR environment based on objective metrics in addition to expert consensus. Validity has been demonstrated for some key metrics. Copyright © 2017 Elsevier Inc. All rights reserved.

Development, initial reliability and validity testing of an observational tool for assessing technical skills of operating room nurses.

PubMed

Sevdalis, Nick; Undre, Shabnam; Henry, Janet; Sydney, Elaine; Koutantji, Mary; Darzi, Ara; Vincent, Charles A

2009-09-01

The recent emergence of the Systems Approach to the safety and quality of surgical care has triggered individual and team skills training modules for surgeons and anaesthetists and relevant observational assessment tools have been developed. To develop an observational tool that captures operating room (OR) nurses' technical skill and can be used for assessment and training. The Imperial College Assessment of Technical Skills for Nurses (ICATS-N) assesses (i) gowning and gloving, (ii) setting up instrumentation, (iii) draping, and (iv) maintaining sterility. Three to five observable behaviours have been identified for each skill and are rated on 1-6 scales. Feasibility and aspects of reliability and validity were assessed in 20 simulation-based crisis management training modules for trainee nurses and doctors, carried out in a Simulated Operating Room. The tool was feasible to use in the context of simulation-based training. Satisfactory reliability (Cronbach alpha) was obtained across trainers' and trainees' scores (analysed jointly and separately). Moreover, trainer nurse's ratings of the four skills correlated positively, thus indicating adequate content validity. Trainer's and trainees' ratings did not correlate. Assessment of OR nurses' technical skill is becoming a training priority. The present evidence suggests that the ICATS-N could be considered for use as an assessment/training tool for junior OR nurses.

Clerkship maturity: Does the idea of training clinical skills work?

PubMed Central

Stosch, Christoph; Joachim, Alexander; Ascher, Johannes

2011-01-01

Background: With the reformed curriculum “4C”, the Medical Faculty of the University of Cologne has started to systematically plan practical skills training, for which Clerkship Maturity is the first step. The key guidelines along which the curriculum was development were developed by experts. This approach has now been validated. Materials and methods: Both students and teachers were asked to fill in a questionnaire regarding preclinical practical skills training to confirm the concept of Clerkship Maturity. Results and discussion: The Cologne training program Clerkship Maturity can be validated empirically overall through the activities of the students awaiting the clerkship framework and through the evaluation by the medical staff providing the training. The subjective ratings of the advantages of the training by the students leave room for improvement. Apart from minor improvements to the program, the most likely solution providing sustainable results will involve an over-regional strategy for establishing skills training planned as part of the curriculum. PMID:21866243

Optimization of training periods for the estimation model of three-dimensional target positions using an external respiratory surrogate.

PubMed

Iramina, Hiraku; Nakamura, Mitsuhiro; Iizuka, Yusuke; Mitsuyoshi, Takamasa; Matsuo, Yukinori; Mizowaki, Takashi; Kanno, Ikuo

2018-04-19

During therapeutic beam irradiation, an unvisualized three-dimensional (3D) target position should be estimated using an external surrogate with an estimation model. Training periods for the developed model with no additional imaging during beam irradiation were optimized using clinical data. Dual-source 4D-CBCT projection data for 20 lung cancer patients were used for validation. Each patient underwent one to three scans. The actual target positions of each scan were equally divided into two equal parts: one for the modeling and the other for the validating session. A quadratic target position estimation equation was constructed during the modeling session. Various training periods for the session-i.e., modeling periods (T M )-were employed: T M  ∈ {5,10,15,25,35} [s]. First, the equation was used to estimate target positions in the validating session of the same scan (intra-scan estimations). Second, the equation was then used to estimate target positions in the validating session of another temporally different scan (inter-scan estimations). The baseline drift of the surrogate and target between scans was corrected. Various training periods for the baseline drift correction-i.e., correction periods (T C s)-were employed: T C  ∈ {5,10,15; T C  ≤ T M } [s]. Evaluations were conducted with and without the correction. The difference between the actual and estimated target positions was evaluated by the root-mean-square error (RMSE). The range of mean respiratory period and 3D motion amplitude of the target was 2.4-13.0 s and 2.8-34.2 mm, respectively. On intra-scan estimation, the median 3D RMSE was within 1.5-2.1 mm, supported by previous studies. On inter-scan estimation, median elapsed time between scans was 10.1 min. All T M s exhibited 75th percentile 3D RMSEs of 5.0-6.4 mm due to baseline drift of the surrogate and the target. After the correction, those for each T M s fell by 1.4-2.3 mm. The median 3D RMSE for both the 10-s T M and the T C period was 2.4 mm, which plateaued when the two training periods exceeded 10 s. A widely-applicable estimation model for the 3D target positions during beam irradiation was developed. The optimal T M and T C for the model were both 10 s, to allow for more than one respiratory cycle. UMIN000014825 . Registered: 11 August 2014.

An integrated approach to endoscopic instrument tracking for augmented reality applications in surgical simulation training.

PubMed

Loukas, Constantinos; Lahanas, Vasileios; Georgiou, Evangelos

2013-12-01

Despite the popular use of virtual and physical reality simulators in laparoscopic training, the educational potential of augmented reality (AR) has not received much attention. A major challenge is the robust tracking and three-dimensional (3D) pose estimation of the endoscopic instrument, which are essential for achieving interaction with the virtual world and for realistic rendering when the virtual scene is occluded by the instrument. In this paper we propose a method that addresses these issues, based solely on visual information obtained from the endoscopic camera. Two different tracking algorithms are combined for estimating the 3D pose of the surgical instrument with respect to the camera. The first tracker creates an adaptive model of a colour strip attached to the distal part of the tool (close to the tip). The second algorithm tracks the endoscopic shaft, using a combined Hough-Kalman approach. The 3D pose is estimated with perspective geometry, using appropriate measurements extracted by the two trackers. The method has been validated on several complex image sequences for its tracking efficiency, pose estimation accuracy and applicability in AR-based training. Using a standard endoscopic camera, the absolute average error of the tip position was 2.5 mm for working distances commonly found in laparoscopic training. The average error of the instrument's angle with respect to the camera plane was approximately 2°. The results are also supplemented by video segments of laparoscopic training tasks performed in a physical and an AR environment. The experiments yielded promising results regarding the potential of applying AR technologies for laparoscopic skills training, based on a computer vision framework. The issue of occlusion handling was adequately addressed. The estimated trajectory of the instruments may also be used for surgical gesture interpretation and assessment. Copyright © 2013 John Wiley & Sons, Ltd.

Benchmark of Machine Learning Methods for Classification of a SENTINEL-2 Image

NASA Astrophysics Data System (ADS)

Pirotti, F.; Sunar, F.; Piragnolo, M.

2016-06-01

Thanks to mainly ESA and USGS, a large bulk of free images of the Earth is readily available nowadays. One of the main goals of remote sensing is to label images according to a set of semantic categories, i.e. image classification. This is a very challenging issue since land cover of a specific class may present a large spatial and spectral variability and objects may appear at different scales and orientations. In this study, we report the results of benchmarking 9 machine learning algorithms tested for accuracy and speed in training and classification of land-cover classes in a Sentinel-2 dataset. The following machine learning methods (MLM) have been tested: linear discriminant analysis, k-nearest neighbour, random forests, support vector machines, multi layered perceptron, multi layered perceptron ensemble, ctree, boosting, logarithmic regression. The validation is carried out using a control dataset which consists of an independent classification in 11 land-cover classes of an area about 60 km2, obtained by manual visual interpretation of high resolution images (20 cm ground sampling distance) by experts. In this study five out of the eleven classes are used since the others have too few samples (pixels) for testing and validating subsets. The classes used are the following: (i) urban (ii) sowable areas (iii) water (iv) tree plantations (v) grasslands. Validation is carried out using three different approaches: (i) using pixels from the training dataset (train), (ii) using pixels from the training dataset and applying cross-validation with the k-fold method (kfold) and (iii) using all pixels from the control dataset. Five accuracy indices are calculated for the comparison between the values predicted with each model and control values over three sets of data: the training dataset (train), the whole control dataset (full) and with k-fold cross-validation (kfold) with ten folds. Results from validation of predictions of the whole dataset (full) show the random forests method with the highest values; kappa index ranging from 0.55 to 0.42 respectively with the most and least number pixels for training. The two neural networks (multi layered perceptron and its ensemble) and the support vector machines - with default radial basis function kernel - methods follow closely with comparable performance.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

PubMed

Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F

2011-11-28

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

PubMed Central

2011-01-01

Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy. PMID:22122853

OR fire virtual training simulator: design and face validity.

PubMed

Dorozhkin, Denis; Olasky, Jaisa; Jones, Daniel B; Schwaitzberg, Steven D; Jones, Stephanie B; Cao, Caroline G L; Molina, Marcos; Henriques, Steven; Wang, Jinling; Flinn, Jeff; De, Suvranu

2017-09-01

The Virtual Electrosurgical Skill Trainer is a tool for training surgeons the safe operation of electrosurgery tools in both open and minimally invasive surgery. This training includes a dedicated team-training module that focuses on operating room (OR) fire prevention and response. The module was developed to allow trainees, practicing surgeons, anesthesiologist, and nurses to interact with a virtual OR environment, which includes anesthesia apparatus, electrosurgical equipment, a virtual patient, and a fire extinguisher. Wearing a head-mounted display, participants must correctly identify the "fire triangle" elements and then successfully contain an OR fire. Within these virtual reality scenarios, trainees learn to react appropriately to the simulated emergency. A study targeted at establishing the face validity of the virtual OR fire simulator was undertaken at the 2015 Society of American Gastrointestinal and Endoscopic Surgeons conference. Forty-nine subjects with varying experience participated in this Institutional Review Board-approved study. The subjects were asked to complete the OR fire training/prevention sequence in the VEST simulator. Subjects were then asked to answer a subjective preference questionnaire consisting of sixteen questions, focused on the usefulness and fidelity of the simulator. On a 5-point scale, 12 of 13 questions were rated at a mean of 3 or greater (92%). Five questions were rated above 4 (38%), particularly those focusing on the simulator effectiveness and its usefulness in OR fire safety training. A total of 33 of the 49 participants (67%) chose the virtual OR fire trainer over the traditional training methods such as a textbook or an animal model. Training for OR fire emergencies in fully immersive VR environments, such as the VEST trainer, may be the ideal training modality. The face validity of the OR fire training module of the VEST simulator was successfully established on many aspects of the simulation.

Validity and reliability of the session-RPE method for quantifying training in Australian football: a comparison of the CR10 and CR100 scales.

PubMed

Scott, Tannath J; Black, Cameron R; Quinn, John; Coutts, Aaron J

2013-01-01

The purpose of this study was to examine and compare the criterion validity and test-retest reliability of the CR10 and CR100 rating of perceived exertion (RPE) scales for team sport athletes that undertake high-intensity, intermittent exercise. Twenty-one male Australian football (AF) players (age: 19.0 ± 1.8 years, body mass: 83.92 ± 7.88 kg) participated the first part (part A) of this study, which examined the construct validity of the session-RPE (sRPE) method for quantifying training load in AF. Ten male athletes (age: 16.1 ± 0.5 years) participated in the second part of the study (part B), which compared the test-retest reliability of the CR10 and CR100 RPE scales. In part A, the validity of the sRPE method was assessed by examining the relationships between sRPE, and objective measures of internal (i.e., heart rate) and external training load (i.e., distance traveled), collected from AF training sessions. Part B of the study assessed the reliability of sRPE through examining the test-retest reliability of sRPE during 3 different intensities of controlled intermittent running (10, 11.5, and 13 km·h(-1)). Results from part A demonstrated strong correlations for CR10- and CR100-derived sRPE with measures of internal training load (Banisters TRIMP and Edwards TRIMP) (CR10: r = 0.83 and 0.83, and CR100: r = 0.80 and 0.81, p < 0.05). Correlations between sRPE and external training load (distance, higher speed running and player load) for both the CR10 (r = 0.81, 0.71, and 0.83) and CR100 (r = 0.78, 0.69, and 0.80) were significant (p < 0.05). Results from part B demonstrated poor reliability for both the CR10 (31.9% CV) and CR100 (38.6% CV) RPE scales after short bouts of intermittent running. Collectively, these results suggest both CR10- and CR100-derived sRPE methods have good construct validity for assessing training load in AF. The poor levels of reliability revealed under field testing indicate that the sRPE method may not be sensible to detecting small changes in exercise intensity during brief intermittent running bouts. Despite this limitation, the sRPE remains a valid method to quantify training loads in high-intensity, intermittent team sport.

Development of 1RM Prediction Equations for Bench Press in Moderately Trained Men.

PubMed

Macht, Jordan W; Abel, Mark G; Mullineaux, David R; Yates, James W

2016-10-01

Macht, JW, Abel, MG, Mullineaux, DR, and Yates, JW. Development of 1RM prediction equations for bench press in moderately trained men. J Strength Cond Res 30(10): 2901-2906, 2016-There are a variety of established 1 repetition maximum (1RM) prediction equations, however, very few prediction equations use anthropometric characteristics exclusively or in part, to estimate 1RM strength. Therefore, the purpose of this study was to develop an original 1RM prediction equation for bench press using anthropometric and performance characteristics in moderately trained male subjects. Sixty male subjects (21.2 ± 2.4 years) completed a 1RM bench press and were randomly assigned a load to complete as many repetitions as possible. In addition, body composition, upper-body anthropometric characteristics, and handgrip strength were assessed. Regression analysis was used to develop a performance-based 1RM prediction equation: 1RM = 1.20 repetition weight + 2.19 repetitions to fatigue - 0.56 biacromial width (cm) + 9.6 (R = 0.99, standard error of estimate [SEE] = 3.5 kg). Regression analysis to develop a nonperformance-based 1RM prediction equation yielded: 1RM (kg) = 0.997 cross-sectional area (CSA) (cm) + 0.401 chest circumference (cm) - 0.385%fat - 0.185 arm length (cm) + 36.7 (R = 0.81, SEE = 13.0 kg). The performance prediction equations developed in this study had high validity coefficients, minimal mean bias, and small limits of agreement. The anthropometric equations had moderately high validity coefficient but larger limits of agreement. The practical applications of this study indicate that the inclusion of anthropometric characteristics and performance variables produce a valid prediction equation for 1RM strength. In addition, the CSA of the arm uses a simple nonperformance method of estimating the lifter's 1RM. This information may be used to predict the starting load for a lifter performing a 1RM prediction protocol or a 1RM testing protocol.

ICT Teacher Training: Evaluation of the Curriculum and Training Approach in Flanders

ERIC Educational Resources Information Center

Valcke, Martin; Rots, Isabel; Verbeke, Marjolein; van Braak, Johan

2007-01-01

A policy-evaluation study was set up of Information and Communication Technologies (ICT) teacher training in Flanders, focusing on the following questions: (a) What is the validity of the content and format of the teacher training, and (b) to what extent is the ICT teacher training linked to policies of schools? In-depth interviews were organised…

A quantitative and qualitative pilot study of the perceived benefits of autogenic training for a group of people with cancer.

PubMed

Wright, S; Courtney, U; Crowther, D

2002-06-01

This paper describes the application of autogenic training (AT), a technique of deep relaxation and self-hypnosis, in patients diagnosed with cancer,with the aim of increasing their coping ability, and reports the results of a questionnaire survey performed before and after an AT course. A reduction in arousal and anxiety can help individuals to perceive their environment as less hostile and threatening, with implications for improved perceived coping ability. Complementary therapies are considered useful in enhancing symptom relief, overall well-being and self-help when used as adjuvant therapies to allopathic medical interventions. The present study aimed to validate, in an Irish context, the effectiveness of AT as a complementary therapy for patients with cancer. Each participant completed a Hospital Anxiety and Depression Scale and Profile of Mood States questionnaire before and after a 10-week AT course. The results indicated a significant reduction in anxiety and increase in 'fighting spirit' after compared with before training, with an improved sense of coping and improved sleep being apparent benefits of AT practice.

Adaptive optics vision simulation and perceptual learning system based on a 35-element bimorph deformable mirror.

PubMed

Dai, Yun; Zhao, Lina; Xiao, Fei; Zhao, Haoxin; Bao, Hua; Zhou, Hong; Zhou, Yifeng; Zhang, Yudong

2015-02-10

An adaptive optics visual simulation combined with a perceptual learning (PL) system based on a 35-element bimorph deformable mirror (DM) was established. The larger stroke and smaller size of the bimorph DM made the system have larger aberration correction or superposition ability and be more compact. By simply modifying the control matrix or the reference matrix, select correction or superposition of aberrations was realized in real time similar to a conventional adaptive optics closed-loop correction. PL function was first integrated in addition to conventional adaptive optics visual simulation. PL training undertaken with high-order aberrations correction obviously improved the visual function of adult anisometropic amblyopia. The preliminary application of high-order aberrations correction with PL training on amblyopia treatment was being validated with a large scale population, which might have great potential in amblyopia treatment and visual performance maintenance.

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

Evaluation of the HARDMAN comparability methodology for manpower, personnel and training

NASA Technical Reports Server (NTRS)

Zimmerman, W.; Butler, R.; Gray, V.; Rosenberg, L.

1984-01-01

The methodology evaluation and recommendation are part of an effort to improve Hardware versus Manpower (HARDMAN) methodology for projecting manpower, personnel, and training (MPT) to support new acquisition. Several different validity tests are employed to evaluate the methodology. The methodology conforms fairly well with both the MPT user needs and other accepted manpower modeling techniques. Audits of three completed HARDMAN applications reveal only a small number of potential problem areas compared to the total number of issues investigated. The reliability study results conform well with the problem areas uncovered through the audits. The results of the accuracy studies suggest that the manpower life-cycle cost component is only marginally sensitive to changes in other related cost variables. Even with some minor problems, the methodology seem sound and has good near term utility to the Army. Recommendations are provided to firm up the problem areas revealed through the evaluation.

Classification With Truncated Distance Kernel.

PubMed

Huang, Xiaolin; Suykens, Johan A K; Wang, Shuning; Hornegger, Joachim; Maier, Andreas

2018-05-01

This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and local linear classifiers can be established simultaneously. The TL1 kernel has good adaptiveness to nonlinearity and is suitable for problems which require different nonlinearities in different areas. Though the TL1 kernel is not positive semidefinite, some classical kernel learning methods are still applicable which means that the TL1 kernel can be directly used in standard toolboxes by replacing the kernel evaluation. In numerical experiments, the TL1 kernel with a pregiven parameter achieves similar or better performance than the radial basis function kernel with the parameter tuned by cross validation, implying the TL1 kernel a promising nonlinear kernel for classification tasks.

A novel configuration for a brushless DC motor with an integrated planetary gear train

NASA Astrophysics Data System (ADS)

Yan, Hong-Sen; Wu, Yi-Chang

2006-06-01

This paper presents a novel configuration of a brushless DC (BLDC) motor with an integrated planetary gear train, which provides further functional and structural integrations to overcome inherent drawbacks of traditional designs. The effects of gear teeth on the magnetic field and performance of the BLDC motor are investigated. Two standard gear profile systems integrated on the stator with feasible numbers of gear teeth are introduced to reduce the cogging torque. An equivalent magnetic circuit model and an air-gap permeance model are applied to analytically analyze the magnetic field, while the validity is verified by 2-D finite-element method (FEM). Furthermore, the motor performance is discussed and compared with an existing design. The results show that the present design has the characteristics of lower cogging torque and torque ripple than the conventional design, which is of benefit to the widely applications on accurate motion and position control for BLDC motors.

46 CFR 401.211 - Requirements for training of Applicant Pilots.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 8 2011-10-01 2011-10-01 false Requirements for training of Applicant Pilots. 401.211... PILOTAGE REGULATIONS Registration of Pilots § 401.211 Requirements for training of Applicant Pilots. (a) The Director shall determine the number of Applicant Pilots required to be in training by each...

Evaluation of a virtual-reality-based simulator using passive haptic feedback for knee arthroscopy.

PubMed

Fucentese, Sandro F; Rahm, Stefan; Wieser, Karl; Spillmann, Jonas; Harders, Matthias; Koch, Peter P

2015-04-01

The aim of this work is to determine face validity and construct validity of a new virtual-reality-based simulator for diagnostic and therapeutic knee arthroscopy. The study tests a novel arthroscopic simulator based on passive haptics. Sixty-eight participants were grouped into novices, intermediates, and experts. All participants completed two exercises. In order to establish face validity, all participants filled out a questionnaire concerning different aspects of simulator realism, training capacity, and different statements using a seven-point Likert scale (range 1-7). Construct validity was tested by comparing various simulator metric values between novices and experts. Face validity could be established: overall realism was rated with a mean value of 5.5 points. Global training capacity scored a mean value of 5.9. Participants considered the simulator as useful for procedural training of diagnostic and therapeutic arthroscopy. In the foreign body removal exercise, experts were overall significantly faster in the whole procedure (6 min 24 s vs. 8 min 24 s, p < 0.001), took less time to complete the diagnostic tour (2 min 49 s vs. 3 min 32 s, p = 0.027), and had a shorter camera path length (186 vs. 246 cm, p = 0.006). The simulator achieved high scores in terms of realism. It was regarded as a useful training tool, which is also capable of differentiating between varying levels of arthroscopic experience. Nevertheless, further improvements of the simulator especially in the field of therapeutic arthroscopy are desirable. In general, the findings support that virtual-reality-based simulation using passive haptics has the potential to complement conventional training of knee arthroscopy skills. II.

Piloted aircraft simulation concepts and overview

NASA Technical Reports Server (NTRS)

Sinacori, J. B.

1978-01-01

An overview of piloted aircraft simulation is presented that reflects the viewpoint of an aeronautical technologist. The intent is to acquaint potential users with some of the basic concepts and issues that characterize piloted simulation. Application to the development of aircraft are highlighted, but some aspects of training simulators are covered. A historical review is given together with a description of some current simulators. Simulator usages, advantages, and limitations are discussed and human perception qualities important to simulation are related. An assessment of current simulation is presented that addresses validity, fidelity, and deficiencies. Future prospects are discussed and technology projections are made.

Qualitative analysis of pure and adulterated canola oil via SIMCA

NASA Astrophysics Data System (ADS)

Basri, Katrul Nadia; Khir, Mohd Fared Abdul; Rani, Rozina Abdul; Sharif, Zaiton; Rusop, M.; Zoolfakar, Ahmad Sabirin

2018-05-01

This paper demonstrates the utilization of near infrared (NIR) spectroscopy to classify pure and adulterated sample of canola oil. Soft Independent Modeling Class Analogies (SIMCA) algorithm was implemented to discriminate the samples to its classes. Spectral data obtained was divided using Kennard Stone algorithm into training and validation dataset by a fixed ratio of 7:3. The model accuracy obtained based on the model built is 0.99 whereas the sensitivity and precision are 0.92 and 1.00. The result showed the classification model is robust to perform qualitative analysis of canola oil for future application.

14 CFR 91.1041 - Aircraft proving and validation tests.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Aircraft proving and validation tests. 91... Ownership Operations Program Management § 91.1041 Aircraft proving and validation tests. (a) No program... tests. However, pilot flight training may be conducted during the proving tests. (d) Validation testing...

14 CFR 91.1041 - Aircraft proving and validation tests.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Aircraft proving and validation tests. 91... Ownership Operations Program Management § 91.1041 Aircraft proving and validation tests. (a) No program... tests. However, pilot flight training may be conducted during the proving tests. (d) Validation testing...

14 CFR 91.1041 - Aircraft proving and validation tests.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Aircraft proving and validation tests. 91... Ownership Operations Program Management § 91.1041 Aircraft proving and validation tests. (a) No program... tests. However, pilot flight training may be conducted during the proving tests. (d) Validation testing...

14 CFR 91.1041 - Aircraft proving and validation tests.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Aircraft proving and validation tests. 91... Ownership Operations Program Management § 91.1041 Aircraft proving and validation tests. (a) No program... tests. However, pilot flight training may be conducted during the proving tests. (d) Validation testing...

14 CFR 91.1041 - Aircraft proving and validation tests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Aircraft proving and validation tests. 91... Ownership Operations Program Management § 91.1041 Aircraft proving and validation tests. (a) No program... tests. However, pilot flight training may be conducted during the proving tests. (d) Validation testing...

A QSAR Model for Thyroperoxidase Inhibition and Screening ...

EPA Pesticide Factsheets

Thyroid hormones (THs) are critical modulators of a wide range of biological processes from neurodevelopment to metabolism. Well regulated levels of THs are critical during development and even moderate changes in maternal or fetal TH levels produce irreversible neurological deficits in children. The enzyme thyroperoxidase (TPO) plays a key role in the synthesis of THs. Inhibition of TPO by xenobiotics leads to decreased TH synthesis and, depending on the degree of synthesis inhibition, may result in adverse developmental outcomes. Recently, a high-throughput screening assay for TPO inhibition (AUR-TPO) was developed and used to screen the ToxCast Phase I and II chemicals. In the present study, we used the results from the AUR-TPO screening to develop a Quantitative Structure-Activity Relationship (QSAR) model for TPO inhibition in Leadscope®. The training set consisted of 898 discrete organic chemicals: 134 positive and 764 negative for TPO inhibition. A 10 times two-fold 50% cross-validation of the model was performed, yielding a balanced accuracy of 78.7% within its defined applicability domain. More recently, an additional ~800 chemicals from the US EPA Endocrine Disruption Screening Program (EDSP21) were screened using the AUR-TPO assay. This data was used for external validation of the QSAR model, demonstrating a balanced accuracy of 85.7% within its applicability domain. Overall, the cross- and external validations indicate a model with a high predictiv

Application of adaptive boosting to EP-derived multilayer feed-forward neural networks (MLFN) to improve benign/malignant breast cancer classification

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Masters, Timothy D.; Lo, Joseph Y.; McKee, Dan

2001-07-01

A new neural network technology was developed for improving the benign/malignant diagnosis of breast cancer using mammogram findings. A new paradigm, Adaptive Boosting (AB), uses a markedly different theory in solutioning Computational Intelligence (CI) problems. AB, a new machine learning paradigm, focuses on finding weak learning algorithm(s) that initially need to provide slightly better than random performance (i.e., approximately 55%) when processing a mammogram training set. Then, by successive development of additional architectures (using the mammogram training set), the adaptive boosting process improves the performance of the basic Evolutionary Programming derived neural network architectures. The results of these several EP-derived hybrid architectures are then intelligently combined and tested using a similar validation mammogram data set. Optimization focused on improving specificity and positive predictive value at very high sensitivities, where an analysis of the performance of the hybrid would be most meaningful. Using the DUKE mammogram database of 500 biopsy proven samples, on average this hybrid was able to achieve (under statistical 5-fold cross-validation) a specificity of 48.3% and a positive predictive value (PPV) of 51.8% while maintaining 100% sensitivity. At 97% sensitivity, a specificity of 56.6% and a PPV of 55.8% were obtained.

Summative assessment of undergraduates' communication competence in challenging doctor-patient encounters. Evaluation of the Düsseldorf CoMeD-OSCE.

PubMed

Mortsiefer, Achim; Immecke, Janine; Rotthoff, Thomas; Karger, André; Schmelzer, Regine; Raski, Bianca; Schmitten, Jürgen In der; Altiner, Attila; Pentzek, Michael

2014-06-01

To evaluate the summative assessment (OSCE) of a communication training programme for dealing with challenging doctor-patient encounters in the 4th study year. Our OSCE consists of 4 stations (breaking bad news, guilt and shame, aggressive patients, shared decision making), using a 4-item global rating (GR) instrument. We calculated reliability coefficients for different levels, discriminability of single items and interrater reliability. Validity was estimated by gender differences and accordance between GR and a checklist. In a pooled sample of 456 students in 3 OSCEs over 3 terms, total reliability was α=0.64, reliability coefficients for single stations were >0.80, and discriminability in 3 of 4 stations was within the range of 0.4-0.7. Except for one station, interrater reliability was moderate to strong. Reliability on item level was poor and pointed to some problems with the use of the GR. The application of the GR on regular undergraduate medical education shows moderate reliability in need of improvement and some traits of validity. Ongoing development and evaluation is needed with particular regard to the training of the examiners. Our CoMeD-OSCE proved suitable for the summative assessment of communication skills in challenging doctor-patient encounters. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Astrophysical data mining with GPU. A case study: Genetic classification of globular clusters

NASA Astrophysics Data System (ADS)

Cavuoti, S.; Garofalo, M.; Brescia, M.; Paolillo, M.; Pescape', A.; Longo, G.; Ventre, G.

2014-01-01

We present a multi-purpose genetic algorithm, designed and implemented with GPGPU/CUDA parallel computing technology. The model was derived from our CPU serial implementation, named GAME (Genetic Algorithm Model Experiment). It was successfully tested and validated on the detection of candidate Globular Clusters in deep, wide-field, single band HST images. The GPU version of GAME will be made available to the community by integrating it into the web application DAMEWARE (DAta Mining Web Application REsource, http://dame.dsf.unina.it/beta_info.html), a public data mining service specialized on massive astrophysical data. Since genetic algorithms are inherently parallel, the GPGPU computing paradigm leads to a speedup of a factor of 200× in the training phase with respect to the CPU based version.

Relaxation training after stroke: potential to reduce anxiety.

PubMed

Kneebone, Ian; Walker-Samuel, Natalie; Swanston, Jennifer; Otto, Elisabeth

2014-01-01

To consider the feasibility of setting up a relaxation group to treat symptoms of post stroke anxiety in an in-patient post-acute setting; and to explore the effectiveness of relaxation training in reducing self-reported tension. A relaxation group protocol was developed in consultation with a multidisciplinary team and a user group. Over a period of 24 months, 55 stroke patients attended group autogenic relaxation training on a rehabilitation ward. Attendance ranged between one and eleven sessions. Self-reported tension was assessed pre and post relaxation training using the Tension Rating Circles (TRCs). The TRCs identified a significant reduction in self-reported tension from pre to post training, irrespective of the number of sessions attended; z = -3.656, p < 0.001, r = -0.67, for those who attended multiple sessions, z = -2.758, p < 0.01, r = -0.6 for those who attended a single session. The routine use of relaxation techniques in treating anxiety in patients undergoing post-stroke rehabilitation shows potential. Self-reported tension decreased after attendance at relaxation training. The TRCs proved acceptable to group members, but should be validated against standard anxiety measures. Further exploration of the application of relaxation techniques in clinical practice is desirable. Implications for Rehabilitation Anxiety is prevalent after stroke and likely affects rehabilitation outcomes. Relaxation training is a well proven treatment for anxiety in the non-stroke population. A significant within session reduction in tension, a hallmark symptom of anxiety, was evidenced via group relaxation training delivered in a post-acute, in-patient stroke unit setting. Relaxation training a shows promise as a treatment for anxiety after stroke.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images.

PubMed

Mraity, Hussien A A B; England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.

Fluorescence In Situ Hybridization Probe Validation for Clinical Use.

PubMed

Gu, Jun; Smith, Janice L; Dowling, Patricia K

2017-01-01

In this chapter, we provide a systematic overview of the published guidelines and validation procedures for fluorescence in situ hybridization (FISH) probes for clinical diagnostic use. FISH probes-which are classified as molecular probes or analyte-specific reagents (ASRs)-have been extensively used in vitro for both clinical diagnosis and research. Most commercially available FISH probes in the United States are strictly regulated by the U.S. Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), the Centers for Medicare & Medicaid Services (CMS) the Clinical Laboratory Improvement Amendments (CLIA), and the College of American Pathologists (CAP). Although home-brewed FISH probes-defined as probes made in-house or acquired from a source that does not supply them to other laboratories-are not regulated by these agencies, they too must undergo the same individual validation process prior to clinical use as their commercial counterparts. Validation of a FISH probe involves initial validation and ongoing verification of the test system. Initial validation includes assessment of a probe's technical specifications, establishment of its standard operational procedure (SOP), determination of its clinical sensitivity and specificity, development of its cutoff, baseline, and normal reference ranges, gathering of analytics, confirmation of its applicability to a specific research or clinical setting, testing of samples with or without the abnormalities that the probe is meant to detect, staff training, and report building. Ongoing verification of the test system involves testing additional normal and abnormal samples using the same method employed during the initial validation of the probe.

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images

PubMed Central

England, Andrew; Cassidy, Simon; Eachus, Peter; Dominguez, Alejandro; Hogg, Peter

2016-01-01

Objective: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. Methods: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. Results: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). Conclusion: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. Advances in knowledge: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality. PMID:26943836

Comparison between genetic parameters of cheese yield and nutrient recovery or whey loss traits measured from individual model cheese-making methods or predicted from unprocessed bovine milk samples using Fourier-transform infrared spectroscopy.

PubMed

Bittante, G; Ferragina, A; Cipolat-Gotet, C; Cecchinato, A

2014-10-01

Cheese yield is an important technological trait in the dairy industry. The aim of this study was to infer the genetic parameters of some cheese yield-related traits predicted using Fourier-transform infrared (FTIR) spectral analysis and compare the results with those obtained using an individual model cheese-producing procedure. A total of 1,264 model cheeses were produced using 1,500-mL milk samples collected from individual Brown Swiss cows, and individual measurements were taken for 10 traits: 3 cheese yield traits (fresh curd, curd total solids, and curd water as a percent of the weight of the processed milk), 4 milk nutrient recovery traits (fat, protein, total solids, and energy of the curd as a percent of the same nutrient in the processed milk), and 3 daily cheese production traits per cow (fresh curd, total solids, and water weight of the curd). Each unprocessed milk sample was analyzed using a MilkoScan FT6000 (Foss, Hillerød, Denmark) over the spectral range, from 5,000 to 900 wavenumber × cm(-1). The FTIR spectrum-based prediction models for the previously mentioned traits were developed using modified partial least-square regression. Cross-validation of the whole data set yielded coefficients of determination between the predicted and measured values in cross-validation of 0.65 to 0.95 for all traits, except for the recovery of fat (0.41). A 3-fold external validation was also used, in which the available data were partitioned into 2 subsets: a training set (one-third of the herds) and a testing set (two-thirds). The training set was used to develop calibration equations, whereas the testing subsets were used for external validation of the calibration equations and to estimate the heritabilities and genetic correlations of the measured and FTIR-predicted phenotypes. The coefficients of determination between the predicted and measured values in cross-validation results obtained from the training sets were very similar to those obtained from the whole data set, but the coefficient of determination of validation values for the external validation sets were much lower for all traits (0.30 to 0.73), and particularly for fat recovery (0.05 to 0.18), for the training sets compared with the full data set. For each testing subset, the (co)variance components for the measured and FTIR-predicted phenotypes were estimated using bivariate Bayesian analyses and linear models. The intraherd heritabilities for the predicted traits obtained from our internal cross-validation using the whole data set ranged from 0.085 for daily yield of curd solids to 0.576 for protein recovery, and were similar to those obtained from the measured traits (0.079 to 0.586, respectively). The heritabilities estimated from the testing data set used for external validation were more variable but similar (on average) to the corresponding values obtained from the whole data set. Moreover, the genetic correlations between the predicted and measured traits were high in general (0.791 to 0.996), and they were always higher than the corresponding phenotypic correlations (0.383 to 0.995), especially for the external validation subset. In conclusion, we herein report that application of the cross-validation technique to the whole data set tended to overestimate the predictive ability of FTIR spectra, give more precise phenotypic predictions than the calibrations obtained using smaller data sets, and yield genetic correlations similar to those obtained from the measured traits. Collectively, our findings indicate that FTIR predictions have the potential to be used as indicator traits for the rapid and inexpensive selection of dairy populations for improvement of cheese yield, milk nutrient recovery in curd, and daily cheese production per cow. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Digital pathology for the primary diagnosis of breast histopathological specimens: an innovative validation and concordance study on digital pathology validation and training.

PubMed

Williams, Bethany Jill; Hanby, Andrew; Millican-Slater, Rebecca; Nijhawan, Anju; Verghese, Eldo; Treanor, Darren

2018-03-01

To train and individually validate a group of breast pathologists in specialty-specific digital primary diagnosis by using a novel protocol endorsed by the Royal College of Pathologists' new guideline for digital pathology. The protocol allows early exposure to live digital reporting, in a risk-mitigated environment, and focuses on patient safety and professional development. Three specialty breast pathologists completed training in the use of a digital microscopy system, and were exposed to a training set of 20 challenging cases, designed to help them identify personal digital diagnostic pitfalls. Following this, the three pathologists viewed a total of 694 live, entire breast cases. All primary diagnoses were made on digital slides, with immediate glass slide review and reconciliation before final case sign-out. There was complete clinical concordance between the glass and digital impression of the case in 98.8% of cases. Only 1.2% of cases had a clinically significant difference in diagnosis/prognosis on glass and digital slide reads. All pathologists elected to continue using the digital microscope as the standard for breast histopathology specimens, with deferral to glass for a limited number of clinical/histological scenarios as a safety net. Individual training and validation for digital primary diagnosis allows pathologists to develop competence and confidence in their digital diagnostic skills, and aids safe and responsible transition from the light microscope to the digital microscope. © 2017 John Wiley & Sons Ltd.

Gene Expression-Based Survival Prediction in Lung Adenocarcinoma: A Multi-Site, Blinded Validation Study

PubMed Central

Shedden, Kerby; Taylor, Jeremy M.G.; Enkemann, Steve A.; Tsao, Ming S.; Yeatman, Timothy J.; Gerald, William L.; Eschrich, Steve; Jurisica, Igor; Venkatraman, Seshan E.; Meyerson, Matthew; Kuick, Rork; Dobbin, Kevin K.; Lively, Tracy; Jacobson, James W.; Beer, David G.; Giordano, Thomas J.; Misek, David E.; Chang, Andrew C.; Zhu, Chang Qi; Strumpf, Dan; Hanash, Samir; Shepherd, Francis A.; Ding, Kuyue; Seymour, Lesley; Naoki, Katsuhiko; Pennell, Nathan; Weir, Barbara; Verhaak, Roel; Ladd-Acosta, Christine; Golub, Todd; Gruidl, Mike; Szoke, Janos; Zakowski, Maureen; Rusch, Valerie; Kris, Mark; Viale, Agnes; Motoi, Noriko; Travis, William; Sharma, Anupama

2009-01-01

Although prognostic gene expression signatures for survival in early stage lung cancer have been proposed, for clinical application it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) can be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. PMID:18641660

On the relation between personality and job performance of airline pilots.

PubMed

Hormann, H J; Maschke, P

1996-01-01

The validity of a personality questionnaire for the prediction of job success of airline pilots is compared to validities of a simulator checkflight and of flying experience data. During selection, 274 pilots applying for employment with a European charter airline were examined with a multidimensional personality questionnaire (Temperature Structure Scales; TSS). Additionally, the applicants were graded in a simulator checkflight. On the basis of training records, the pilots were classified as performing at standard or below standard after about 3 years of employment in the hiring company. In a multiple-regression model, this dichotomous criterion for job success can be predicted with 73.8% accuracy through the simulator checkflight and flying experience prior to employment. By adding the personality questionnaire to the regression equation, the number of correct classifications increases to 79.3%. On average, successful pilots score substantially higher on interpersonal scales and lower on emotional scales of the TSS.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

Short version of the "instrument for assessment of stress in nursing students" in the Brazilian reality.

PubMed

Costa, Ana Lúcia Siqueira; Silva, Rodrigo Marques da; Mussi, Fernanda Carneiro; Serrano, Patrícia Maria; Graziano, Eliane da Silva; Batista, Karla de Melo

2018-01-08

validate a short version of the Instrument for assessment of stress in nursing students in the Brazilian reality. Methodological study conducted with 1047 nursing students from five Brazilian institutions, who answered the 30 items initially distributed in eight domains. Data were analyzed in the R Statistical Package and in the latent variable analysis, using exploratory and confirmatory factor analyses, Cronbach's alpha and item-total correlation. The short version of the instrument had 19 items distributed into four domains: Environment, Professional Training, Theoretical Activities and Performance of Practical Activities. The confirmatory analysis showed absolute and parsimony fit to the proposed model with satisfactory residual levels. Alpha values ​​per factor ranged from 0.736 (Environment) to 0.842 (Performance of Practical Activities). The short version of the instrument has construct validity and reliability for application to Brazilian nursing undergraduates at any stage of the course.

Development and validation of a mortality risk model for pediatric sepsis.

PubMed

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-05-01

Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial.We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities.According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively.The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients.

Development and validation of a mortality risk model for pediatric sepsis

PubMed Central

Chen, Mengshi; Lu, Xiulan; Hu, Li; Liu, Pingping; Zhao, Wenjiao; Yan, Haipeng; Tang, Liang; Zhu, Yimin; Xiao, Zhenghui; Chen, Lizhang; Tan, Hongzhuan

2017-01-01

Abstract Pediatric sepsis is a burdensome public health problem. Assessing the mortality risk of pediatric sepsis patients, offering effective treatment guidance, and improving prognosis to reduce mortality rates, are crucial. We extracted data derived from electronic medical records of pediatric sepsis patients that were collected during the first 24 hours after admission to the pediatric intensive care unit (PICU) of the Hunan Children's hospital from January 2012 to June 2014. A total of 788 children were randomly divided into a training (592, 75%) and validation group (196, 25%). The risk factors for mortality among these patients were identified by conducting multivariate logistic regression in the training group. Based on the established logistic regression equation, the logit probabilities for all patients (in both groups) were calculated to verify the model's internal and external validities. According to the training group, 6 variables (brain natriuretic peptide, albumin, total bilirubin, D-dimer, lactate levels, and mechanical ventilation in 24 hours) were included in the final logistic regression model. The areas under the curves of the model were 0.854 (0.826, 0.881) and 0.844 (0.816, 0.873) in the training and validation groups, respectively. The Mortality Risk Model for Pediatric Sepsis we established in this study showed acceptable accuracy to predict the mortality risk in pediatric sepsis patients. PMID:28514310

A broad scope knowledge based model for optimization of VMAT in esophageal cancer: validation and assessment of plan quality among different treatment centers.

PubMed

Fogliata, Antonella; Nicolini, Giorgia; Clivio, Alessandro; Vanetti, Eugenio; Laksar, Sarbani; Tozzi, Angelo; Scorsetti, Marta; Cozzi, Luca

2015-10-31

To evaluate the performance of a broad scope model-based optimisation process for volumetric modulated arc therapy applied to esophageal cancer. A set of 70 previously treated patients in two different institutions, were selected to train a model for the prediction of dose-volume constraints. The model was built with a broad-scope purpose, aiming to be effective for different dose prescriptions and tumour localisations. It was validated on three groups of patients from the same institution and from another clinic not providing patients for the training phase. Comparison of the automated plans was done against reference cases given by the clinically accepted plans. Quantitative improvements (statistically significant for the majority of the analysed dose-volume parameters) were observed between the benchmark and the test plans. Of 624 dose-volume objectives assessed for plan evaluation, in 21 cases (3.3 %) the reference plans failed to respect the constraints while the model-based plans succeeded. Only in 3 cases (<0.5 %) the reference plans passed the criteria while the model-based failed. In 5.3 % of the cases both groups of plans failed and in the remaining cases both passed the tests. Plans were optimised using a broad scope knowledge-based model to determine the dose-volume constraints. The results showed dosimetric improvements when compared to the benchmark data. Particularly the plans optimised for patients from the third centre, not participating to the training, resulted in superior quality. The data suggests that the new engine is reliable and could encourage its application to clinical practice.

Development and validation of a high-fidelity phonomicrosurgical trainer.

PubMed

Klein, Adam M; Gross, Jennifer

2017-04-01

To validate the use of a high-fidelity phonomicrosurgical trainer. A high-fidelity phonomicrosurgical trainer, based on a previously validated model by Contag et al., 1 was designed with multilayered vocal folds that more closely mimic the consistency of true vocal folds, containing intracordal lesions to practice phonomicrosurgical removal. A training module was developed to simulate the true phonomicrosurgical experience. A validation study with novice and expert surgeons was conducted. Novices and experts were instructed to remove the lesion from the synthetic vocal folds, and novices were given four training trials. Performances were measured by the amount of time spent and tissue injury (microflap, superficial, deep) to the vocal fold. An independent Student t test and Fisher exact tests were used to compare subjects. A matched-paired t test and Wilcoxon signed rank tests were used to compare novice performance on the first and fourth trials and assess for improvement. Experts completed the excision with less total errors than novices (P = .004) and made less injury to the microflap (P = .05) and superficial tissue (P = .003). Novices improved their performance with training, making less total errors (P = .002) and superficial tissue injuries (P = .02) and spending less time for removal (P = .002) after several practice trials. This high-fidelity phonomicrosurgical trainer has been validated for novice surgeons. It can distinguish between experts and novices; and after training, it helped to improve novice performance. N/A. Laryngoscope, 127:888-893, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

First validation of the PASSPORT training environment for arthroscopic skills.

PubMed

Tuijthof, Gabriëlle J M; van Sterkenburg, Maayke N; Sierevelt, Inger N; van Oldenrijk, Jakob; Van Dijk, C Niek; Kerkhoffs, Gino M M J

2010-02-01

The demand for high quality care is in contrast to reduced training time for residents to develop arthroscopic skills. Thereto, simulators are introduced to train skills away from the operating room. In our clinic, a physical simulation environment to Practice Arthroscopic Surgical Skills for Perfect Operative Real-life Treatment (PASSPORT) is being developed. The PASSPORT concept consists of maintaining the normal arthroscopic equipment, replacing the human knee joint by a phantom, and integrating registration devices to provide performance feedback. The first prototype of the knee phantom allows inspection, treatment of menisci, irrigation, and limb stressing. PASSPORT was evaluated for face and construct validity. Construct validity was assessed by measuring the performance of two groups with different levels of arthroscopic experience (20 surgeons and 8 residents). Participants performed a navigation task five times on PASSPORT. Task times were recorded. Face validity was assessed by completion of a short questionnaire on the participants' impressions and comments for improvements. Construct validity was demonstrated as the surgeons (median task time 19.7 s [8.0-37.6]) were more efficient than the residents (55.2 s [27.9-96.6]) in task completion for each repetition (Mann-Whitney U test, P < 0.05). The prototype of the knee phantom sufficiently imitated limb outer appearance (79%), portal resistance (82%), and arthroscopic view (81%). Improvements are required for the stressing device and the material of cruciate ligaments. Our physical simulation environment (PASSPORT) demonstrates its potential to evolve as a training modality. In future, automated performance feedback is aimed for.

Simulation-based medical education: an ethical imperative.

PubMed

Ziv, Amitai; Wolpe, Paul Root; Small, Stephen D; Glick, Shimon

2006-01-01

Medical training must at some point use live patients to hone the skills of health professionals. But there is also an obligation to provide optimal treatment and to ensure patients' safety and well-being. Balancing these 2 needs represents a fundamental ethical tension in medical education. Simulation-based learning can help mitigate this tension by developing health professionals' knowledge, skills, and attitudes while protecting patients from unnecessary risk. Simulation-based training has been institutionalized in other high-hazard professions, such as aviation, nuclear power, and the military, to maximize training safety and minimize risk. Health care has lagged behind in simulation applications for a number of reasons, including cost, lack of rigorous proof of effect, and resistance to change. Recently, the international patient safety movement and the U.S. federal policy agenda have created a receptive atmosphere for expanding the use of simulators in medical training, stressing the ethical imperative to "first do no harm" in the face of validated, large epidemiological studies describing unacceptable preventable injuries to patients as a result of medical management. Four themes provide a framework for an ethical analysis of simulation-based medical education: best standards of care and training, error management and patient safety, patient autonomy, and social justice and resource allocation. These themes are examined from the perspectives of patients, learners, educators, and society. The use of simulation wherever feasible conveys a critical educational and ethical message to all: patients are to be protected whenever possible and they are not commodities to be used as conveniences of training.

Simulation-based medical education: an ethical imperative.

PubMed

Ziv, Amitai; Wolpe, Paul Root; Small, Stephen D; Glick, Shimon

2003-08-01

Medical training must at some point use live patients to hone the skills of health professionals. But there is also an obligation to provide optimal treatment and to ensure patients' safety and well-being. Balancing these two needs represents a fundamental ethical tension in medical education. Simulation-based learning can help mitigate this tension by developing health professionals' knowledge, skills, and attitudes while protecting patients from unnecessary risk. Simulation-based training has been institutionalized in other high-hazard professions, such as aviation, nuclear power, and the military, to maximize training safety and minimize risk. Health care has lagged behind in simulation applications for a number of reasons, including cost, lack of rigorous proof of effect, and resistance to change. Recently, the international patient safety movement and the U.S. federal policy agenda have created a receptive atmosphere for expanding the use of simulators in medical training, stressing the ethical imperative to "first do no harm" in the face of validated, large epidemiological studies describing unacceptable preventable injuries to patients as a result of medical management. Four themes provide a framework for an ethical analysis of simulation-based medical education: best standards of care and training, error management and patient safety, patient autonomy, and social justice and resource allocation. These themes are examined from the perspectives of patients, learners, educators, and society. The use of simulation wherever feasible conveys a critical educational and ethical message to all: patients are to be protected whenever possible and they are not commodities to be used as conveniences of training.

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

PubMed

Ngo, Tuan Anh; Lu, Zhi; Carneiro, Gustavo

2017-01-01

We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where the visual object of interest presents large shape and appearance variations, but the annotated training set is small, which is the case for various medical image analysis applications, including the one considered in this paper. In particular, level set methods are based on shape and appearance terms that use small training sets, but present limitations for modelling the visual object variations. Deep learning methods can model such variations using relatively small amounts of annotated training, but they often need to be regularised to produce good generalisation. Therefore, the combination of these methods brings together the advantages of both approaches, producing a methodology that needs small training sets and produces accurate segmentation results. We test our methodology on the MICCAI 2009 left ventricle segmentation challenge database (containing 15 sequences for training, 15 for validation and 15 for testing), where our approach achieves the most accurate results in the semi-automated problem and state-of-the-art results for the fully automated challenge. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Determination of the n-octanol/water partition coefficients of weakly ionizable basic compounds by reversed-phase high-performance liquid chromatography with neutral model compounds.

PubMed

Liang, Chao; Han, Shu-ying; Qiao, Jun-qin; Lian, Hong-zhen; Ge, Xin

2014-11-01

A strategy to utilize neutral model compounds for lipophilicity measurement of ionizable basic compounds by reversed-phase high-performance liquid chromatography is proposed in this paper. The applicability of the novel protocol was justified by theoretical derivation. Meanwhile, the linear relationships between logarithm of apparent n-octanol/water partition coefficients (logKow '') and logarithm of retention factors corresponding to the 100% aqueous fraction of mobile phase (logkw ) were established for a basic training set, a neutral training set and a mixed training set of these two. As proved in theory, the good linearity and external validation results indicated that the logKow ''-logkw relationships obtained from a neutral model training set were always reliable regardless of mobile phase pH. Afterwards, the above relationships were adopted to determine the logKow of harmaline, a weakly dissociable alkaloid. As far as we know, this is the first report on experimental logKow data for harmaline (logKow = 2.28 ± 0.08). Introducing neutral compounds into a basic model training set or using neutral model compounds alone is recommended to measure the lipophilicity of weakly ionizable basic compounds especially those with high hydrophobicity for the advantages of more suitable model compound choices and convenient mobile phase pH control. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-guided training for deep brain stimulation planning using objective assessment.

PubMed

Holden, Matthew S; Zhao, Yulong; Haegelen, Claire; Essert, Caroline; Fernandez-Vidal, Sara; Bardinet, Eric; Ungi, Tamas; Fichtinger, Gabor; Jannin, Pierre

2018-04-04

Deep brain stimulation (DBS) is an increasingly common treatment for neurodegenerative diseases. Neurosurgeons must have thorough procedural, anatomical, and functional knowledge to plan electrode trajectories and thus ensure treatment efficacy and patient safety. Developing this knowledge requires extensive training. We propose a training approach with objective assessment of neurosurgeon proficiency in DBS planning. To assess proficiency, we propose analyzing both the viability of the planned trajectory and the manner in which the operator arrived at the trajectory. To improve understanding, we suggest a self-guided training course for DBS planning using real-time feedback. To validate the proposed measures of proficiency and training course, two experts and six novices followed the training course, and we monitored their proficiency measures throughout. At baseline, experts planned higher quality trajectories and did so more efficiently. As novices progressed through the training course, their proficiency measures increased significantly, trending toward expert measures. We developed and validated measures which reliably discriminate proficiency levels. These measures are integrated into a training course, which quantitatively improves trainee performance. The proposed training course can be used to improve trainees' proficiency, and the quantitative measures allow trainees' progress to be monitored.

Initial validation of a virtual-reality robotic simulator.

PubMed

Lendvay, Thomas S; Casale, Pasquale; Sweet, Robert; Peters, Craig

2008-09-01

Robotic surgery is an accepted adjunct to minimally invasive surgery, but training is restricted to console time. Virtual-reality (VR) simulation has been shown to be effective for laparoscopic training and so we seek to validate a novel VR robotic simulator. The American Urological Association (AUA) Office of Education approved this study. Subjects enrolled in a robotics training course at the 2007 AUA annual meeting underwent skills training in a da Vinci dry-lab module and a virtual-reality robotics module which included a three-dimensional (3D) VR robotic simulator. Demographic and acceptability data were obtained, and performance metrics from the simulator were compared between experienced and nonexperienced roboticists for a ring transfer task. Fifteen subjects-four with previous robotic surgery experience and 11 without-participated. Nine subjects were still in urology training and nearly half of the group had reported playing video games. Overall performance of the da Vinci system and the simulator were deemed acceptable by a Likert scale (0-6) rating of 5.23 versus 4.69, respectively. Experienced subjects outperformed nonexperienced subjects on the simulator on three metrics: total task time (96 s versus 159 s, P < 0.02), economy of motion (1,301 mm versus 2,095 mm, P < 0.04), and time the telemanipulators spent outside of the center of the platform's workspace (4 s versus 35 s, P < 0.02). This is the first demonstration of face and construct validity of a virtual-reality robotic simulator. Further studies assessing predictive validity are ultimately required to support incorporation of VR robotic simulation into training curricula.

Development and content validation of the power mobility training tool.

PubMed

Kenyon, Lisa K; Farris, John P; Cain, Brett; King, Emily; VandenBerg, Ashley

2018-01-01

This paper outlines the development and content validation of the power mobility training tool (PMTT), an observational tool designed to assist therapists in developing power mobility training programs for children who have multiple, severe impairments. Initial items on the PMTT were developed based on a literature review and in consultation with therapists experienced in the use of power mobility. Items were trialled in clinical settings, reviewed, and refined. Items were then operationalized and an administration manual detailing scoring for each item was created. Qualitative and quantitative methods were used to establish content validity via a 15 member, international expert panel. The content validity ratio (CVR) was determined for each possible item. Of the 19 original items, 10 achieved minimum required CVR values and were included in the final version of the PMTT. Items related to manoeuvring a power mobility device were merged and an item related to the number of switches used concurrently to operate a power mobility device were added to the PMTT. The PMTT may assist therapists in developing training programs that facilitate the acquisition of beginning power mobility skills in children who have multiple, severe impairments. Implications for Rehabilitation The Power Mobility Training Tool (PMTT) was developed to help guide the development of power mobility intervention programs for children who have multiple, severe impairments. The PMTT can be used with children who access a power mobility device using either a joystick or a switch. Therapists who have limited experience with power mobility may find the PMTT to be helpful in setting up and conducting power mobility training interventions as a feasible aspect of a plan of care for children who have multiple, severe impairments.

A novel augmented reality simulator for skills assessment in minimal invasive surgery.

PubMed

Lahanas, Vasileios; Loukas, Constantinos; Smailis, Nikolaos; Georgiou, Evangelos

2015-08-01

Over the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills. The components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system. Between-group comparison demonstrated highly significant differences (<0.01) in all performance metrics and tasks denoting the simulator's construct validity. Qualitative analysis on the instruments' trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects' ratings on the feedback questionnaire highlighted the face-validity of the training system. The results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training.

Does rational selection of training and test sets improve the outcome of QSAR modeling?

PubMed

Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

2012-10-22

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

An Effective Antifreeze Protein Predictor with Ensemble Classifiers and Comprehensive Sequence Descriptors.

PubMed

Yang, Runtao; Zhang, Chengjin; Gao, Rui; Zhang, Lina

2015-09-07

Antifreeze proteins (AFPs) play a pivotal role in the antifreeze effect of overwintering organisms. They have a wide range of applications in numerous fields, such as improving the production of crops and the quality of frozen foods. Accurate identification of AFPs may provide important clues to decipher the underlying mechanisms of AFPs in ice-binding and to facilitate the selection of the most appropriate AFPs for several applications. Based on an ensemble learning technique, this study proposes an AFP identification system called AFP-Ensemble. In this system, random forest classifiers are trained by different training subsets and then aggregated into a consensus classifier by majority voting. The resulting predictor yields a sensitivity of 0.892, a specificity of 0.940, an accuracy of 0.938 and a balanced accuracy of 0.916 on an independent dataset, which are far better than the results obtained by previous methods. These results reveal that AFP-Ensemble is an effective and promising predictor for large-scale determination of AFPs. The detailed feature analysis in this study may give useful insights into the molecular mechanisms of AFP-ice interactions and provide guidance for the related experimental validation. A web server has been designed to implement the proposed method.

Can smartwatches replace smartphones for posture tracking?

PubMed

Mortazavi, Bobak; Nemati, Ebrahim; VanderWall, Kristina; Flores-Rodriguez, Hector G; Cai, Jun Yu Jacinta; Lucier, Jessica; Naeim, Arash; Sarrafzadeh, Majid

2015-10-22

This paper introduces a human posture tracking platform to identify the human postures of sitting, standing or lying down, based on a smartwatch. This work develops such a system as a proof-of-concept study to investigate a smartwatch's ability to be used in future remote health monitoring systems and applications. This work validates the smartwatches' ability to track the posture of users accurately in a laboratory setting while reducing the sampling rate to potentially improve battery life, the first steps in verifying that such a system would work in future clinical settings. The algorithm developed classifies the transitions between three posture states of sitting, standing and lying down, by identifying these transition movements, as well as other movements that might be mistaken for these transitions. The system is trained and developed on a Samsung Galaxy Gear smartwatch, and the algorithm was validated through a leave-one-subject-out cross-validation of 20 subjects. The system can identify the appropriate transitions at only 10 Hz with an F-score of 0.930, indicating its ability to effectively replace smart phones, if needed.

Alzheimer's Disease Diagnosis in Individual Subjects using Structural MR Images: Validation Studies

PubMed Central

Vemuri, Prashanthi; Gunter, Jeffrey L.; Senjem, Matthew L.; Whitwell, Jennifer L.; Kantarci, Kejal; Knopman, David S.; Boeve, Bradley F.; Petersen, Ronald C.; Jack, Clifford R.

2008-01-01

OBJECTIVE To develop and validate a tool for Alzheimer's disease (AD) diagnosis in individual subjects using support vector machine (SVM) based classification of structural MR (sMR) images. BACKGROUND Libraries of sMR scans of clinically well characterized subjects can be harnessed for the purpose of diagnosing new incoming subjects. METHODS 190 patients with probable AD were age- and gender-matched with 190 cognitively normal (CN) subjects. Three different classification models were implemented: Model I uses tissue densities obtained from sMR scans to give STructural Abnormality iNDex (STAND)-score; and Models II and III use tissue densities as well as covariates (demographics and Apolipoprotein E genotype) to give adjusted-STAND (aSTAND)-score. Data from 140 AD and 140 CN were used for training. The SVM parameter optimization and training was done by four-fold cross validation. The remaining independent sample of 50 AD and 50 CN were used to obtain a minimally biased estimate of the generalization error of the algorithm. RESULTS The CV accuracy of Model II and Model III aSTAND-scores was 88.5% and 89.3% respectively and the developed models generalized well on the independent test datasets. Anatomic patterns best differentiating the groups were consistent with the known distribution of neurofibrillary AD pathology. CONCLUSIONS This paper presents preliminary evidence that application of SVM-based classification of an individual sMR scan relative to a library of scans can provide useful information in individual subjects for diagnosis of AD. Including demographic and genetic information in the classification algorithm slightly improves diagnostic accuracy. PMID:18054253

Training Culture: A New Conceptualization to Capture Values and Meanings of Training in Organizations

ERIC Educational Resources Information Center

Polo, Federica; Cervai, Sara; Kantola, Jussi

2018-01-01

Purpose: The purpose of this study is to introduce and validate the concept of training culture defined as a subset of the main organizational culture that allows examining meanings and values attributed to the training within an organization by management and employees. Design/methodology/approach: This study, following the deductive scale…

A Job Corps Study of Relative Cost Benefits, Volume I and II.

ERIC Educational Resources Information Center

Software Systems, Inc., Washington, DC.

This study was undertaken to relate Job Corps training outcomes to the costs of training, in terms of human talent, time, and material resources. Training outcomes or benefits were classified according to Job Corps objectives, then compared to total costs incurred by both training center and enrollee. Empirical validation and other evaluation of…

The Influence of Transfer System Factors and Training Elapsed Time on Transfer in a Healthcare Organization

ERIC Educational Resources Information Center

Mihalko, Beverly J.

2010-01-01

Organizations and other sponsors of training face increasing pressure to demonstrate the value or impact of their training programs on individual and organizational performance. A critical element in the validation of training effectiveness is the permanent transfer of learned knowledge, skills, and behaviors to the workplace. The generalization…

Teaching and assessing procedural skills using simulation: metrics and methodology.

PubMed

Lammers, Richard L; Davenport, Moira; Korley, Frederick; Griswold-Theodorson, Sharon; Fitch, Michael T; Narang, Aneesh T; Evans, Leigh V; Gross, Amy; Rodriguez, Elliot; Dodge, Kelly L; Hamann, Cara J; Robey, Walter C

2008-11-01

Simulation allows educators to develop learner-focused training and outcomes-based assessments. However, the effectiveness and validity of simulation-based training in emergency medicine (EM) requires further investigation. Teaching and testing technical skills require methods and assessment instruments that are somewhat different than those used for cognitive or team skills. Drawing from work published by other medical disciplines as well as educational, behavioral, and human factors research, the authors developed six research themes: measurement of procedural skills; development of performance standards; assessment and validation of training methods, simulator models, and assessment tools; optimization of training methods; transfer of skills learned on simulator models to patients; and prevention of skill decay over time. The article reviews relevant and established educational research methodologies and identifies gaps in our knowledge of how physicians learn procedures. The authors present questions requiring further research that, once answered, will advance understanding of simulation-based procedural training and assessment in EM.

Play to become a surgeon: impact of Nintendo Wii training on laparoscopic skills.

PubMed

Giannotti, Domenico; Patrizi, Gregorio; Di Rocco, Giorgio; Vestri, Anna Rita; Semproni, Camilla Proietti; Fiengo, Leslie; Pontone, Stefano; Palazzini, Giorgio; Redler, Adriano

2013-01-01

Video-games have become an integral part of the new multimedia culture. Several studies assessed video-gaming enhancement of spatial attention and eye-hand coordination. Considering the technical difficulty of laparoscopic procedures, legal issues and time limitations, the validation of appropriate training even outside of the operating rooms is ongoing. We investigated the influence of a four-week structured Nintendo® Wii™ training on laparoscopic skills by analyzing performance metrics with a validated simulator (Lap Mentor™, Simbionix™). We performed a prospective randomized study on 42 post-graduate I-II year residents in General, Vascular and Endoscopic Surgery. All participants were tested on a validated laparoscopic simulator and then randomized to group 1 (Controls, no training with the Nintendo® Wii™), and group 2 (training with the Nintendo® Wii™) with 21 subjects in each group, according to a computer-generated list. After four weeks, all residents underwent a testing session on the laparoscopic simulator of the same tasks as in the first session. All 42 subjects in both groups improved significantly from session 1 to session 2. Compared to controls, the Wii group showed a significant improvement in performance (p<0.05) for 13 of the 16 considered performance metrics. The Nintendo® Wii™ might be helpful, inexpensive and entertaining part of the training of young laparoscopists, in addition to a standard surgical education based on simulators and the operating room.

Predicting emergency coronary artery bypass graft following PCI: application of a computational model to refer patients to hospitals with and without onsite surgical backup

PubMed Central

Syed, Zeeshan; Moscucci, Mauro; Share, David; Gurm, Hitinder S

2015-01-01

Background Clinical tools to stratify patients for emergency coronary artery bypass graft (ECABG) after percutaneous coronary intervention (PCI) create the opportunity to selectively assign patients undergoing procedures to hospitals with and without onsite surgical facilities for dealing with potential complications while balancing load across providers. The goal of our study was to investigate the feasibility of a computational model directly optimised for cohort-level performance to predict ECABG in PCI patients for this application. Methods Blue Cross Blue Shield of Michigan Cardiovascular Consortium registry data with 69 pre-procedural and angiographic risk variables from 68 022 PCI procedures in 2004–2007 were used to develop a support vector machine (SVM) model for ECABG. The SVM model was optimised for the area under the receiver operating characteristic curve (AUROC) at the level of the training cohort and validated on 42 310 PCI procedures performed in 2008–2009. Results There were 87 cases of ECABG (0.21%) in the validation cohort. The SVM model achieved an AUROC of 0.81 (95% CI 0.76 to 0.86). Patients in the predicted top decile were at a significantly increased risk relative to the remaining patients (OR 9.74, 95% CI 6.39 to 14.85, p<0.001) for ECABG. The SVM model optimised for the AUROC on the training cohort significantly improved discrimination, net reclassification and calibration over logistic regression and traditional SVM classification optimised for univariate performance. Conclusions Computational risk stratification directly optimising cohort-level performance holds the potential of high levels of discrimination for ECABG following PCI. This approach has value in selectively referring PCI patients to hospitals with and without onsite surgery. PMID:26688738

Square pegs in round holes: has psychometric testing a place in choosing a surgical career? A preliminary report of work in progress.

PubMed Central

Gilligan, J. H.; Welsh, F. K.; Watts, C.; Treasure, T.

1999-01-01

Methods of selection of candidates for training in surgery has long been regarded as lacking explicit criteria and objectivity. Our purpose was to discover the aptitudes and personality types of applicants for surgical posts at the outset, in order to discover which were most likely to result in a satisfactory progression through training and which were associated with career difficulties. This longitudinal predictive validation study has been undertaken in a London Teaching Hospital since 1994. After short-listing, but immediately before interview, all candidates for senior house officer posts in basic surgical training and in geriatric medicine were asked to undertake psychometric tests of numerical (GMA) and spatial (SIT7) reasoning, personality type (MBTI), and self-rating of competency. There were no differences in ability scores between surgeons or geriatricians. Personality differences were revealed between the surgeons and the geriatricians, and between male and female surgeons. This study suggests that while there are no differences in ability between surgeons and geriatricians at the start of training, there are differences in personality. Long-term follow-up of the career development of this cohort of surgical SHOs is required to determine whether the psychometric measures described correlate with achievements of milestones in their surgical careers. PMID:10364959

Development of a Neural Network Simulator for Studying the Constitutive Behavior of Structural Composite Materials

DOE PAGES

Na, Hyuntae; Lee, Seung-Yub; Üstündag, Ersan; ...

2013-01-01

This paper introduces a recent development and application of a noncommercial artificial neural network (ANN) simulator with graphical user interface (GUI) to assist in rapid data modeling and analysis in the engineering diffraction field. The real-time network training/simulation monitoring tool has been customized for the study of constitutive behavior of engineering materials, and it has improved data mining and forecasting capabilities of neural networks. This software has been used to train and simulate the finite element modeling (FEM) data for a fiber composite system, both forward and inverse. The forward neural network simulation precisely reduplicates FEM results several orders ofmore » magnitude faster than the slow original FEM. The inverse simulation is more challenging; yet, material parameters can be meaningfully determined with the aid of parameter sensitivity information. The simulator GUI also reveals that output node size for materials parameter and input normalization method for strain data are critical train conditions in inverse network. The successful use of ANN modeling and simulator GUI has been validated through engineering neutron diffraction experimental data by determining constitutive laws of the real fiber composite materials via a mathematically rigorous and physically meaningful parameter search process, once the networks are successfully trained from the FEM database.« less

Applications of neural networks in training science.

PubMed

Pfeiffer, Mark; Hohmann, Andreas

2012-04-01

Training science views itself as an integrated and applied science, developing practical measures founded on scientific method. Therefore, it demands consideration of a wide spectrum of approaches and methods. Especially in the field of competitive sports, research questions are usually located in complex environments, so that mainly field studies are drawn upon to obtain broad external validity. Here, the interrelations between different variables or variable sets are mostly of a nonlinear character. In these cases, methods like neural networks, e.g., the pattern recognizing methods of Self-Organizing Kohonen Feature Maps or similar instruments to identify interactions might be successfully applied to analyze data. Following on from a classification of data analysis methods in training-science research, the aim of the contribution is to give examples of varied sports in which network approaches can be effectually used in training science. First, two examples are given in which neural networks are employed for pattern recognition. While one investigation deals with the detection of sporting talent in swimming, the other is located in game sports research, identifying tactical patterns in team handball. The third and last example shows how an artificial neural network can be used to predict competitive performance in swimming. Copyright © 2011 Elsevier B.V. All rights reserved.

Quantitative thickness prediction of tectonically deformed coal using Extreme Learning Machine and Principal Component Analysis: a case study

NASA Astrophysics Data System (ADS)

Wang, Xin; Li, Yan; Chen, Tongjun; Yan, Qiuyan; Ma, Li

2017-04-01

The thickness of tectonically deformed coal (TDC) has positive correlation associations with gas outbursts. In order to predict the TDC thickness of coal beds, we propose a new quantitative predicting method using an extreme learning machine (ELM) algorithm, a principal component analysis (PCA) algorithm, and seismic attributes. At first, we build an ELM prediction model using the PCA attributes of a synthetic seismic section. The results suggest that the ELM model can produce a reliable and accurate prediction of the TDC thickness for synthetic data, preferring Sigmoid activation function and 20 hidden nodes. Then, we analyze the applicability of the ELM model on the thickness prediction of the TDC with real application data. Through the cross validation of near-well traces, the results suggest that the ELM model can produce a reliable and accurate prediction of the TDC. After that, we use 250 near-well traces from 10 wells to build an ELM predicting model and use the model to forecast the TDC thickness of the No. 15 coal in the study area using the PCA attributes as the inputs. Comparing the predicted results, it is noted that the trained ELM model with two selected PCA attributes yields better predication results than those from the other combinations of the attributes. Finally, the trained ELM model with real seismic data have a different number of hidden nodes (10) than the trained ELM model with synthetic seismic data. In summary, it is feasible to use an ELM model to predict the TDC thickness using the calculated PCA attributes as the inputs. However, the input attributes, the activation function and the number of hidden nodes in the ELM model should be selected and tested carefully based on individual application.

Formalizing procedures for operations automation, operator training and spacecraft autonomy

NASA Technical Reports Server (NTRS)

Lecouat, Francois; Desaintvincent, Arnaud

1994-01-01

The generation and validation of operations procedures is a key task of mission preparation that is quite complex and costly. This has motivated the development of software applications providing support for procedures preparation. Several applications have been developed at MATRA MARCONI SPACE (MMS) over the last five years. They are presented in the first section of this paper. The main idea is that if procedures are represented in a formal language, they can be managed more easily with a computer tool and some automatic verifications can be performed. One difficulty is to define a formal language that is easy to use for operators and operations engineers. From the experience of the various procedures management tools developed in the last five years (including the POM, EOA, and CSS projects), MMS has derived OPSMAKER, a generic tool for procedure elaboration and validation. It has been applied to quite different types of missions, ranging from crew procedures (PREVISE system), ground control centers management procedures (PROCSU system), and - most relevant to the present paper - satellite operation procedures (PROCSAT developed for CNES, to support the preparation and verification of SPOT 4 operation procedures, and OPSAT for MMS telecom satellites operation procedures).

Nontechnical skill training and the use of scenarios in modern surgical education.

PubMed

Brunckhorst, Oliver; Khan, Muhammad S; Dasgupta, Prokar; Ahmed, Kamran

2017-07-01

Nontechnical skills are being increasingly recognized as a core reason of surgical errors. Combined with the changing nature of surgical training, there has therefore been an increase in nontechnical skill research in the literature. This review therefore aims to: define nontechnical skillsets, assess current training methods, explore assessment modalities and suggest future research aims. The literature demonstrates an increasing understanding of the components of nontechnical skills within surgery. This has led to a greater availability of validated training methods for its training, including the use of didactic teaching, e-learning and simulation-based scenarios. In addition, there are now various extensively validated assessment tools for nontechnical skills including NOTSS, the Oxford NOTECHS and OTAS. Finally, there is now more focus on the development of tools which target individual nontechnical skill components and an attempt to understand which of these play a greater role in specific procedures such as laparoscopic or robotic surgery. Current evidence demonstrates various training methods and tools for the training of nontechnical skills. Future research is likely to focus increasingly on individual nontechnical skill components and procedure-specific skills.

Development and validation of a new assessment tool for suturing skills in medical students.

PubMed

Sundhagen, Henriette Pisani; Almeland, Stian Kreken; Hansson, Emma

2018-01-01

In recent years, emphasis has been put on that medical student should demonstrate pre-practice/pre-registration core procedural skills to ensure patient safety. Nonetheless, the formal teaching and training of basic suturing skills to medical students have received relatively little attention and there is no standard for what should be tested and how. The aim of this study was to develop and validate, using scientific methods, a tool for assessment of medical students' suturing skills, measuring both micro- and macrosurgical qualities. A tool was constructed and content, construct, concurrent validity, and inter-rater, inter-item, inter-test reliability were tested. Three groups were included: students with no training in suturing skills, students who have had training, plastic surgery. The results show promising reliability and validity when assessing novice medical students' suturing skills. Further studies are needed on implementation of the instrument. Moreover, how the instrument can be used to give formative feedback, evaluate if a required standard is met and for curriculum development needs further investigation.Level of Evidence: Not ratable.

Using the Training Reactions Questionnaire to Analyze the Reactions of University Students Undergoing Career-Related Training in Jordan: A Prospective Human Resource Development Approach

ERIC Educational Resources Information Center

Khasawneh, Samer; Al-Zawahreh, Abdelghafour

2015-01-01

The primary purpose of the present study was to validate Morgan and Casper's training reactions questionnaire (TRQ) for use in Jordan. The study also investigated the reactions of university students to career-related training programs. Another purpose of the study was to determine the impact of certain aspects of training programs on the overall…

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

NASA Technical Reports Server (NTRS)

Hyde, Patricia R.; Loftin, R. Bowen

1993-01-01

The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications.

Can Driving-Simulator Training Enhance Visual Attention, Cognition, and Physical Functioning in Older Adults?

PubMed

Haeger, Mathias; Bock, Otmar; Memmert, Daniel; Hüttermann, Stefanie

2018-01-01

Virtual reality offers a good possibility for the implementation of real-life tasks in a laboratory-based training or testing scenario. Thus, a computerized training in a driving simulator offers an ecological valid training approach. Visual attention had an influence on driving performance, so we used the reverse approach to test the influence of a driving training on visual attention and executive functions. Thirty-seven healthy older participants (mean age: 71.46 ± 4.09; gender: 17 men and 20 women) took part in our controlled experimental study. We examined transfer effects from a four-week driving training (three times per week) on visual attention, executive function, and motor skill. Effects were analyzed using an analysis of variance with repeated measurements. Therefore, main factors were group and time to show training-related benefits of our intervention. Results revealed improvements for the intervention group in divided visual attention; however, there were benefits neither in the other cognitive domains nor in the additional motor task. Thus, there are no broad training-induced transfer effects from such an ecologically valid training regime. This lack of findings could be addressed to insufficient training intensities or a participant-induced bias following the cancelled randomization process.

Optimization study on multiple train formation scheme of urban rail transit

NASA Astrophysics Data System (ADS)

Xia, Xiaomei; Ding, Yong; Wen, Xin

2018-05-01

The new organization method, represented by the mixed operation of multi-marshalling trains, can adapt to the characteristics of the uneven distribution of passenger flow, but the research on this aspect is still not perfect enough. This paper introduced the passenger sharing rate and congestion penalty coefficient with different train formations. On this basis, this paper established an optimization model with the minimum passenger cost and operation cost as objective, and operation frequency and passenger demand as constraint. The ideal point method is used to solve this model. Compared with the fixed marshalling operation model, the overall cost of this scheme saves 9.24% and 4.43% respectively. This result not only validates the validity of the model, but also illustrate the advantages of the multiple train formations scheme.

3D active shape models of human brain structures: application to patient-specific mesh generation

NASA Astrophysics Data System (ADS)

Ravikumar, Nishant; Castro-Mateos, Isaac; Pozo, Jose M.; Frangi, Alejandro F.; Taylor, Zeike A.

2015-03-01

The use of biomechanics-based numerical simulations has attracted growing interest in recent years for computer-aided diagnosis and treatment planning. With this in mind, a method for automatic mesh generation of brain structures of interest, using statistical models of shape (SSM) and appearance (SAM), for personalised computational modelling is presented. SSMs are constructed as point distribution models (PDMs) while SAMs are trained using intensity profiles sampled from a training set of T1-weighted magnetic resonance images. The brain structures of interest are, the cortical surface (cerebrum, cerebellum & brainstem), lateral ventricles and falx-cerebri membrane. Two methods for establishing correspondences across the training set of shapes are investigated and compared (based on SSM quality): the Coherent Point Drift (CPD) point-set registration method and B-spline mesh-to-mesh registration method. The MNI-305 (Montreal Neurological Institute) average brain atlas is used to generate the template mesh, which is deformed and registered to each training case, to establish correspondence over the training set of shapes. 18 healthy patients' T1-weightedMRimages form the training set used to generate the SSM and SAM. Both model-training and model-fitting are performed over multiple brain structures simultaneously. Compactness and generalisation errors of the BSpline-SSM and CPD-SSM are evaluated and used to quantitatively compare the SSMs. Leave-one-out cross validation is used to evaluate SSM quality in terms of these measures. The mesh-based SSM is found to generalise better and is more compact, relative to the CPD-based SSM. Quality of the best-fit model instance from the trained SSMs, to test cases are evaluated using the Hausdorff distance (HD) and mean absolute surface distance (MASD) metrics.

14 CFR Appendix B to Part 63 - Flight Navigator Training Course Requirements

Code of Federal Regulations, 2010 CFR

2010-01-01

... include additional subjects in the ground training curriculum, such as international law, flight hygiene... weather reports. Forecasting. International Morse code: Ability to receive code groups of letters and... school subjects. (3) Each instructor who conducts flight training must hold a valid flight navigator...

Sensitivity Training: Relevance for Social Work Education.

ERIC Educational Resources Information Center

Papell, Catherine P.

The author explores the validity of sensitivity training for professional social work education with its inherent concern for the relation between experiential and theoretical learning. The various streams in the sensitivity training movement are surveyed and the laboratory concept identified as particularly relevant. A human relations laboratory,…

Does training novices to criteria and does rapid acquisition of skills on laparoscopic simulators have predictive validity or are we just playing video games?

PubMed

Hogle, Nancy J; Widmann, Warren D; Ude, Aku O; Hardy, Mark A; Fowler, Dennis L

2008-01-01

To determine whether LapSim training (version 3.0; Surgical Science Ltd, Göteborg, Sweden) to criteria for novice PGY1 surgical residents had predictive validity for improvement in the performance of laparoscopic cholecystectomy. In all, 21 PGY1 residents performed laparoscopic cholecystectomies in pigs after minimal training; their performance was evaluated by skilled laparoscopic surgeons using the validated tool GOALS (global operative assessment of laparoscopic operative skills: depth perception, bimanual dexterity, efficiency, tissue handling, and overall competence). From the group, 10 residents trained to competency on the LapSim Basic Skills Programs (camera navigation, instrument navigation, coordination, grasping, lifting and grasping, cutting, and clip applying). All 21 PGY1 residents again performed laparoscopic cholecystectomies on pigs; their performance was again evaluated by skilled laparoscopic surgeons using GOALS. Additionally, we studied the rate of learning to determine whether the slow or fast learners on the LapSim performed equivalently when performing actual cholecystectomies in pigs. Finally, 6 categorical residents were tracked, and their clinical performance on all of the laparoscopic cholecystectomies in which they were "surgeon, junior" was prospectively evaluated using the GOALS criteria. We found a statistical improvement of depth perception in the operative performance of cholecystectomies in pigs in the group trained on the LapSim. In the other 4 domains, a trend toward improvement was observed. No correlation between being a fast learner and the ultimate skill was demonstrated in the clinical performance of laparoscopic cholecystectomies. We did find that the fast learners on LapSim all were past or current video game players ("gamers"); however, that background did not translate into better clinical performance. Using current criteria, we doubt that the time and effort spent training novice PGY1 Surgical Residents on the basic LapSim training programs is justified, as such training to competence lacks predictive validity in most domains of the GOALS program. We are investigating 2 other approaches: more difficult training exercises using the LapSim system and an entirely different approach using haptic technology (ProMis; Haptica Ltd., Ireland), which uses real instruments, with training on realistic 3-dimensional models with real rather than simulated cutting, sewing, and dissection. Although experienced video gamers achieve competency faster than nongamers on LapSim programs, that skill set does not translate into improved clinical performance.

Validation of Robotic Surgery Simulator (RoSS).

PubMed

Kesavadas, Thenkurussi; Stegemann, Andrew; Sathyaseelan, Gughan; Chowriappa, Ashirwad; Srimathveeravalli, Govindarajan; Seixas-Mikelus, Stéfanie; Chandrasekhar, Rameella; Wilding, Gregory; Guru, Khurshid

2011-01-01

Recent growth of daVinci Robotic Surgical System as a minimally invasive surgery tool has led to a call for better training of future surgeons. In this paper, a new virtual reality simulator, called RoSS is presented. Initial results from two studies - face and content validity, are very encouraging. 90% of the cohort of expert robotic surgeons felt that the simulator was excellent or somewhat close to the touch and feel of the daVinci console. Content validity of the simulator received 90% approval in some cases. These studies demonstrate that RoSS has the potential of becoming an important training tool for the daVinci surgical robot.

Validation of a Full-Immersion Simulation Platform for Percutaneous Nephrolithotomy Using Three-Dimensional Printing Technology.

PubMed

Ghazi, Ahmed; Campbell, Timothy; Melnyk, Rachel; Feng, Changyong; Andrusco, Alex; Stone, Jonathan; Erturk, Erdal

2017-12-01

The restriction of resident hours with an increasing focus on patient safety and a reduced caseload has impacted surgical training. A complex and complication prone procedure such as percutaneous nephrolithotomy (PCNL) with a steep learning curve may create an unsafe environment for hands-on resident training. In this study, we validate a high fidelity, inanimate PCNL model within a full-immersion simulation environment. Anatomically correct models of the human pelvicaliceal system, kidney, and relevant adjacent structures were created using polyvinyl alcohol hydrogels and three-dimensional-printed injection molds. All steps of a PCNL were simulated including percutaneous renal access, nephroscopy, and lithotripsy. Five experts (>100 caseload) and 10 novices (<20 caseload) from both urology (full procedure) and interventional radiology (access only) departments completed the simulation. Face and content validity were calculated using model ratings for similarity to the real procedure and usefulness as a training tool. Differences in performance among groups with various levels of experience using clinically relevant procedural metrics were used to calculate construct validity. The model was determined to have an excellent face and content validity with an average score of 4.5/5.0 and 4.6/5.0, respectively. There were significant differences between novice and expert operative metrics including mean fluoroscopy time, the number of percutaneous access attempts, and number of times the needle was repositioned. Experts achieved better stone clearance with fewer procedural complications. We demonstrated the face, content, and construct validity of an inanimate, full task trainer for PCNL. Construct validity between experts and novices was demonstrated using incorporated procedural metrics, which permitted the accurate assessment of performance. While hands-on training under supervision remains an integral part of any residency, this full-immersion simulation provides a comprehensive tool for surgical skills development and evaluation before hands-on exposure.

Application of a deep-learning method to the forecast of daily solar flare occurrence using Convolution Neural Network

NASA Astrophysics Data System (ADS)

Shin, Seulki; Moon, Yong-Jae; Chu, Hyoungseok

2017-08-01

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT 195Å, and 304Å from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the overfitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). Our model can immediately be applied to automatic forecasting service when image data are available.

A Surgical Virtual Reality Simulator Distinguishes Between Expert Gynecologic Laparoscopic Surgeons and Perinatologists

PubMed Central

von Dadelszen, Peter; Allaire, Catherine

2011-01-01

Background: Concern regarding the quality of surgical training in obstetrics and gynecology residency programs is focusing attention on competency based education. Because open surgical skills cannot necessarily be translated into laparoscopic skills and with minimally invasive surgery becoming standard in operative gynecology, the discrepancy in training between obstetrics and gynecology will widen. Training on surgical simulators with virtual reality may improve surgical skills. However, before incorporation into training programs for gynecology residents the validity of such instruments needs to first be established. We sought to prove the construct validity of a virtual reality laparoscopic simulator, the SurgicalSimTM, by showing its ability to distinguish between surgeons with different laparoscopic experience. Methods: Eleven gynecologic surgeons (experts) and 11 perinatologists (controls) completed 3 tasks on the simulator, and 10 performance parameters were compared. Results: The experts performed faster, more efficiently, and with fewer errors, proving the construct validity of the SurgicalSim. Conclusions: Laparoscopic virtual reality simulators can measure relevant surgical skills and so distinguish between subjects having different skill levels. Hence, these simulators could be integrated into gynecology resident endoscopic training and utilized for objective assessment. Second, the skills required for competency in obstetrics cannot necessarily be utilized for better performance in laparoscopic gynecology. PMID:21985726

Can Findings from Randomized Controlled Trials of Social Skills Training in Autism Spectrum Disorder Be Generalized? The Neglected Dimension of External Validity

ERIC Educational Resources Information Center

Jonsson, Ulf; Olsson, Nora Choque; Bölte, Sven

2016-01-01

Systematic reviews have traditionally focused on internal validity, while external validity often has been overlooked. In this study, we systematically reviewed determinants of external validity in the accumulated randomized controlled trials of social skills group interventions for children and adolescents with autism spectrum disorder. We…

City and County Solar PV Training Program, Module 3: Detailed Site Evaluation, Project Validation, and Permitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Day, Megan H; Lisell, Lars J

This is the third of five training modules recorded for the City and County Solar PV Training Program. The program is focused on training local government staff in the PV procurement process. This module focuses on siting and permitting for both rooftop and larger, ground-mounted systems rand includes a link to a video.

A Model Pilot Program for Training Personnel to Develop Solutions to Major Educational Problems. Final Report.

ERIC Educational Resources Information Center

Cullinan, Paul A.; Merrifield, Philip R.

This document is the final report of the Model Educational Research Training (MERT) program, a graduate program of the New York University School of Education. MERT trains urban school staff in skills necessary to identify problems, design valid research projects, and apply research results. The long-term objective is the training of small groups…

Gradual training of alpacas to the confinement of metabolism pens reduces stress when normal excretion behavior is accommodated.

PubMed

Lund, Kirrin E; Maloney, Shane K; Milton, John T B; Blache, Dominique

2012-01-01

Confinement in metabolism pens may provoke a stress response in alpacas that will reduce the welfare of the animal and jeopardize the validity of scientific results obtained in such pens. In this study, we tested a protocol designed to successfully train alpacas to be held in a specially designed metabolism pen so that the animals' confinement would not jeopardize their welfare. We hypothesized that the alpacas would show fewer behaviors associated with a response to stress as training gradually progressed, and that they would adapt to being in the confinement of the metabolism pen. The training protocol was successful at introducing alpacas to the metabolism pens, and it did reduce the incidence of behavioral responses to stress as the training progressed. The success of the training protocol may be attributed to the progressive nature of the training, the tailoring of the protocol to suit alpacas, and the use of positive reinforcement. This study demonstrated that both animal welfare and the validity of the scientific outcomes could be maximized by the gradual training of experimental animals, thereby minimizing the stress imposed on the animals during experimental procedures.

Maximising harm reduction in early specialty training for general practice: validation of a safety checklist

PubMed Central

2012-01-01

Background Making health care safer is a key policy priority worldwide. In specialty training, medical educators may unintentionally impact on patient safety e.g. through failures of supervision; providing limited feedback on performance; and letting poorly developed behaviours continue unchecked. Doctors-in-training are also known to be susceptible to medical error. Ensuring that all essential educational issues are addressed during training is problematic given the scale of the tasks to be undertaken. Human error and the reliability of local systems may increase the risk of safety-critical topics being inadequately covered. However adherence to a checklist reminder may improve the reliability of task delivery and maximise harm reduction. We aimed to prioritise the most safety-critical issues to be addressed in the first 12-weeks of specialty training in the general practice environment and validate a related checklist reminder. Methods We used mixed methods with different groups of GP educators (n = 127) and specialty trainees (n = 9) in two Scottish regions to prioritise, develop and validate checklist content. Generation and refinement of checklist themes and items were undertaken on an iterative basis using a range of methods including small group work in dedicated workshops; a modified-Delphi process; and telephone interviews. The relevance of potential checklist items was rated using a 4-point scale content validity index to inform final inclusion. Results 14 themes (e.g. prescribing safely; dealing with medical emergency; implications of poor record keeping; and effective & safe communication) and 47 related items (e.g. how to safety-net face-to-face or over the telephone; knowledge of practice systems for results handling; recognition of harm in children) were judged to be essential safety-critical educational issues to be covered. The mean content validity index ratio was 0.98. Conclusion A checklist was developed and validated for educational supervisors to assist in the reliable delivery of safety-critical educational issues in the opening 12-week period of training, and aligned with national curriculum competencies. The tool can also be adapted for use as a self-assessment instrument by trainees to guide patient safety-related learning needs. Dissemination and implementation of the checklist and self-rating scale are proceeding on a national, voluntary basis with plans to evaluate its feasibility and educational impact. PMID:22721273

Maximising harm reduction in early specialty training for general practice: validation of a safety checklist.

PubMed

Bowie, Paul; McKay, John; Kelly, Moya

2012-06-21

Making health care safer is a key policy priority worldwide. In specialty training, medical educators may unintentionally impact on patient safety e.g. through failures of supervision; providing limited feedback on performance; and letting poorly developed behaviours continue unchecked. Doctors-in-training are also known to be susceptible to medical error. Ensuring that all essential educational issues are addressed during training is problematic given the scale of the tasks to be undertaken. Human error and the reliability of local systems may increase the risk of safety-critical topics being inadequately covered. However adherence to a checklist reminder may improve the reliability of task delivery and maximise harm reduction. We aimed to prioritise the most safety-critical issues to be addressed in the first 12-weeks of specialty training in the general practice environment and validate a related checklist reminder. We used mixed methods with different groups of GP educators (n=127) and specialty trainees (n=9) in two Scottish regions to prioritise, develop and validate checklist content. Generation and refinement of checklist themes and items were undertaken on an iterative basis using a range of methods including small group work in dedicated workshops; a modified-Delphi process; and telephone interviews. The relevance of potential checklist items was rated using a 4-point scale content validity index to inform final inclusion. 14 themes (e.g. prescribing safely; dealing with medical emergency; implications of poor record keeping; and effective & safe communication) and 47 related items (e.g. how to safety-net face-to-face or over the telephone; knowledge of practice systems for results handling; recognition of harm in children) were judged to be essential safety-critical educational issues to be covered. The mean content validity index ratio was 0.98. A checklist was developed and validated for educational supervisors to assist in the reliable delivery of safety-critical educational issues in the opening 12-week period of training, and aligned with national curriculum competencies. The tool can also be adapted for use as a self-assessment instrument by trainees to guide patient safety-related learning needs. Dissemination and implementation of the checklist and self-rating scale are proceeding on a national, voluntary basis with plans to evaluate its feasibility and educational impact.

Smartphone-Based System for Learning and Inferring Hearing Aid Settings

PubMed Central

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J.

2017-01-01

Background Previous research has shown that hearing aid wearers can successfully self-train their instruments’ gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the “untrained system,” that is, the manufacturer’s algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The “trained system” first learned each individual’s preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). Purpose To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. Research Design An experimental within-participants study. Participants used a prototype hearing system—comprising two hearing aids, Android smartphone, and body-worn gateway device—for ~6 weeks. Study Sample Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Intervention Participants were fitted and instructed to perform daily comparisons of settings (“listening evaluations”) through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone—including environmental sound classification, sound level, and location—to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system (“trained settings”) to those suggested by the hearing aids’ untrained system (“untrained settings”). Data Collection and Analysis We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Results Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. Conclusions The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. PMID:27718350

Smartphone-Based System for Learning and Inferring Hearing Aid Settings.

PubMed

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J

2016-10-01

Previous research has shown that hearing aid wearers can successfully self-train their instruments' gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the "untrained system," that is, the manufacturer's algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The "trained system" first learned each individual's preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. An experimental within-participants study. Participants used a prototype hearing system-comprising two hearing aids, Android smartphone, and body-worn gateway device-for ∼6 weeks. Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Participants were fitted and instructed to perform daily comparisons of settings ("listening evaluations") through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone-including environmental sound classification, sound level, and location-to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system ("trained settings") to those suggested by the hearing aids' untrained system ("untrained settings"). We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. American Academy of Audiology

76 FR 50233 - Submission for OMB Review; Comment Request; Web-Based Skills Training for SBIRT (Screening Brief...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-12

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Submission for OMB Review; Comment Request; Web-Based Skills Training for SBIRT (Screening Brief Intervention and Referral to... currently valid OMB control number. Proposed Collection Title: Web-based Skills Training for SBIRT...

Improving Communicative Competence: Validation of a Social Skills Training Workshop.

ERIC Educational Resources Information Center

Dawson, Pamela J.; Spitzberg, Brian H.

The effectiveness of a social skills training workshop was assessed by comparing the rated competence of participants in an Interpersonal Skills Training Program to the rated competence of nonparticipants. Subjects' self-ratings were included. This comparison was operationalized through a pretest-posttest design with 12 experimental and 22 control…

Online Plagiarism Training Falls Short in Biology Classrooms

ERIC Educational Resources Information Center

Holt, Emily A.; Fagerheim, Britt; Durham, Susan

2014-01-01

Online plagiarism tutorials are increasingly popular in higher education, as faculty and staff try to curb the plagiarism epidemic. Yet no research has validated the efficacy of such tools in minimizing plagiarism in the sciences. Our study compared three plagiarism-avoidance training regimens (i.e., no training, online tutorial, or homework…

The Job Training and Job Satisfaction Survey Technical Manual

ERIC Educational Resources Information Center

Schmidt, Steven W.

2004-01-01

Job training has become an important aspect of an employee's overall job experience. However, it is not often called out specifically on instruments measuring job satisfaction. This technical manual details the processes used in the development and validation of a survey instrument to measure job training satisfaction and overall job…

The Mediating Role of Social Support in the Evaluation of Training Effectiveness

ERIC Educational Resources Information Center

Alvelos, Rita; Ferreira, Aristides I.; Bates, Reid

2015-01-01

Purpose: The purpose of this study is to contribute to the understanding of factors that affect training effectiveness. According to the literature, social support, perceived content validity, transfer design, the motivation to improve work through learning and positive transfer, contribute to the effectiveness of training.…

76 FR 17963 - Renewal of Agency Information Collection for Application for Job Placement and Training Services...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-31

... training program, which provides vocational/technical training, related counseling, guidance, job placement... the job placement and training program, which provides vocational/technical training, related... Application for Job Placement and Training Services; Request for Comments AGENCY: Bureau of Indian Affairs...

Validation of a structured training and assessment curriculum for technical skill acquisition in minimally invasive surgery: a randomized controlled trial.

PubMed

Palter, Vanessa N; Orzech, Neil; Reznick, Richard K; Grantcharov, Teodor P

2013-02-01

: To develop and validate an ex vivo comprehensive curriculum for a basic laparoscopic procedure. : Although simulators have been well validated as tools to teach technical skills, their integration into comprehensive curricula is lacking. Moreover, neither the effect of ex vivo training on learning curves in the operating room (OR), nor the effect on nontechnical proficiency has been investigated. : This randomized single-blinded prospective trial allocated 20 surgical trainees to a structured training and assessment curriculum (STAC) group or conventional residency training. The STAC consisted of case-based learning, proficiency-based virtual reality training, laparoscopic box training, and OR participation. After completion of the intervention, all participants performed 5 sequential laparoscopic cholecystectomies in the OR. The primary outcome measure was the difference in technical performance between the 2 groups during the first laparoscopic cholecystectomy. Secondary outcome measures included differences with respect to learning curves in the OR, technical proficiency of each sequential laparoscopic cholecystectomy, and nontechnical skills. : Residents in the STAC group outperformed residents in the conventional group in the first (P = 0.004), second (P = 0.036), third (P = 0.021), and fourth (P = 0.023) laparoscopic cholecystectomies. The conventional group demonstrated a significant learning curve in the OR (P = 0.015) in contrast to the STAC group (P = 0.032). Residents in the STAC group also had significantly higher nontechnical skills (P = 0.027). : Participating in the STAC shifted the learning curve for a basic laparoscopic procedure from the operating room into the simulation laboratory. STAC-trained residents had superior technical proficiency in the OR and nontechnical skills compared with conventionally trained residents. (The study registration ID is NCT01560494.).

Quality assessment of a new surgical simulator for neuroendoscopic training.

PubMed

Filho, Francisco Vaz Guimarães; Coelho, Giselle; Cavalheiro, Sergio; Lyra, Marcos; Zymberg, Samuel T

2011-04-01

Ideal surgical training models should be entirely reliable, atoxic, easy to handle, and, if possible, low cost. All available models have their advantages and disadvantages. The choice of one or another will depend on the type of surgery to be performed. The authors created an anatomical model called the S.I.M.O.N.T. (Sinus Model Oto-Rhino Neuro Trainer) Neurosurgical Endotrainer, which can provide reliable neuroendoscopic training. The aim in the present study was to assess both the quality of the model and the development of surgical skills by trainees. The S.I.M.O.N.T. is built of a synthetic thermoretractable, thermosensible rubber called Neoderma, which, combined with different polymers, produces more than 30 different formulas. Quality assessment of the model was based on qualitative and quantitative data obtained from training sessions with 9 experienced and 13 inexperienced neurosurgeons. The techniques used for evaluation were face validation, retest and interrater reliability, and construct validation. The experts considered the S.I.M.O.N.T. capable of reproducing surgical situations as if they were real and presenting great similarity with the human brain. Surgical results of serial training showed that the model could be considered precise. Finally, development and improvement in surgical skills by the trainees were observed and considered relevant to further training. It was also observed that the probability of any single error was dramatically decreased after each training session, with a mean reduction of 41.65% (range 38.7%-45.6%). Neuroendoscopic training has some specific requirements. A unique set of instruments is required, as is a model that can resemble real-life situations. The S.I.M.O.N.T. is a new alternative model specially designed for this purpose. Validation techniques followed by precision assessments attested to the model's feasibility.

An integrated decision model for the application of airborne sensors for improved response to accidental and terrorist chemical vapor releases

NASA Astrophysics Data System (ADS)

Kapitan, Loginn

This research created a new model which provides an integrated approach to planning the effective selection and employment of airborne sensor systems in response to accidental or intentional chemical vapor releases. The approach taken was to use systems engineering and decision analysis methods to construct a model architecture which produced a modular structure for integrating both new and existing components into a logical procedure to assess the application of airborne sensor systems to address chemical vapor hazards. The resulting integrated process model includes an internal aggregation model which allowed differentiation among alternative airborne sensor systems. Both models were developed and validated by experts and demonstrated using appropriate hazardous chemical release scenarios. The resultant prototype integrated process model or system fills a current gap in capability allowing improved planning, training and exercise for HAZMAT teams and first responders when considering the selection and employment of airborne sensor systems. Through the research process, insights into the current response structure and how current airborne capability may be most effectively used were generated. Furthermore, the resultant prototype system is tailorable for local, state, and federal application, and can potentially be modified to help evaluate investments in new airborne sensor technology and systems. Better planning, training and preparedness exercising holds the prospect for the effective application of airborne assets for improved response to large scale chemical release incidents. Improved response will result in fewer casualties and lives lost, reduced economic impact, and increased protection of critical infrastructure when faced with accidental and intentional terrorist release of hazardous industrial chemicals. With the prospect of more airborne sensor systems becoming available, this prototype system integrates existing and new tools into an effective process for the selection and employment of airborne sensors to better plan, train and exercise ahead of potential chemical release events.

Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges

PubMed Central

Amarasingham, Ruben; Audet, Anne-Marie J.; Bates, David W.; Glenn Cohen, I.; Entwistle, Martin; Escobar, G. J.; Liu, Vincent; Etheredge, Lynn; Lo, Bernard; Ohno-Machado, Lucila; Ram, Sudha; Saria, Suchi; Schilling, Lisa M.; Shahi, Anand; Stewart, Walter F.; Steyerberg, Ewout W.; Xie, Bin

2016-01-01

Context: The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events in real time with the intent to improve patient outcomes and reduce costs. There is an urgent need for a systematic framework to guide the development and application of e-HPA to ensure that the field develops in a scientifically sound, ethical, and efficient manner. Objectives: Building upon earlier frameworks of model development and utilization, we identify the emerging opportunities and challenges of e-HPA, propose a framework that enables us to realize these opportunities, address these challenges, and motivate e-HPA stakeholders to both adopt and continuously refine the framework as the applications of e-HPA emerge. Methods: To achieve these objectives, 17 experts with diverse expertise including methodology, ethics, legal, regulation, and health care delivery systems were assembled to identify emerging opportunities and challenges of e-HPA and to propose a framework to guide the development and application of e-HPA. Findings: The framework proposed by the panel includes three key domains where e-HPA differs qualitatively from earlier generations of models and algorithms (Data Barriers, Transparency, and Ethics) and areas where current frameworks are insufficient to address the emerging opportunities and challenges of e-HPA (Regulation and Certification; and Education and Training). The following list of recommendations summarizes the key points of the framework: Data Barriers: Establish mechanisms within the scientific community to support data sharing for predictive model development and testing.Transparency: Set standards around e-HPA validation based on principles of scientific transparency and reproducibility.Ethics: Develop both individual-centered and society-centered risk-benefit approaches to evaluate e-HPA.Regulation and Certification: Construct a self-regulation and certification framework within e-HPA.Education and Training: Make significant changes to medical, nursing, and paraprofessional curricula by including training for understanding, evaluating, and utilizing predictive models. PMID:27141516