A new intelligent electronic nose system for measuring and analysing livestock and poultry farm odours.

PubMed

Pan, Leilei; Yang, Simon X

2007-12-01

This paper introduces a new portable intelligent electronic nose system developed especially for measuring and analysing livestock and poultry farm odours. It can be used in both laboratory and field. The sensor array of the proposed electronic nose consists of 14 gas sensors, a humidity sensor, and a temperature sensor. The gas sensors were especially selected for the main compounds from the livestock farm odours. An expert system called "Odour Expert" was developed to support researchers' and farmers' decision making on odour control strategies for livestock and poultry operations. "Odour Expert" utilises several advanced artificial intelligence technologies tailored to livestock and poultry farm odours. It can provide more advanced odour analysis than existing commercially available products. In addition, a rank of odour generation factors is provided, which refines the focus of odour control research. Field experiments were conducted downwind from the barns on 14 livestock and poultry farms. Experimental results show that the predicted odour strengths by the electronic nose yield higher consistency in comparison to the perceived odour intensity by human panel. The "Odour Expert" is a useful tool for assisting farmers' odour management practises.

Using expert opinion to evaluate a habitat effectiveness model for elk in western Oregon and Washington.

Treesearch

Richard S. Holthausen; Michael J. Wisdom; John Pierce; Daniel K. Edwards; Mary M. Rowland

1994-01-01

We used expert opinion to evaluate the predictive reliability of a habitat effectiveness model for elk in western Oregon and Washington. Twenty-five experts in elk ecology were asked to rate habitat quality for 16 example landscapes. Rankings and ratings of 21 experts were significantly correlated with model output. Expert opinion and model predictions differed for 4...

An expert elicitation process to project the frequency and magnitude of Florida manatee mortality events caused by red tide (Karenia brevis)

USGS Publications Warehouse

Martin, Julien; Runge, Michael C.; Flewelling, Leanne J.; Deutsch, Charles J.; Landsberg, Jan H.

2017-11-20

Red tides (blooms of the harmful alga Karenia brevis) are one of the major sources of mortality for the Florida manatee (Trichechus manatus latirostris), especially in southwest Florida. It has been hypothesized that the frequency and severity of red tides may increase in the future because of global climate change and other factors. To improve our ecological forecast for the effects of red tides on manatee population dynamics and long-term persistence, we conducted a formal expert judgment process to estimate probability distributions for the frequency and relative magnitude of red-tide-related manatee mortality (RTMM) events over a 100-year time horizon in three of the four regions recognized as manatee management units in Florida. This information was used to update a population viability analysis for the Florida manatee (the Core Biological Model). We convened a panel of 12 experts in manatee biology or red-tide ecology; the panel met to frame, conduct, and discuss the elicitation. Each expert provided a best estimate and plausible low and high values (bounding a confidence level of 80 percent) for each parameter in each of three regions (Northwest, Southwest, and Atlantic) of the subspecies’ range (excluding the Upper St. Johns River region) for two time periods (0−40 and 41−100 years from present). We fitted probability distributions for each parameter, time period, and expert by using these three elicited values. We aggregated the parameter estimates elicited from individual experts and fitted a parametric distribution to the aggregated results.Across regions, the experts expected the future frequency of RTMM events to be higher than historical levels, which is consistent with the hypothesis that global climate change (among other factors) may increase the frequency of red-tide blooms. The experts articulated considerable uncertainty, however, about the future frequency of RTMM events. The historical frequency of moderate and intense RTMM (combined) in the Southwest region was 0.35 (80-percent confidence interval [CI]: 0.21−0.52), whereas the forecast probability was 0.48 (80-percent CI: 0.30−0.64) over a 40-year projected time horizon. Moderate and intense RTMM events are expected to continue to be most frequent in the Southwest region, to increase in mean frequency in the Northwest region (historical frequency of moderate and intense RTMM events [combined] in the Northwest region was 0, whereas the forecast probability was 0.12 [80-percent CI: 0.02−0.39] over a 40-year projected time horizon) and in the Atlantic region (historical frequency of moderate and intense RTMM events [combined] in the Atlantic region was 0.05 [80-percent CI: 0.005–0.18], whereas the forecast probability was 0.11 [80-percent CI: 0.03−0.25] over a 40-year projected time horizon), and to remain absent from the Upper St. Johns River region. The impact of red-tide blooms on manatee mortality has been measured for the Southwest region but not for the Northwest and Atlantic regions, where such events have been rare. The expert panel predicted that the median magnitude of RTMM events in the Atlantic and Northwest regions will be much smaller than that in the Southwest; given the large uncertainties, however, they acknowledged the possibility that these events could be larger in their mortality impacts than in the Southwest region. By its nature, forecasting requires expert judgment because it is impossible to have empirical evidence about the future. The large uncertainties in parameter estimates over a 100-year timeframe are to be expected and may also indicate that the training provided to panelists successfully minimized one common pitfall of expert judgment, that of overconfidence. This study has provided useful and needed inputs to the Florida manatee population viability analysis associated with an important and recurrent source of mortality from harmful algal blooms.

Forensic Comparison and Matching of Fingerprints: Using Quantitative Image Measures for Estimating Error Rates through Understanding and Predicting Difficulty

PubMed Central

Kellman, Philip J.; Mnookin, Jennifer L.; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E.

2014-01-01

Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and subjective assessment of difficulty in fingerprint comparisons. PMID:24788812

Musical Expertise and the Ability to Imagine Loudness

PubMed Central

Bishop, Laura; Bailes, Freya; Dean, Roger T.

2013-01-01

Most perceived parameters of sound (e.g. pitch, duration, timbre) can also be imagined in the absence of sound. These parameters are imagined more veridically by expert musicians than non-experts. Evidence for whether loudness is imagined, however, is conflicting. In music, the question of whether loudness is imagined is particularly relevant due to its role as a principal parameter of performance expression. This study addressed the hypothesis that the veridicality of imagined loudness improves with increasing musical expertise. Experts, novices and non-musicians imagined short passages of well-known classical music under two counterbalanced conditions: 1) while adjusting a slider to indicate imagined loudness of the music and 2) while tapping out the rhythm to indicate imagined timing. Subtests assessed music listening abilities and working memory span to determine whether these factors, also hypothesised to improve with increasing musical expertise, could account for imagery task performance. Similarity between each participant’s imagined and listening loudness profiles and reference recording intensity profiles was assessed using time series analysis and dynamic time warping. The results suggest a widespread ability to imagine the loudness of familiar music. The veridicality of imagined loudness tended to be greatest for the expert musicians, supporting the predicted relationship between musical expertise and musical imagery ability. PMID:23460791

Musical expertise and the ability to imagine loudness.

PubMed

Bishop, Laura; Bailes, Freya; Dean, Roger T

2013-01-01

Most perceived parameters of sound (e.g. pitch, duration, timbre) can also be imagined in the absence of sound. These parameters are imagined more veridically by expert musicians than non-experts. Evidence for whether loudness is imagined, however, is conflicting. In music, the question of whether loudness is imagined is particularly relevant due to its role as a principal parameter of performance expression. This study addressed the hypothesis that the veridicality of imagined loudness improves with increasing musical expertise. Experts, novices and non-musicians imagined short passages of well-known classical music under two counterbalanced conditions: 1) while adjusting a slider to indicate imagined loudness of the music and 2) while tapping out the rhythm to indicate imagined timing. Subtests assessed music listening abilities and working memory span to determine whether these factors, also hypothesised to improve with increasing musical expertise, could account for imagery task performance. Similarity between each participant's imagined and listening loudness profiles and reference recording intensity profiles was assessed using time series analysis and dynamic time warping. The results suggest a widespread ability to imagine the loudness of familiar music. The veridicality of imagined loudness tended to be greatest for the expert musicians, supporting the predicted relationship between musical expertise and musical imagery ability.

Graphic Novels in Libraries: An Expert's Opinion

ERIC Educational Resources Information Center

Foster, Katy

2004-01-01

Barbara Gordon a librarian and computer expert from Gotham city is a genius level intellect and photographic memory expert at research and analysis. According to her, graphic novels and comics are wildly appealing to readers of all ages and intensely popular with adolescents.

Planning intensive care unit design using computer simulation modeling: optimizing integration of clinical, operational, and architectural requirements.

PubMed

OʼHara, Susan

2014-01-01

Nurses have increasingly been regarded as critical members of the planning team as architects recognize their knowledge and value. But the nurses' role as knowledge experts can be expanded to leading efforts to integrate the clinical, operational, and architectural expertise through simulation modeling. Simulation modeling allows for the optimal merge of multifactorial data to understand the current state of the intensive care unit and predict future states. Nurses can champion the simulation modeling process and reap the benefits of a cost-effective way to test new designs, processes, staffing models, and future programming trends prior to implementation. Simulation modeling is an evidence-based planning approach, a standard, for integrating the sciences with real client data, to offer solutions for improving patient care.

Football experts versus sports economists: Whose forecasts are better?

PubMed

Frick, Bernd; Wicker, Pamela

2016-08-01

Given the uncertainty of outcome in sport, predicting the outcome of sporting contests is a major topic in sport sciences. This study examines the accuracy of expert predictions in the German Bundesliga and compares their predictions to those of sports economists. Prior to the start of each season, a set of distinguished experts (head coaches and players) express their subjective evaluations of the teams in school grades. While experts may be driven by irrational sentiments and may therefore systematically over- or underestimate specific teams, sports economists use observable characteristics to predict season outcomes. The latter typically use team wage bills given the positive pay-performance relationship as well as other factors (average team age, tenure, appearances on national team, and attendance). Using data from 15 consecutive Bundesliga seasons, the predictive accuracy of expert evaluations and sports economists is analysed. The results of separate estimations show that relative grade and relative wage bill significantly affect relative points, while age, tenure, appearances, and attendance are insignificant. In a joint model, relative grade and relative wage bill are still statistically significant, suggesting that the two types of predictions are complements rather than substitutes. Consequently, football experts and sports economists seem to rely on completely different sources of information when making their predictions.

Predicting soccer matches after unconscious and conscious thought as a function of expertise.

PubMed

Dijksterhuis, Ap; Bos, Maarten W; van der Leij, Andries; van Baaren, Rick B

2009-11-01

In two experiments, we investigated the effects of expertise and mode of thought on the accuracy of people's predictions. Both experts and nonexperts predicted the results of soccer matches after conscious thought, after unconscious thought, or immediately. In Experiment 1, experts who thought unconsciously outperformed participants in all other conditions. Whereas unconscious thinkers showed a correlation between expertise and accuracy of prediction, no such relation was observed for conscious thinkers or for immediate decision makers. In Experiment 2, this general pattern was replicated. In addition, experts who thought unconsciously were better at applying diagnostic information than experts who thought consciously or who decided immediately. The results are consistent with unconscious-thought theory.

ECG Rhythm Analysis with Expert and Learner-Generated Schemas in Novice Learners

ERIC Educational Resources Information Center

Blissett, Sarah; Cavalcanti, Rodrigo; Sibbald, Matthew

2015-01-01

Although instruction using expert-generated schemas is associated with higher diagnostic performance, implementation is resource intensive. Learner-generated schemas are an alternative, but may be limited by increases in cognitive load. We compared expert- and learner-generated schemas for learning ECG rhythm interpretation on diagnostic accuracy,…

Comparison of Decision Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions

DTIC Science & Technology

2015-03-01

min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by...Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm...15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

PubMed

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

Does expert perceptual anticipation transfer to a dissimilar domain?

PubMed

Müller, Sean; McLaren, Michelle; Appleby, Brendyn; Rosalie, Simon M

2015-06-01

The purpose of this experiment was to extend theoretical understanding of transfer of learning by investigating whether expert perceptual anticipation skill transfers to a dissimilar domain. The capability of expert and near-expert rugby players as well as novices to anticipate skill type within rugby (learning sport) was first examined using a temporal occlusion paradigm. Participants watched video footage of an opponent performing rugby skill types that were temporally occluded at different points in the opponent's action and then made a written prediction. Thereafter, the capability of participants to transfer their anticipation skill to predict pitch type in baseball (transfer sport) was examined. Participants watched video footage of a pitcher throwing different pitch types that were temporally occluded and made a written prediction. Results indicated that expert and near-expert rugby players anticipated significantly better than novices across all occlusion conditions. However, none of the skill groups were able to transfer anticipation skill to predict pitch type in baseball. The findings of this paper, along with existing literature, support the theoretical prediction that transfer of perceptual anticipation is expertise dependent and restricted to similar domains. (c) 2015 APA, all rights reserved).

Advancements in the management of medically less-fit and older adults with newly diagnosed acute myeloid leukemia.

PubMed

Michaelis, Laura C; Klepin, Heidi D; Walter, Roland B

2018-06-01

Treating acute myeloid leukemia (AML) in older adults remains daunting. The unique biology often renders conventional chemotherapies less effective. Accurately predicting the toxicities of treatment is another unresolved challenge. Treatment planning thus requires a good knowledge of the current trial data and familiarity with clinical tools, including formal fitness and geriatric assessments. Both obstacles - disease biology and patient fitness - might be easier overcome with specific, AML cell-targeted agents rather than traditional cytotoxic chemotherapy. This may be the future of AML therapy, but it is not our current state. Areas covered: Herein, the authors appraise the data supporting a standard induction approach, including an outline of how to predict treatment-related mortality and a review of the most up-to-date methods of geriatric assessment. They also discuss treatment expectations with less-intense therapies and highlight novel agents in development. Finally, they provide a basic approach to choosing treatment intensity. Expert opinion: In an older and/or medically less-fit patient, treatment choice should begin with a thorough disease assessment, a formal evaluation of patient fitness and frailty. There should also be a clear communication with the patient and patient's family about the risks and anticipated benefits of either an intense or nonintense treatment approach.

An evaluation of selected (Q)SARs/expert systems for the Prediction of Skin Sensitization Potential (WC10)

EPA Science Inventory

One of the alternative approaches to assessing skin sensitization hazard is through the use of (Q)SARs/expert systems. Here we evaluate the predictive performance of two expert systems (TIMES-SS and VEGA) and two SAR rulebases (OASIS protein binding alerts and Toxtree’s reactivit...

The use of a sweetener substitution method to predict dietary exposures for the intense sweetener rebaudioside A.

PubMed

Renwick, A G

2008-07-01

There are more published dietary exposure data for intense sweeteners than for any other group of food additives. Data are available for countries with different patterns of sweetener approvals and also for population groups with high potential intakes, such as children and diabetic subjects. These data provide a secure basis for predicting the potential intakes of a novel intense sweetener by adjustment of the reported intakes of different sweeteners in mg/kg body weight by their relative sweetness intensities. This approach allows the possibility that a novel sweetener attains the same pattern and extent of use as the existing sweeteners. The intakes by high consumers of other sweeteners allows for possible brand loyalty to the novel sweetener. Using this method, the estimated dietary exposures for rebaudioside A in average and high consumers are predicted to be 1.3 and 3.4mg/kg body weight per day for the general population, 2.1 and 5.0mg/kg body weight per day for children and 3.4 and 4.5mg/kg body weight per day for children with diabetes. The temporary ADI defined by the JECFA for steviol glycosides [JECFA, 2005. Steviol glycosides. In: 63rd Meeting of the Joint FAO/WHO Expert Committee on Food Additives. World Health Organization (WHO), Geneva, Switzerland, WHO Technical Report Series 928, pp. 34-39] was set at 0-2mg/kg body weight (expressed as steviol equivalents); after correction for the difference in molecular weights, these estimated intakes of rebaudioside A are equivalent to daily steviol intakes of less than 2mg/kg. In consequence, this analysis shows that the intakes of rebaudioside A would not exceed the JECFA temporary ADI set for steviol glycosides.

Interictal epileptiform discharge characteristics underlying expert interrater agreement.

PubMed

Bagheri, Elham; Dauwels, Justin; Dean, Brian C; Waters, Chad G; Westover, M Brandon; Halford, Jonathan J

2017-10-01

The presence of interictal epileptiform discharges (IED) in the electroencephalogram (EEG) is a key finding in the medical workup of a patient with suspected epilepsy. However, inter-rater agreement (IRA) regarding the presence of IED is imperfect, leading to incorrect and delayed diagnoses. An improved understanding of which IED attributes mediate expert IRA might help in developing automatic methods for IED detection able to emulate the abilities of experts. Therefore, using a set of IED scored by a large number of experts, we set out to determine which attributes of IED predict expert agreement regarding the presence of IED. IED were annotated on a 5-point scale by 18 clinical neurophysiologists within 200 30-s EEG segments from recordings of 200 patients. 5538 signal analysis features were extracted from the waveforms, including wavelet coefficients, morphological features, signal energy, nonlinear energy operator response, electrode location, and spectrogram features. Feature selection was performed by applying elastic net regression and support vector regression (SVR) was applied to predict expert opinion, with and without the feature selection procedure and with and without several types of signal normalization. Multiple types of features were useful for predicting expert annotations, but particular types of wavelet features performed best. Local EEG normalization also enhanced best model performance. As the size of the group of EEGers used to train the models was increased, the performance of the models leveled off at a group size of around 11. The features that best predict inter-rater agreement among experts regarding the presence of IED are wavelet features, using locally standardized EEG. Our models for predicting expert opinion based on EEGer's scores perform best with a large group of EEGers (more than 10). By examining a large group of EEG signal analysis features we found that wavelet features with certain wavelet basis functions performed best to identify IEDs. Local normalization also improves predictability, suggesting the importance of IED morphology over amplitude-based features. Although most IED detection studies in the past have used opinion from three or fewer experts, our study suggests a "wisdom of the crowd" effect, such that pooling over a larger number of expert opinions produces a better correlation between expert opinion and objectively quantifiable features of the EEG. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other's Actions by Humans.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2017-01-01

The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions.

Processes in construction of failure management expert systems from device design information

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Lance, Nick

1987-01-01

This paper analyzes the tasks and problem solving methods used by an engineer in constructing a failure management expert system from design information about the device to te diagnosed. An expert test engineer developed a trouble-shooting expert system based on device design information and experience with similar devices, rather than on specific expert knowledge gained from operating the device or troubleshooting its failures. The construction of the expert system was intensively observed and analyzed. This paper characterizes the knowledge, tasks, methods, and design decisions involved in constructing this type of expert system, and makes recommendations concerning tools for aiding and automating construction of such systems.

An expert systems approach to automated fault management in a regenerative life support subsystem

NASA Technical Reports Server (NTRS)

Malin, J. T.; Lance, N., Jr.

1986-01-01

This paper describes FIXER, a prototype expert system for automated fault management in a regenerative life support subsystem typical of Space Station applications. The development project provided an evaluation of the use of expert systems technology to enhance controller functions in space subsystems. The software development approach permitted evaluation of the effectiveness of direct involvement of the expert in design and development. The approach also permitted intensive observation of the knowledge and methods of the expert. This paper describes the development of the prototype expert system and presents results of the evaluation.

Field-testing of a cost-effective mobile-phone based microscope for screening of Schistosoma haematobium infection (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ceylan Koydemir, Hatice; Bogoch, Isaac I.; Tseng, Derek; Ephraim, Richard K. D.; Duah, Evans; Tee, Joseph; Andrews, Jason R.; Ozcan, Aydogan

2016-03-01

Schistosomiasis is a parasitic and neglected tropical disease, and affects <200-million people across the world, with school-aged children disproportionately affected. Here we present field-testing results of a handheld and cost effective smartphone-based microscope in rural Ghana, Africa, for point-of-care diagnosis of S. haematobium infection. In this mobile-phone microscope, a custom-designed 3D printed opto-mechanical attachment (~150g) is placed in contact with the smartphone camera-lens, creating an imaging-system with a half-pitch resolution of ~0.87µm. This unit includes an external lens (also taken from a mobile-phone camera), a sample tray, a z-stage to adjust the focus, two light-emitting-diodes (LEDs) and two diffusers for uniform illumination of the sample. In our field-testing, 60 urine samples, collected from children, were used, where the prevalence of the infection was 72.9%. After concentration of the sample with centrifugation, the sediment was placed on a glass-slide and S. haematobium eggs were first identified/quantified using conventional benchtop microscopy by an expert diagnostician, and then a second expert, blinded to these results, determined the presence/absence of eggs using our mobile-phone microscope. Compared to conventional microscopy, our mobile-phone microscope had a diagnostic sensitivity of 72.1%, specificity of 100%, positive-predictive-value of 100%, and a negative-predictive-value of 57.1%. Furthermore, our mobile-phone platform demonstrated a sensitivity of 65.7% and 100% for low-intensity infections (≤50 eggs/10 mL urine) and high-intensity infections (<50 eggs/10 mL urine), respectively. We believe that this cost-effective and field-portable mobile-phone microscope may play an important role in the diagnosis of schistosomiasis and various other global health challenges.

[Differences between experts and novices in estimations of cue predictive power in crime].

PubMed

García-Retamero, Rocío; Dhami, Mandeep K

2009-08-01

In this study, we compared experts' and novices' estimates of the power of several cues to predict residential burglary. Participants were experienced police officers and burglars, and graduates with no experience in this domain. They all estimated the weight of each cue in predicting the likelihood of a property being burgled. In addition, they ranked the cues according to how useful they would be in predicting the likelihood of burglary. Results showed that the two expert groups differed substantially in their cue weights and rankings, and the police officers were actually more similar to novices in this regard. Beyond this, the two expert groups were more consistent in their responses than novices, that is, they showed less variability in their estimates when using different response method and were more consistent with other participants from their own group. Our results extend the literature on expert-novice differences, and have implications for criminal justice policy and decision making.

Watching novice action degrades expert motor performance: Causation between action production and outcome prediction of observed actions by humans

PubMed Central

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2014-01-01

Our social skills are critically determined by our ability to understand and appropriately respond to actions performed by others. However despite its obvious importance, the mechanisms enabling action understanding in humans have remained largely unclear. A popular but controversial belief is that parts of the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral paradigm, we investigated this belief by examining a causal relation between action production, and a component of action understanding - outcome prediction, the ability of a person to predict the outcome of observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert's ability to predict watched actions while controlling the other experimental factors, and exhibited that a change (improvement) in their outcome prediction ability results in a progressive and proportional deterioration in the expert's own darts performance. This causal relationship supports involvement of the motor system in outcome prediction by humans of actions observed in others. PMID:25384755

Semi-automatic segmentation of nonviable cardiac tissue using cine and delayed enhancement magnetic resonance images

NASA Astrophysics Data System (ADS)

O'Donnell, Thomas P.; Xu, Ning; Setser, Randolph M.; White, Richard D.

2003-05-01

Post myocardial infarction, the identification and assessment of non-viable (necrotic) tissues is necessary for effective development of intervention strategies and treatment plans. Delayed Enhancement Magnetic Resonance (DEMR) imaging is a technique whereby non-viable cardiac tissue appears with increased signal intensity. Radiologists typically acquire these images in conjunction with other functional modalities (e.g., MR Cine), and use domain knowledge and experience to isolate the non-viable tissues. In this paper, we present a technique for automatically segmenting these tissues given the delineation of myocardial borders in the DEMR and in the End-systolic and End-diastolic MR Cine images. Briefly, we obtain a set of segmentations furnished by an expert and employ an artificial intelligence technique, Support Vector Machines (SVMs), to "learn" the segmentations based on features culled from the images. Using those features we then allow the SVM to predict the segmentations the expert would provide on previously unseen images.

Computer vision and machine learning for robust phenotyping in genome-wide studies

PubMed Central

Zhang, Jiaoping; Naik, Hsiang Sing; Assefa, Teshale; Sarkar, Soumik; Reddy, R. V. Chowda; Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh K.

2017-01-01

Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse plant-introduction accessions was evaluated using an end-to-end phenotyping workflow. The workflow consisted of a multi-stage procedure including: (1) optimized protocols for consistent image capture across plant canopies, (2) canopy identification and registration from cluttered backgrounds, (3) extraction of domain expert informed features from the processed images to accurately represent IDC expression, and (4) supervised ML-based classifiers that linked the automatically extracted features with expert-rating equivalent IDC scores. ML-generated phenotypic data were subsequently utilized for the genome-wide association study and genomic prediction. The results illustrate the reliability and advantage of ML-enabled image-phenotyping pipeline by identifying previously reported locus and a novel locus harboring a gene homolog involved in iron acquisition. This study demonstrates a promising path for integrating the phenotyping pipeline into genomic prediction, and provides a systematic framework enabling robust and quicker phenotyping through ground-based systems. PMID:28272456

Communicating Chemical Risks for Social Learning: Findings from an Expert Opinion Survey

ERIC Educational Resources Information Center

Lyytimaki, Jari; Assmuth, Timo; Hilden, Mikael

2009-01-01

Environmental and health risks caused by chemical substances have been intensively debated in various arenas of science and policy, and in news media. The impacts of risk debates on the public have been widely studied, while less attention has been paid to expert views. We present results from a cross-national survey charting expert views on the…

Effects of Long-term Diving Training on Cortical Gyrification.

PubMed

Zhang, Yuanchao; Zhao, Lu; Bi, Wenwei; Wang, Yue; Wei, Gaoxia; Evans, Alan; Jiang, Tianzi

2016-06-20

During human brain development, cortical gyrification, which is believed to facilitate compact wiring of neural circuits, has been shown to follow an inverted U-shaped curve, coinciding with the two-stage neurodevelopmental process of initial synaptic overproduction with subsequent pruning. This trajectory allows postnatal experiences to refine the wiring, which may manifest as endophenotypic changes in cortical gyrification. Diving experts, typical elite athletes who commence intensive motor training at a very young age in their early childhood, serve ideal models for examining the gyrification changes related to long-term intensive diving training. Using local gyrification index (LGI), we compared the cortical gyrification between 12 diving experts and 12 controls. Compared with controls, diving experts showed widespread LGI reductions in regions relevant to diving performance. Negative correlations between LGIs and years of diving training were also observed in diving experts. Further exploratory network efficiency analysis of structural cortical networks, inferred from interregional correlation of LGIs, revealed comparable global and local efficiency in diving experts relative to controls. These findings suggest that gyrification reductions in diving experts may be the result of long-term diving training which could refine the neural circuitry (via synaptic pruning) and might be the anatomical substrate underlying their extraordinary diving performance.

Identifying structural elements needed for development of a predictive life-history model for pallid and shovelnose sturgeons

USGS Publications Warehouse

Wildhaber, Mark L.; DeLonay, A.J.; Papoulias, D.M.; Galat, D.L.; Jacobson, R.B.; Simpkins, D.G.; Braaten, P.J.; Korschgen, C.E.; Mac, M.J.

2011-01-01

Intensive management of the Missouri and Mississippi Rivers has resulted in dramatic changes to the river systems and their biota. These changes have been implicated in the decline of the pallid sturgeon (Scaphirhynchus albus), which has been listed as a United States federal endangered species. The sympatric shovelnose sturgeon (S. platorynchus) is more common and widespread but has also been in decline. The decline of pallid sturgeon is considered symptomatic of poor reproductive success and low or no recruitment. In order to organize information about these species and provide a basis for future development of a predictive model to help guide recovery efforts, we present an expert-vetted, conceptual life-history framework that incorporates the factors that affect reproduction, growth, and survival of shovelnose and pallid sturgeons.

Automatic single questionnaire intensity (SQI, EMS98 scale) estimation using ranking models built on the existing BCSF database

NASA Astrophysics Data System (ADS)

Schlupp, A.; Sira, C.; Schmitt, K.; Schaming, M.

2013-12-01

In charge of intensity estimations in France, BCSF has collected and manually analyzed more than 47000 online individual macroseismic questionnaires since 2000 up to intensity VI. These macroseismic data allow us to estimate one SQI value (Single Questionnaire Intensity) for each form following the EMS98 scale. The reliability of the automatic intensity estimation is important as they are today used for automatic shakemaps communications and crisis management. Today, the automatic intensity estimation at BCSF is based on the direct use of thumbnails selected on a menu by the witnesses. Each thumbnail corresponds to an EMS-98 intensity value, allowing us to quickly issue an intensity map of the communal intensity by averaging the SQIs at each city. Afterwards an expert, to determine a definitive SQI, manually analyzes each form. This work is time consuming and not anymore suitable considering the increasing number of testimonies at BCSF. Nevertheless, it can take into account incoherent answers. We tested several automatic methods (USGS algorithm, Correlation coefficient, Thumbnails) (Sira et al. 2013, IASPEI) and compared them with 'expert' SQIs. These methods gave us medium score (between 50 to 60% of well SQI determined and 35 to 40% with plus one or minus one intensity degree). The best fit was observed with the thumbnails. Here, we present new approaches based on 3 statistical ranking methods as 1) Multinomial logistic regression model, 2) Discriminant analysis DISQUAL and 3) Support vector machines (SVMs). The two first methods are standard methods, while the third one is more recent. Theses methods could be applied because the BCSF has already in his database more then 47000 forms and because their questions and answers are well adapted for a statistical analysis. The ranking models could then be used as automatic method constrained on expert analysis. The performance of the automatic methods and the reliability of the estimated SQI can be evaluated thanks to the fact that each definitive BCSF SQIs is determined by an expert analysis. We compare the SQIs obtained by these methods from our database and discuss the coherency and variations between automatic and manual processes. These methods lead to high scores with up to 85% of the forms well classified and most of the remaining forms classified with only a shift of one intensity degree. This allows us to use the ranking methods as the best automatic methods to fast SQIs estimation and to produce fast shakemaps. The next step, to improve the use of these methods, will be to identify explanations for the forms not classified at the correct value and a way to select the few remaining forms that should be analyzed by the expert. Note that beyond intensity VI, on-line questionnaires are insufficient and a field survey is indispensable to estimate intensity. For such survey, in France, BCSF leads a macroseismic intervention group (GIM).

On the use of different measures of exposure-experiences from a case-control study on testicular cancer and PVC exposure.

PubMed

Westberg, Håkan B T; Hardell, Lennart O; Malmqvist, Nils; Ohlson, Carl-Göran; Axelson, Olav

2005-07-01

Associations between exposure to PVC plastics and testicular cancer have been reported. To improve the exposure-response analysis in a matched case-control study on testicular cancer and occupational exposures, a self-administered exposure questionnaire and expert assessment was applied and different exposure measures were developed. The questionnaires regarding work histories and employment in PVC production, manufacturing, and handling of PVC products were completed by 1582 subjects (90%). By expert assessment, 360 subjects were considered exposed, and the exposure intensity to PVC plastics for different working periods was determined. Different exposure measures to PVC plastics were then developed, such as ever/never exposed, duration, maximum intensity, median intensity, and cumulative median intensity. The correlation between the different measures of exposure was high for exposure duration and the cumulative median exposure intensity (Spearman rank coefficient r(s) = 0.94), as was the correlation between the maximum intensity and the median intensity (r(s) = 0.94). The agreement between the answers in the questionnaire and the expert assessments was moderate, Kappa value 0.56. The odds ratio for "ever" exposed based on the exposure as reported in the questionnaire was 1.1 (95%, CI 0.82-1.56), and as determined by expert assessment 1.3 (CI 1.05-1.69). The odds ratios for all four different categories of exposure measures varied between 0.86 and 2.6 but decreased by increasing exposure. An overall excess of testicular cancer for the PVC exposed vs. the unexposed was not supported by the pattern seen in a standard exposure-response analysis based on several exposure measures. The findings stress the importance of using several exposure measures as dose surrogates when the underlying toxic mechanisms are unknown and when there are indications of an overall effect.

Preparing for uncertainty: toward managing fluvial geomorphic assessment of Massachusetts rivers

NASA Astrophysics Data System (ADS)

Hatch, C. E.; Mabee, S. B.; Slovin, N. B.; Vogel, E.

2014-12-01

Climate scientists predict (and have already observed) that in the Northeastern U.S., individual storms may be more intense, and that there will be more precipitation on an annual basis. In steep post-glacial terrain, erosion caused by floodwaters is the largest destructive force during high-intensity storm events, and the force most likely to drive major morphological changes to riverbanks and channels. What remains uncertain is which watersheds or river reaches may be subjected to increased damage from more intense storms. This presents a challenge for scientific outreach and management. Many New England states have developed systems for delineating the potentially geomorphically active zones adjacent to rivers, and Vermont has an excellent assessment and land use management system informed by process-based fluvial geomorphologic science. To date, however, Massachusetts has neither. In this project we survey existing protocols for accurately predicting locations of fluvial erosion hazard, including using LiDAR and DEM models to extract basic morphologic metrics. Particularly in states or landscapes with high river density, and during a time of tight fiscal constraints, managers need automated methods that require a minimum of expert input. We test these methods in the Deerfield river watershed in Massachusetts and Vermont, and integrate our knowledge with that of the basin's agricultural and floodplain stakeholders. The results will inform development of a comprehensive river assessment and land use management system for the state of Massachusetts.

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

PubMed

Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

2016-01-01

The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The potential to visualize the likely course of recovery has implications for clinical decision-making, as well as trial enrichment.

Accelerating Adverse Outcome Pathway Development Using ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledgebase, however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally-predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of twenty-first century toxicity testing strategies. This review article describes how effective knowledge management and automated approaches to AOP development can enhance and accelerate the development and use of AOPs. As the principles documented in this review are put into practice, we anticipate that the quality and quantity of AOPs available will increase substantially. This, in turn, will aid in the interpretation of ToxCast and other high-throughput tox

OCT minimum intensity as a predictor of geographic atrophy enlargement.

PubMed

Stetson, Paul F; Yehoshua, Zohar; Garcia Filho, Carlos Alexandre A; Portella Nunes, Renata; Gregori, Giovanni; Rosenfeld, Philip J

2014-02-10

We determined whether the minimum intensity (MI) of the optical coherence tomography (OCT) A-scans within the retina can predict locations of growth at the margin of geographic atrophy (GA) and the growth rate outside the margin. The OCT scans were analyzed at baseline and 52 weeks. Expert graders manually segmented OCT images of GA. The 52-week follow-up scans were registered to the baseline scan coordinates for comparison. The OCT MI values were studied within a 180-μm margin around the boundary of GA at baseline. Baseline MI values were compared in areas of progression and nonprogression of the GA, and sensitivity and specificity were assessed for prediction of growth at the margin. Average MI values in the margins were compared to overall growth rates to evaluate the prediction of growth outside the margins. A statistically significant increase in MI (P < 0.05) was seen in areas of growth in 21/24 cases (88%), and 22/24 cases (92%) when the foveal subfield was excluded. Locations of growth within the margins at 52 weeks were predicted with 61% sensitivity and 61% specificity. The MI values correlated significantly with overall growth rate, and high and low growth rate subjects were identified with 80% sensitivity and 64% specificity. The MI may be increased at the margins of GA lesions before enlargement, which may indicate disruption or atrophy of the photoreceptors in these areas before GA becomes apparent. Increased MI may help predict areas of enlargement of GA, and may relate to overall growth rate and be a useful screening tool for GA. (ClinicalTrials.gov number, NCT00935883.).

Predicting Forest Regeneration in the Central Appalachians Using the REGEN Expert System

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system designed by David Loftis to predict the future species composition of dominant and codominant stems in forest stands at the onset of stem exclusion following a proposed harvest. REGEN predictions are generated using competitive rankings for advance reproduction along with other existing stand conditions. These parameters are contained within...

Intensive Intervention Practice Guide: Motivation Training

ERIC Educational Resources Information Center

Didion, Lisa Anne; Gesel, Samantha A.; Martinez-Lincoln, Amanda; Leonard, Kaitlin

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge.

PubMed

Biggerstaff, Matthew; Alper, David; Dredze, Mark; Fox, Spencer; Fung, Isaac Chun-Hai; Hickmann, Kyle S; Lewis, Bryan; Rosenfeld, Roni; Shaman, Jeffrey; Tsou, Ming-Hsiang; Velardi, Paola; Vespignani, Alessandro; Finelli, Lyn

2016-07-22

Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts.

Management of neutropenic patients in the intensive care unit (NEWBORNS EXCLUDED) recommendations from an expert panel from the French Intensive Care Society (SRLF) with the French Group for Pediatric Intensive Care Emergencies (GFRUP), the French Society of Anesthesia and Intensive Care (SFAR), the French Society of Hematology (SFH), the French Society for Hospital Hygiene (SF2H), and the French Infectious Diseases Society (SPILF).

PubMed

Schnell, David; Azoulay, Elie; Benoit, Dominique; Clouzeau, Benjamin; Demaret, Pierre; Ducassou, Stéphane; Frange, Pierre; Lafaurie, Matthieu; Legrand, Matthieu; Meert, Anne-Pascale; Mokart, Djamel; Naudin, Jérôme; Pene, Frédéric; Rabbat, Antoine; Raffoux, Emmanuel; Ribaud, Patricia; Richard, Jean-Christophe; Vincent, François; Zahar, Jean-Ralph; Darmon, Michael

2016-12-01

Neutropenia is defined by either an absolute or functional defect (acute myeloid leukemia or myelodysplastic syndrome) of polymorphonuclear neutrophils and is associated with high risk of specific complications that may require intensive care unit (ICU) admission. Specificities in the management of critically ill neutropenic patients prompted the establishment of guidelines dedicated to intensivists. These recommendations were drawn up by a panel of experts brought together by the French Intensive Care Society in collaboration with the French Group for Pediatric Intensive Care Emergencies, the French Society of Anesthesia and Intensive Care, the French Society of Hematology, the French Society for Hospital Hygiene, and the French Infectious Diseases Society. Literature review and formulation of recommendations were performed using the Grading of Recommendations Assessment, Development and Evaluation system. Each recommendation was then evaluated and rated by each expert using a methodology derived from the RAND/UCLA Appropriateness Method. Six fields are covered by the provided recommendations: (1) ICU admission and prognosis, (2) protective isolation and prophylaxis, (3) management of acute respiratory failure, (4) organ failure and organ support, (5) antibiotic management and source control, and (6) hematological management. Most of the provided recommendations are obtained from low levels of evidence, however, suggesting a need for additional studies. Seven recommendations were, however, associated with high level of evidences and are related to protective isolation, diagnostic workup of acute respiratory failure, medical management, and timing surgery in patients with typhlitis.

Effect of Increased Intensity of Physiotherapy on Patient Outcomes After Stroke: An Economic Literature Review and Cost-Effectiveness Analysis

PubMed Central

Chan, B

2015-01-01

Background Functional improvements have been seen in stroke patients who have received an increased intensity of physiotherapy. This requires additional costs in the form of increased physiotherapist time. Objectives The objective of this economic analysis is to determine the cost-effectiveness of increasing the intensity of physiotherapy (duration and/or frequency) during inpatient rehabilitation after stroke, from the perspective of the Ontario Ministry of Health and Long-term Care. Data Sources The inputs for our economic evaluation were extracted from articles published in peer-reviewed journals and from reports from government sources or the Canadian Stroke Network. Where published data were not available, we sought expert opinion and used inputs based on the experts' estimates. Review Methods The primary outcome we considered was cost per quality-adjusted life-year (QALY). We also evaluated functional strength training because of its similarities to physiotherapy. We used a 2-state Markov model to evaluate the cost-effectiveness of functional strength training and increased physiotherapy intensity for stroke inpatient rehabilitation. The model had a lifetime timeframe with a 5% annual discount rate. We then used sensitivity analyses to evaluate uncertainty in the model inputs. Results We found that functional strength training and higher-intensity physiotherapy resulted in lower costs and improved outcomes over a lifetime. However, our sensitivity analyses revealed high levels of uncertainty in the model inputs, and therefore in the results. Limitations There is a high level of uncertainty in this analysis due to the uncertainty in model inputs, with some of the major inputs based on expert panel consensus or expert opinion. In addition, the utility outcomes were based on a clinical study conducted in the United Kingdom (i.e., 1 study only, and not in an Ontario or Canadian setting). Conclusions Functional strength training and higher-intensity physiotherapy may result in lower costs and improved health outcomes. However, these results should be interpreted with caution. PMID:26366241

Is Weight Training Safe during Pregnancy?

ERIC Educational Resources Information Center

Work, Janis A.

1989-01-01

Examines the opinions of several experts on the safety of weight training during pregnancy, noting that no definitive research on weight training alone has been done. Experts agree that low-intensity weight training probably poses no harm for mother or fetus; exercise programs should be individualized. (SM)

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

Intensive Intervention Practice Guide: System of Least Prompts

ERIC Educational Resources Information Center

Walte, Samantha; Brown, Christerralyn; Wallace, Theresa

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

Intensive Intervention Practice Guide: School-Based Functional Analysis

ERIC Educational Resources Information Center

Pennington, Brittany; Pokorski, Elizabeth A.; Kumm, Skip; Sterrett, Brittany I.

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

"As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players.

PubMed

Gray, Rob; Beilock, Sun L; Carr, Thomas H

2007-08-01

A virtual-reality batting task compared novice and expert baseball players' ability to predict the outcomes of their swings as well as the susceptibility of these outcome predictions to hindsight bias--a measure of strength and resistance to distortion of memory for predicted action outcomes. During each swing the simulation stopped when the bat met the ball. Batters marked where on the field they thought the ball would land. Correct feedback was then displayed, after which batters attempted to remark the location they had indicated prior to feedback. Expert batters were more accurate than less-skilled individuals in the initial marking and showed less hindsight bias in the postfeedback marking. Furthermore, experts' number of hits in the previous block of trials was positively correlated with prediction accuracy and negatively correlated with hindsight bias. The reverse was true for novices. Thus the ability to predict the outcome of one's performance before such information is available in the environment is not only based on one's overall skill level, but how one is performing at a given moment.

The nutrition advisor expert system

NASA Technical Reports Server (NTRS)

Huse, Scott M.; Shyne, Scott S.

1991-01-01

The Nutrition Advisor Expert System (NAES) is an expert system written in the C Language Integrated Production System (CLIPS). NAES provides expert knowledge and guidance into the complex world of nutrition management by capturing the knowledge of an expert and placing it at the user's fingertips. Specifically, NAES enables the user to: (1) obtain precise nutrition information for food items; (2) perform nutritional analysis of meal(s), flagging deficiencies based upon the U.S. Recommended Daily Allowances; (3) predict possible ailments based upon observed nutritional deficiency trends; (4) obtain a top ten listing of food items for a given nutrient; and (5) conveniently upgrade the data base. An explanation facility for the ailment prediction feature is also provided to document the reasoning process.

Development of a risk-screening tool for cancer survivors to participate in unsupervised moderate- to vigorous-intensity exercise: results from a survey study.

PubMed

Brown, Justin C; Ko, Emily M; Schmitz, Kathryn H

2015-02-01

The health benefits of exercise increase in dose-response fashion among cancer survivors. However, it is unclear how to identify cancer survivors who may require a pre-exercise evaluation before they progress from the common recommendation of walking to unsupervised moderate- to vigorous-intensity exercise. To clarify how to identify cancer survivors who should undergo a pre-exercise evaluation before they progress from the common recommendation of walking to unsupervised moderate- to vigorous-intensity exercise. Electronic survey. Forty-seven (n = 47) experts in the field of exercise physiology, rehabilitation medicine, and cancer survivorship. Not applicable. We synthesized peer-reviewed guidelines for exercise and cancer survivorship and identified 82 health factors that may warrant a pre-exercise evaluation before a survivor engages in unsupervised moderate- to vigorous-intensity exercise. The 82 health factors were classified into 3 domains: (1) clinical health factors; (2) comorbidity and device health factors; and (3) medications. We surveyed a sample of experts asking them to identify which of the 82 health factors among cancer survivors would indicate the need for a pre-exercise evaluation before they engaged in moderate- to vigorous-intensity exercise. The response rate to our survey was 75% (n = 47). Across the 3 domains of health factors, acute symptoms, comorbidities, and medications related to cardiovascular disease were agreed on to indicate a pre-exercise evaluation for survivors before they engaged in unsupervised moderate- to vigorous-intensity exercise. Other health factors in the survey included hematologic, musculoskeletal, systemic, gastrointestinal, pulmonary, and neurological symptoms and comorbidities. Eighteen experts (38%) said it was difficult to provide absolute answers because no 2 patients are alike, and their decisions are made on a case-by-case basis. The results from this expert survey will help to identify which cancer survivors should undergo a pre-exercise evaluation before they engage in unsupervised moderate- to vigorous-intensity exercise. Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

What do people mean when speaking of evilness?

PubMed

Quiles, Ma Nieves; Morera, Ma Dolores; Correa, Ana Delia; Leyens, Jacques Philippe

2010-11-01

The term evilness started to become popular in social psychology after the publication in 1999 of the special issue edited by Arthur G. Miller, "Perspectives on evil and violence". It is usually used to define behaviors that are extremely and strongly harmful. However, the concept is still imprecise and needs to be empirically delineated. This article attempts to answer the following questions. What is evilness? What is the difference between aggression and evilness? We conducted several studies with three goals: to analyze how laypersons and experts define evilness, to verify whether laypeople distinguish between different intensities of evilness, and to determine the dimensions that predict aggression and evilness. The results offer preliminary answers to the three questions.

A new metric for detecting change in slowly evolving brain tumors: validation in meningioma patients.

PubMed

Pohl, Kilian M; Konukoglu, Ender; Novellas, Sebastian; Ayache, Nicholas; Fedorov, Andriy; Talos, Ion-Florin; Golby, Alexandra; Wells, William M; Kikinis, Ron; Black, Peter M

2011-03-01

Change detection is a critical component in the diagnosis and monitoring of many slowly evolving pathologies. This article describes a semiautomatic monitoring approach using longitudinal medical images. We test the method on brain scans of patients with meningioma, which experts have found difficult to monitor because the tumor evolution is very slow and may be obscured by artifacts related to image acquisition. We describe a semiautomatic procedure targeted toward identifying difficult-to-detect changes in brain tumor imaging. The tool combines input from a medical expert with state-of-the-art technology. The software is easy to calibrate and, in less than 5 minutes, returns the total volume of tumor change in mm. We test the method on postgadolinium, T1-weighted magnetic resonance images of 10 patients with meningioma and compare our results with experts' findings. We also perform benchmark testing with synthetic data. Our experiments indicated that experts' visual inspections are not sensitive enough to detect subtle growth. Measurements based on experts' manual segmentations were highly accurate but also labor intensive. The accuracy of our approach was comparable to the experts' results. However, our approach required far less user input and generated more consistent measurements. The sensitivity of experts' visual inspection is often too low to detect subtle growth of meningiomas from longitudinal scans. Measurements based on experts' segmentation are highly accurate but generally too labor intensive for standard clinical settings. We described an alternative metric that provides accurate and robust measurements of subtle tumor changes while requiring a minimal amount of user input.

Experts' recommendations for the management of cardiogenic shock in children.

PubMed

Brissaud, Olivier; Botte, Astrid; Cambonie, Gilles; Dauger, Stéphane; de Saint Blanquat, Laure; Durand, Philippe; Gournay, Véronique; Guillet, Elodie; Laux, Daniela; Leclerc, Francis; Mauriat, Philippe; Boulain, Thierry; Kuteifan, Khaldoun

2016-12-01

Cardiogenic shock which corresponds to an acute state of circulatory failure due to impairment of myocardial contractility is a very rare disease in children, even more than in adults. To date, no international recommendations regarding its management in critically ill children are available. An experts' recommendations in adult population have recently been made (Levy et al. Ann Intensive Care 5(1):52, 2015; Levy et al. Ann Intensive Care 5(1):26, 2015). We present herein recommendations for the management of cardiogenic shock in children, developed with the grading of recommendations' assessment, development, and evaluation system by an expert group of the Groupe Francophone de Réanimation et Urgences Pédiatriques (French Group for Pediatric Intensive Care and Emergencies). The recommendations cover four major fields of application such as: recognition of early signs of shock and the patient pathway, management principles and therapeutic goals, monitoring hemodynamic and biological variables, and circulatory support (indications, techniques, organization, and transfer criteria). Major principle care for children with cardiogenic shock is primarily based on clinical and echocardiographic assessment. There are few drugs reported as effective in childhood in the medical literature. The use of circulatory support should be facilitated in terms of organization and reflected in the centers that support these children. Children with cardiogenic shock are vulnerable and should be followed regularly by intensivist cardiologists and pediatricians. The experts emphasize the multidisciplinary nature of management of children with cardiogenic shock and the importance of effective communication between emergency medical assistance teams (SAMU), mobile pediatric emergency units (SMUR), pediatric emergency departments, pediatric cardiology and cardiac surgery departments, and pediatric intensive care units.

Toward a consistent model for strain accrual and release for the New Madrid Seismic Zone, central United States

USGS Publications Warehouse

Hough, S.E.; Page, M.

2011-01-01

At the heart of the conundrum of seismogenesis in the New Madrid Seismic Zone is the apparently substantial discrepancy between low strain rate and high recent seismic moment release. In this study we revisit the magnitudes of the four principal 1811–1812 earthquakes using intensity values determined from individual assessments from four experts. Using these values and the grid search method of Bakun and Wentworth (1997), we estimate magnitudes around 7.0 for all four events, values that are significantly lower than previously published magnitude estimates based on macroseismic intensities. We further show that the strain rate predicted from postglacial rebound is sufficient to produce a sequence with the moment release of one Mmax6.8 every 500 years, a rate that is much lower than previous estimates of late Holocene moment release. However, Mw6.8 is at the low end of the uncertainty range inferred from analysis of intensities for the largest 1811–1812 event. We show that Mw6.8 is also a reasonable value for the largest main shock given a plausible rupture scenario. One can also construct a range of consistent models that permit a somewhat higher Mmax, with a longer average recurrence rate. It is thus possible to reconcile predicted strain and seismic moment release rates with alternative models: one in which 1811–1812 sequences occur every 500 years, with the largest events being Mmax∼6.8, or one in which sequences occur, on average, less frequently, with Mmax of ∼7.0. Both models predict that the late Holocene rate of activity will continue for the next few to 10 thousand years.

[Model for unplanned self extubation of ICU patients using system dynamics approach].

PubMed

Song, Yu Gil; Yun, Eun Kyoung

2015-04-01

In this study a system dynamics methodology was used to identify correlation and nonlinear feedback structure among factors affecting unplanned extubation (UE) of ICU patients and to construct and verify a simulation model. Factors affecting UE were identified through a theoretical background established by reviewing literature and preceding studies and referencing various statistical data. Related variables were decided through verification of content validity by an expert group. A causal loop diagram (CLD) was made based on the variables. Stock & Flow modeling using Vensim PLE Plus Version 6.0 b was performed to establish a model for UE. Based on the literature review and expert verification, 18 variables associated with UE were identified and CLD was prepared. From the prepared CLD, a model was developed by converting to the Stock & Flow Diagram. Results of the simulation showed that patient stress, patient in an agitated state, restraint application, patient movability, and individual intensive nursing were variables giving the greatest effect to UE probability. To verify agreement of the UE model with real situations, simulation with 5 cases was performed. Equation check and sensitivity analysis on TIME STEP were executed to validate model integrity. Results show that identification of a proper model enables prediction of UE probability. This prediction allows for adjustment of related factors, and provides basic data do develop nursing interventions to decrease UE.

What do the experts know? Calibration, precision, and the wisdom of crowds among forensic handwriting experts.

PubMed

Martire, Kristy A; Growns, Bethany; Navarro, Danielle J

2018-04-17

Forensic handwriting examiners currently testify to the origin of questioned handwriting for legal purposes. However, forensic scientists are increasingly being encouraged to assign probabilities to their observations in the form of a likelihood ratio. This study is the first to examine whether handwriting experts are able to estimate the frequency of US handwriting features more accurately than novices. The results indicate that the absolute error for experts was lower than novices, but the size of the effect is modest, and the overall error rate even for experts is large enough as to raise questions about whether their estimates can be sufficiently trustworthy for presentation in courts. When errors are separated into effects caused by miscalibration and those caused by imprecision, we find systematic differences between individuals. Finally, we consider several ways of aggregating predictions from multiple experts, suggesting that quite substantial improvements in expert predictions are possible when a suitable aggregation method is used.

Physiotherapy in the intensive care unit: an evidence-based, expert driven, practical statement and rehabilitation recommendations

PubMed Central

Sommers, Juultje; Engelbert, Raoul HH; Dettling-Ihnenfeldt, Daniela; Gosselink, Rik; Spronk, Peter E; Nollet, Frans; van der Schaaf, Marike

2015-01-01

Objective: To develop evidence-based recommendations for effective and safe diagnostic assessment and intervention strategies for the physiotherapy treatment of patients in intensive care units. Methods: We used the EBRO method, as recommended by the ‘Dutch Evidence Based Guideline Development Platform’ to develop an ‘evidence statement for physiotherapy in the intensive care unit’. This method consists of the identification of clinically relevant questions, followed by a systematic literature search, and summary of the evidence with final recommendations being moderated by feedback from experts. Results: Three relevant clinical domains were identified by experts: criteria to initiate treatment; measures to assess patients; evidence for effectiveness of treatments. In a systematic literature search, 129 relevant studies were identified and assessed for methodological quality and classified according to the level of evidence. The final evidence statement consisted of recommendations on eight absolute and four relative contra-indications to mobilization; a core set of nine specific instruments to assess impairments and activity restrictions; and six passive and four active effective interventions, with advice on (a) physiological measures to observe during treatment (with stopping criteria) and (b) what to record after the treatment. Conclusions: These recommendations form a protocol for treating people in an intensive care unit, based on best available evidence in mid-2014. PMID:25681407

Physiotherapy in the intensive care unit: an evidence-based, expert driven, practical statement and rehabilitation recommendations.

PubMed

Sommers, Juultje; Engelbert, Raoul H H; Dettling-Ihnenfeldt, Daniela; Gosselink, Rik; Spronk, Peter E; Nollet, Frans; van der Schaaf, Marike

2015-11-01

To develop evidence-based recommendations for effective and safe diagnostic assessment and intervention strategies for the physiotherapy treatment of patients in intensive care units. We used the EBRO method, as recommended by the 'Dutch Evidence Based Guideline Development Platform' to develop an 'evidence statement for physiotherapy in the intensive care unit'. This method consists of the identification of clinically relevant questions, followed by a systematic literature search, and summary of the evidence with final recommendations being moderated by feedback from experts. Three relevant clinical domains were identified by experts: criteria to initiate treatment; measures to assess patients; evidence for effectiveness of treatments. In a systematic literature search, 129 relevant studies were identified and assessed for methodological quality and classified according to the level of evidence. The final evidence statement consisted of recommendations on eight absolute and four relative contra-indications to mobilization; a core set of nine specific instruments to assess impairments and activity restrictions; and six passive and four active effective interventions, with advice on (a) physiological measures to observe during treatment (with stopping criteria) and (b) what to record after the treatment. These recommendations form a protocol for treating people in an intensive care unit, based on best available evidence in mid-2014. © The Author(s) 2015.

The effects of gender composition on women's experience in math work groups.

PubMed

Grover, Sarah S; Ito, Tiffany A; Park, Bernadette

2017-06-01

The present studies tested a model outlining the effects of group gender composition on self- and others' perceptions of women's math ability in a truly interactive setting with groups composed entirely of naïve participants (N = 158 4-person groups across 3 studies). One woman in each group was designated to be the "expert" by having her complete a tutorial that gave her task-relevant knowledge for a subsequent group task. Group gender composition was hypothesized to influence perceptions of women's math ability through intrapersonal processes (stereotype threat effects on performance) and interpersonal processes (social cohesion between the expert and other group members). Group composition affected the experts' performance in the group math task, but importantly, it also affected their social cohesion with group members. Moreover, both of these effects-lowered performance and poorer social cohesion in male-dominated groups-made independent contributions in accounting for group gender composition effects on perceptions of women's math ability (Studies 1 and 2). Boundary conditions were examined in a 3rd study. Women who had a history of excelling in math and had chosen a math-intensive STEM major were selected to be the designated experts. We predicted and found this would be sufficient to eliminate the effect of group gender composition on interpersonal processes, and correspondingly the effect on women's perceived math ability. Interestingly (and consistent with past work on stereotype threat effects among highly domain-identified individuals), there were continued performance differences indicative of effects on intrapersonal processes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation

PubMed Central

Morris, Alan; Burgon, Nathan; McGann, Christopher; MacLeod, Robert; Cates, Joshua

2013-01-01

Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts. PMID:24236224

Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation

NASA Astrophysics Data System (ADS)

Perry, Daniel; Morris, Alan; Burgon, Nathan; McGann, Christopher; MacLeod, Robert; Cates, Joshua

2012-03-01

Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts.

Computer Based Expert Systems.

ERIC Educational Resources Information Center

Parry, James D.; Ferrara, Joseph M.

1985-01-01

Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

Predicting disease progression from short biomarker series using expert advice algorithm

NASA Astrophysics Data System (ADS)

Morino, Kai; Hirata, Yoshito; Tomioka, Ryota; Kashima, Hisashi; Yamanishi, Kenji; Hayashi, Norihiro; Egawa, Shin; Aihara, Kazuyuki

2015-05-01

Well-trained clinicians may be able to provide diagnosis and prognosis from very short biomarker series using information and experience gained from previous patients. Although mathematical methods can potentially help clinicians to predict the progression of diseases, there is no method so far that estimates the patient state from very short time-series of a biomarker for making diagnosis and/or prognosis by employing the information of previous patients. Here, we propose a mathematical framework for integrating other patients' datasets to infer and predict the state of the disease in the current patient based on their short history. We extend a machine-learning framework of ``prediction with expert advice'' to deal with unstable dynamics. We construct this mathematical framework by combining expert advice with a mathematical model of prostate cancer. Our model predicted well the individual biomarker series of patients with prostate cancer that are used as clinical samples.

Predicting disease progression from short biomarker series using expert advice algorithm.

PubMed

Morino, Kai; Hirata, Yoshito; Tomioka, Ryota; Kashima, Hisashi; Yamanishi, Kenji; Hayashi, Norihiro; Egawa, Shin; Aihara, Kazuyuki

2015-05-20

Well-trained clinicians may be able to provide diagnosis and prognosis from very short biomarker series using information and experience gained from previous patients. Although mathematical methods can potentially help clinicians to predict the progression of diseases, there is no method so far that estimates the patient state from very short time-series of a biomarker for making diagnosis and/or prognosis by employing the information of previous patients. Here, we propose a mathematical framework for integrating other patients' datasets to infer and predict the state of the disease in the current patient based on their short history. We extend a machine-learning framework of "prediction with expert advice" to deal with unstable dynamics. We construct this mathematical framework by combining expert advice with a mathematical model of prostate cancer. Our model predicted well the individual biomarker series of patients with prostate cancer that are used as clinical samples.

An evaluation of selected (Q)SARs/expert systems for predicting skin sensitisation potential.

PubMed

Fitzpatrick, J M; Roberts, D W; Patlewicz, G

2018-06-01

Predictive testing to characterise substances for their skin sensitisation potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximisation Test (GPMT). In recent years, EU regulations, have provided a strong incentive to develop non-animal alternatives, such as expert systems software. Here we selected three different types of expert systems: VEGA (statistical), Derek Nexus (knowledge-based) and TIMES-SS (hybrid), and evaluated their performance using two large sets of animal data: one set of 1249 substances from eChemportal and a second set of 515 substances from NICEATM. A model was considered successful at predicting skin sensitisation potential if it had at least the same balanced accuracy as the LLNA and the GPMT had in predicting the other outcomes, which ranged from 79% to 86%. We found that the highest balanced accuracy of any of the expert systems evaluated was 65% when making global predictions. For substances within the domain of TIMES-SS, however, balanced accuracies for the two datasets were found to be 79% and 82%. In those cases where a chemical was within the TIMES-SS domain, the TIMES-SS skin sensitisation hazard prediction had the same confidence as the result from LLNA or GPMT.

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

PubMed

Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk

2015-05-01

To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Tools for outcome prediction in patients with community acquired pneumonia.

PubMed

Khan, Faheem; Owens, Mark B; Restrepo, Marcos; Povoa, Pedro; Martin-Loeches, Ignacio

2017-02-01

Community-acquired pneumonia (CAP) is one of the most common causes of mortality world-wide. The mortality rate of patients with CAP is influenced by the severity of the disease, treatment failure and the requirement for hospitalization and/or intensive care unit (ICU) management, all of which may be predicted by biomarkers and clinical scoring systems. Areas covered: We review the recent literature examining the efficacy of established and newly-developed clinical scores, biological and inflammatory markers such as C-Reactive protein (CRP), procalcitonin (PCT) and Interleukin-6 (IL-6), whether used alone or in conjunction with clinical severity scores to assess the severity of CAP, predict treatment failure, guide acute in-hospital or ICU admission and predict mortality. Expert commentary: The early prediction of treatment failure using clinical scores and biomarkers plays a developing role in improving survival of patients with CAP by identifying high-risk patients requiring hospitalization or ICU admission; and may enable more efficient allocation of resources. However, it is likely that combinations of scoring systems and biomarkers will be of greater use than individual markers. Further larger studies are needed to corroborate the additive value of these markers to clinical prediction scores to provide a safer and more effective assessment tool for clinicians.

Expert Consensus on the Management of Patients with Postmenopausal Osteoporosis in the Spanish Healthcare System.

PubMed

Del Pino-Montes, Javier; Blanch, Josep; Nogués, Xavier; Moro, María Jesús; Valero, María Del Carmen; Canals, Laura; Lizán, Luis

2016-04-01

The management of postmenopausal osteoporosis (PMO) in routine clinical practice differs considerably from guideline recommendations. The objective of our study was to reach a consensus on the management of PMO, considering prevention, diagnosis, treatment and follow-up, according to expert opinion in Spain. A two-round Delphi technique was conducted, including 38 experts. The questionnaire contained 35 sections, each one including 1-10 questions (n = 308) based on a literature review and contributions from the scientific steering committee. Each question was scored by experts from the current (1 = no occurrence, 9 = occurrence in all cases), wish (1 = total rejection; 9 = wish) and prediction (1 = no occurrence at all; 9 = occurs with maximum probability) perspectives. Consensus (wish and prediction perspectives) was considered when ≥75% of experts scored 7-9 (agreement) or 1-3 (disagreement). Overall, consensus was achieved on 75% of questions. While protocols of clinical management and consultation/referral should be followed, their implementation is unlikely. Furthermore, the medical specialties currently involved in PMO management are poorly defined. PMO patients without fracture should be managed (prevention, diagnosis, treatment and follow-up) in both primary care and rheumatology settings; however, experts predicted that only treatment and follow-up will be assumed by these specialties. A multidisciplinary team should be involved in patients with fracture. No assessment tools are usually applied, and prediction indicated that they will not be used. Efforts should be focused on questions with high divergence between wishes and predictions, defining actions that will improve PMO management. Collaboration between scientific societies and health authorities to address the identified opportunities of improvement is proposed. Amgen S.A.

Intensive Intervention Practice Guide: Explicit Instruction in Reading Comprehension for Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Braun, Gina; Austin, Christy; Ledbetter-Cho, Katherine

2017-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

Shaping beliefs in experimental markets for expert services: Guilt aversion and the impact of promises and money-burning options.

PubMed

Beck, Adrian; Kerschbamer, Rudolf; Qiu, Jianying; Sutter, Matthias

2013-09-01

In a credence goods game with an expert and a consumer, we study experimentally the impact of two devices that are predicted to induce consumer-friendly behavior if the expert has a propensity to feel guilty when he believes that he violates the consumer's payoff expectations: (i) an opportunity for the expert to make a non-binding promise; and (ii) an opportunity for the consumer to burn money. In belief-based guilt aversion theory the first opportunity shapes an expert's behavior if an appropriate promise is made and if it is expected to be believed by the consumer; by contrast, the second opportunity might change behavior even though this option is never used along the predicted path. Experimental results confirm the behavioral relevance of (i) but fail to confirm (ii).

Pedophilia: an evaluation of diagnostic and risk prediction methods.

PubMed

Wilson, Robin J; Abracen, Jeffrey; Looman, Jan; Picheca, Janice E; Ferguson, Meaghan

2011-06-01

One hundred thirty child sexual abusers were diagnosed using each of following four methods: (a) phallometric testing, (b) strict application of Diagnostic and Statistical Manual of Mental Disorders (4th ed., text revision [DSM-IV-TR]) criteria, (c) Rapid Risk Assessment of Sex Offender Recidivism (RRASOR) scores, and (d) "expert" diagnoses rendered by a seasoned clinician. Comparative utility and intermethod consistency of these methods are reported, along with recidivism data indicating predictive validity for risk management. Results suggest that inconsistency exists in diagnosing pedophilia, leading to diminished accuracy in risk assessment. Although the RRASOR and DSM-IV-TR methods were significantly correlated with expert ratings, RRASOR and DSM-IV-TR were unrelated to each other. Deviant arousal was not associated with any of the other methods. Only the expert ratings and RRASOR scores were predictive of sexual recidivism. Logistic regression analyses showed that expert diagnosis did not add to prediction of sexual offence recidivism over and above RRASOR alone. Findings are discussed within a context of encouragement of clinical consistency and evidence-based practice regarding treatment and risk management of those who sexually abuse children.

Logopenic and Nonfluent Variants of Primary Progressive Aphasia Are Differentiated by Acoustic Measures of Speech Production

PubMed Central

Ballard, Kirrie J.; Savage, Sharon; Leyton, Cristian E.; Vogel, Adam P.; Hornberger, Michael; Hodges, John R.

2014-01-01

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. In this study acoustic measures of speech in conjunction with voxel-based morphometry were used to determine the success of the measures as an adjunct to diagnosis and to explore the neural basis of apraxia of speech in nfvPPA. Forty-one patients (21 lvPPA, 20 nfvPPA) were recruited from a consecutive sample with suspected frontotemporal dementia. Patients were diagnosed using the current gold-standard of expert perceptual judgment, based on presence/absence of particular speech features during speaking tasks. Seventeen healthy age-matched adults served as controls. MRI scans were available for 11 control and 37 PPA cases; 23 of the PPA cases underwent amyloid ligand PET imaging. Measures, corresponding to perceptual features of apraxia of speech, were periods of silence during reading and relative vowel duration and intensity in polysyllable word repetition. Discriminant function analyses revealed that a measure of relative vowel duration differentiated nfvPPA cases from both control and lvPPA cases (r 2 = 0.47) with 88% agreement with expert judgment of presence of apraxia of speech in nfvPPA cases. VBM analysis showed that relative vowel duration covaried with grey matter intensity in areas critical for speech motor planning and programming: precentral gyrus, supplementary motor area and inferior frontal gyrus bilaterally, only affected in the nfvPPA group. This bilateral involvement of frontal speech networks in nfvPPA potentially affects access to compensatory mechanisms involving right hemisphere homologues. Measures of silences during reading also discriminated the PPA and control groups, but did not increase predictive accuracy. Findings suggest that a measure of relative vowel duration from of a polysyllable word repetition task may be sufficient for detecting most cases of apraxia of speech and distinguishing between nfvPPA and lvPPA. PMID:24587083

Update of an occupational asthma-specific job exposure matrix to assess exposure to 30 specific agents.

PubMed

Le Moual, Nicole; Zock, Jan-Paul; Dumas, Orianne; Lytras, Theodore; Andersson, Eva; Lillienberg, Linnéa; Schlünssen, Vivi; Benke, Geza; Kromhout, Hans

2018-07-01

We aimed to update an asthmagen job exposure matrix (JEM) developed in the late 1990s. Main reasons were: the number of suspected and recognised asthmagens has since tripled; understanding of the aetiological role of irritants in asthma and methodological insights in application of JEMs have emerged in the period. For each agent of the new occupational asthma-specific JEM (OAsJEM), a working group of three experts out of eight evaluated exposure for each International Standard Classification of Occupations, 1988 (ISCO-88) job code into three categories: 'high' (high probability of exposure and moderate-to-high intensity), 'medium' (low-to-moderate probability or low intensity) and 'unexposed'. Within a working group, experts evaluated exposures independently from each other. If expert assessments were inconsistent the final decision was taken by consensus. Specificity was favoured over sensitivity, that is, jobs were classified with high exposure only if the probability of exposure was high and the intensity moderate-to-high. In the final review, all experts checked assigned exposures and proposed/improved recommendations for expert re-evaluation after default application of the JEM. The OAsJEM covers exposures to 30 sensitisers/irritants, including 12 newly recognised, classified into seven broad groups. Initial agreement between the three experts was mostly fair to moderate (κ values 0.2-0.5). Out of 506 ISCO-88 codes, the majority was classified as unexposed (from 82.6% (organic solvents) to 99.8% (persulfates)) and a minority as 'high-exposed' (0.2% (persulfates) to 2.6% (organic solvents)). The OAsJEM developed to improve occupational exposure assessment may improve evaluations of associations with asthma in epidemiological studies and contribute to assessment of the burden of work-related asthma. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Human Emotion Experiences Can Be Predicted on Theoretical Grounds: Evidence from Verbal Labeling

PubMed Central

Scherer, Klaus R.; Meuleman, Ben

2013-01-01

In an effort to demonstrate that the verbal labeling of emotional experiences obeys lawful principles, we tested the feasibility of using an expert system called the Geneva Emotion Analyst (GEA), which generates predictions based on an appraisal theory of emotion. Several thousand respondents participated in an Internet survey that applied GEA to self-reported emotion experiences. Users recalled appraisals of emotion-eliciting events and labeled the experienced emotion with one or two words, generating a massive data set on realistic, intense emotions in everyday life. For a final sample of 5969 respondents we show that GEA achieves a high degree of predictive accuracy by matching a user’s appraisal input to one of 13 theoretically predefined emotion prototypes. The first prediction was correct in 51% of the cases and the overall diagnosis was considered as at least partially correct or appropriate in more than 90% of all cases. These results support a component process model that encourages focused, hypothesis-guided research on elicitation and differentiation, memory storage and retrieval, and categorization and labeling of emotion episodes. We discuss the implications of these results for the study of emotion terms in natural language semantics. PMID:23483988

SeTES, a Self-Teaching Expert System for the analysis, design and prediction of gas production from shales and a prototype for a new generation of Expert Systems in the Earth Sciences

NASA Astrophysics Data System (ADS)

Kuzma, H. A.; Boyle, K.; Pullman, S.; Reagan, M. T.; Moridis, G. J.; Blasingame, T. A.; Rector, J. W.; Nikolaou, M.

2010-12-01

A Self Teaching Expert System (SeTES) is being developed for the analysis, design and prediction of gas production from shales. An Expert System is a computer program designed to answer questions or clarify uncertainties that its designers did not necessarily envision which would otherwise have to be addressed by consultation with one or more human experts. Modern developments in computer learning, data mining, database management, web integration and cheap computing power are bringing the promise of expert systems to fruition. SeTES is a partial successor to Prospector, a system to aid in the identification and evaluation of mineral deposits developed by Stanford University and the USGS in the late 1970s, and one of the most famous early expert systems. Instead of the text dialogue used in early systems, the web user interface of SeTES helps a non-expert user to articulate, clarify and reason about a problem by navigating through a series of interactive wizards. The wizards identify potential solutions to queries by retrieving and combining together relevant records from a database. Inferences, decisions and predictions are made from incomplete and noisy inputs using a series of probabilistic models (Bayesian Networks) which incorporate records from the database, physical laws and empirical knowledge in the form of prior probability distributions. The database is mainly populated with empirical measurements, however an automatic algorithm supplements sparse data with synthetic data obtained through physical modeling. This constitutes the mechanism for how SeTES self-teaches. SeTES’ predictive power is expected to grow as users contribute more data into the system. Samples are appropriately weighted to favor high quality empirical data over low quality or synthetic data. Finally, a set of data visualization tools digests the output measurements into graphical outputs.

SigmaCLIPSE = presentation management + NASA CLI PS + SQL

NASA Technical Reports Server (NTRS)

Weiss, Bernard P., Jr.

1990-01-01

SigmaCLIPSE provides an expert systems and 'intelligent' data base development program for diverse systems integration environments that require support for automated reasoning and expert systems technology, presentation management, and access to 'intelligent' SQL data bases. The SigmaCLIPSE technology and and its integrated ability to access 4th generation application development and decision support tools through a portable SQL interface, comprises a sophisticated software development environment for solving knowledge engineering and expert systems development problems in information intensive commercial environments -- financial services, health care, and distributed process control -- where the expert system must be extendable -- a major architectural advantage of NASA CLIPS. SigmaCLIPSE is a research effort intended to test the viability of merging SQL data bases with expert systems technology.

Can human experts predict solubility better than computers?

PubMed

Boobier, Samuel; Osbourn, Anne; Mitchell, John B O

2017-12-13

In this study, we design and carry out a survey, asking human experts to predict the aqueous solubility of druglike organic compounds. We investigate whether these experts, drawn largely from the pharmaceutical industry and academia, can match or exceed the predictive power of algorithms. Alongside this, we implement 10 typical machine learning algorithms on the same dataset. The best algorithm, a variety of neural network known as a multi-layer perceptron, gave an RMSE of 0.985 log S units and an R 2 of 0.706. We would not have predicted the relative success of this particular algorithm in advance. We found that the best individual human predictor generated an almost identical prediction quality with an RMSE of 0.942 log S units and an R 2 of 0.723. The collection of algorithms contained a higher proportion of reasonably good predictors, nine out of ten compared with around half of the humans. We found that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median generated excellent predictivity. While our consensus human predictor achieved very slightly better headline figures on various statistical measures, the difference between it and the consensus machine learning predictor was both small and statistically insignificant. We conclude that human experts can predict the aqueous solubility of druglike molecules essentially equally well as machine learning algorithms. We find that, for either humans or algorithms, combining individual predictions into a consensus predictor by taking their median is a powerful way of benefitting from the wisdom of crowds.

"A Prophecy for the Arts" in Higher Education

ERIC Educational Resources Information Center

Merrion, Margaret

2009-01-01

This article presents a Delphi study that captured a myriad of predictions that represent the best thinking of a panel of creative minds, experts in a variety of arts and with many years of experience as arts leaders. Predictions provide a set of interlinked challenges and opportunities. In this study, the experts forecast changes in students that…

Intensive Intervention Practice Guide: Intensifying Check-In Check-Out for Students with or At-Risk for Emotional or Behavioral Disabilities

ERIC Educational Resources Information Center

Kunemund, Rachel; Majeika, Caitlyn; De La Cruz, Veronica Mellado; Wilkinson, Sarah

2016-01-01

The National Center for Leadership in Intensive Intervention (NCLII), a consortium funded by the Office of Special Education Programs (OSEP), prepares special education leaders to become experts in research on intensive intervention for students with disabilities who have persistent and severe academic (e.g., reading and math) and behavioral…

Take-the-best in expert-novice decision strategies for residential burglary.

PubMed

Garcia-Retamero, Rocio; Dhami, Mandeep K

2009-02-01

We examined the decision strategies and cue use of experts and novices in a consequential domain: crime. Three participant groups decided which of two residential properties was more likely to be burgled, on the basis of eight cues such as location of the property. The two expert groups were experienced burglars and police officers, and the novice group was composed of graduate students. We found that experts' choices were best predicted by a lexicographic heuristic strategy called take-the-best that implies noncompensatory information processing, whereas novices' choices were best predicted by a weighted additive linear strategy that implies compensatory processing. The two expert groups, however, differed in the cues they considered important in making their choices, and the police officers were actually more similar to novices in this regard. These findings extend the literature on judgment, decision making, and expertise, and have implications for criminal justice policy.

Fuzzy logic based expert system for the treatment of mobile tooth.

PubMed

Mago, Vijay Kumar; Mago, Anjali; Sharma, Poonam; Mago, Jagmohan

2011-01-01

The aim of this research work is to design an expert system to assist dentist in treating the mobile tooth. There is lack of consistency among dentists in choosing the treatment plan. Moreover, there is no expert system currently available to verify and support such decision making in dentistry. A Fuzzy Logic based expert system has been designed to accept imprecise and vague values of dental sign-symptoms related to mobile tooth and the system suggests treatment plan(s). The comparison of predictions made by the system with those of the dentist is conducted. Chi-square Test of homogeneity is conducted and it is found that the system is capable of predicting accurate results. With this system, dentist feels more confident while planning the treatment of mobile tooth as he can verify his decision with the expert system. The authors also argue that Fuzzy Logic provides an appropriate mechanism to handle imprecise values of dental domain.

Shaping beliefs in experimental markets for expert services: Guilt aversion and the impact of promises and money-burning options☆☆☆

PubMed Central

Beck, Adrian; Kerschbamer, Rudolf; Qiu, Jianying; Sutter, Matthias

2013-01-01

In a credence goods game with an expert and a consumer, we study experimentally the impact of two devices that are predicted to induce consumer-friendly behavior if the expert has a propensity to feel guilty when he believes that he violates the consumerʼs payoff expectations: (i) an opportunity for the expert to make a non-binding promise; and (ii) an opportunity for the consumer to burn money. In belief-based guilt aversion theory the first opportunity shapes an expertʼs behavior if an appropriate promise is made and if it is expected to be believed by the consumer; by contrast, the second opportunity might change behavior even though this option is never used along the predicted path. Experimental results confirm the behavioral relevance of (i) but fail to confirm (ii). PMID:24003266

An infrastructure for data-intensive seismology using ADMIRE: laying the bricks for a new data highway

NASA Astrophysics Data System (ADS)

Trani, L.; Spinuso, A.; Galea, M.; Atkinson, M.; Van Eck, T.; Vilotte, J.

2011-12-01

The data bonanza generated by today's digital revolution is forcing scientists to rethink their methodologies and working practices. Traditional approaches to knowledge discovery are pushed to their limit and struggle to keep apace with the data flows produced by modern systems. This work shows how the ADMIRE data-intensive architecture supports seismologists by enabling them to focus on their scientific goals and questions, abstracting away the underlying technology platform that enacts their data integration and analysis tasks. ADMIRE accomplishes this partly by recognizing 3 different types of experts that require clearly defined interfaces between their interaction: the domain expert who is the application specialist, the data-analysis expert who is a specialist in extracting information from data, and the data-intensive engineer who develops the infrastructure for data-intensive computation. In order to provide a context in which each category of expert may flourish, ADMIRE uses a 3-level architecture: the upper - tool - level supports the work of both domain and data-analysis experts, housing an extensive and evolving set of portals, tools and development environments; the lower - enactment - level houses a large and dynamic community of providers delivering data and data-intensive enactment environments as an evolving infrastructure that supports all of the work underway in the upper layer. Most data-intensive engineers work here; the crucial innovation lies in the middle level, a gateway that is a tightly defined and stable interface through which the two diverse and dynamic upper and lower layers communicate. This is a minimal and simple protocol and language (DISPEL), ultimately to be controlled by standards, so that the upper and lower communities may invest, secure in the knowledge that changes in this interface will be carefully managed. We implemented a well-established procedure for processing seismic ambient noise on the prototype architecture. The primary goal was to evaluate its capabilities for large-scale integration and analysis of distributed data. A secondary goal was to gauge its potential and the added value that it might bring to the seismological community. Though still in its infant state, the architecture met the demands of our use case and promises to cater for our future requirements. We shall continue to develop its capabilities as part of an EU funded project VERCE - Virtual Earthquake and Seismology Research Community for Europe. VERCE aims to significantly advance our understanding of the Earth in order to aid society in its management of natural resources and hazards. Its strategy is to enable seismologists to fully exploit the under-utilized wealth of seismic data, and key to this is a data-intensive computation framework adapted to the scale and diversity of the community. This is a first step in building a data-intensive highway for geoscientists, smoothing their travel from the primary sources of data to new insights and rapid delivery of actionable information.

Prediction of aged red wine aroma properties from aroma chemical composition. Partial least squares regression models.

PubMed

Aznar, Margarita; López, Ricardo; Cacho, Juan; Ferreira, Vicente

2003-04-23

Partial least squares regression (PLSR) models able to predict some of the wine aroma nuances from its chemical composition have been developed. The aromatic sensory characteristics of 57 Spanish aged red wines were determined by 51 experts from the wine industry. The individual descriptions given by the experts were recorded, and the frequency with which a sensory term was used to define a given wine was taken as a measurement of its intensity. The aromatic chemical composition of the wines was determined by already published gas chromatography (GC)-flame ionization detector and GC-mass spectrometry methods. In the whole, 69 odorants were analyzed. Both matrixes, the sensory and chemical data, were simplified by grouping and rearranging correlated sensory terms or chemical compounds and by the exclusion of secondary aroma terms or of weak aroma chemicals. Finally, models were developed for 18 sensory terms and 27 chemicals or groups of chemicals. Satisfactory models, explaining more than 45% of the original variance, could be found for nine of the most important sensory terms (wood-vanillin-cinnamon, animal-leather-phenolic, toasted-coffee, old wood-reduction, vegetal-pepper, raisin-flowery, sweet-candy-cacao, fruity, and berry fruit). For this set of terms, the correlation coefficients between the measured and predicted Y (determined by cross-validation) ranged from 0.62 to 0.81. Models confirmed the existence of complex multivariate relationships between chemicals and odors. In general, pleasant descriptors were positively correlated to chemicals with pleasant aroma, such as vanillin, beta damascenone, or (E)-beta-methyl-gamma-octalactone, and negatively correlated to compounds showing less favorable odor properties, such as 4-ethyl and vinyl phenols, 3-(methylthio)-1-propanol, or phenylacetaldehyde.

An expert system based software sizing tool, phase 2

NASA Technical Reports Server (NTRS)

Friedlander, David

1990-01-01

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

CORMIX1: AN EXPERT SYSTEM FOR MIXING ZONE ANALYSIS OF TOXIC AND CONVENTIONAL, SINGLE PORT AQUATIC DISCHARGES

EPA Science Inventory

An expert system, CORMIX1, was developed to predict the dilution and trajectory of a single buoyant discharge into an unstratified aquatic environment with and without crossflow. The system uses knowledge and inference rules obtained from hydrodynamic experts to classify and pred...

Predicting Outcomes to Optimize Disease Management in Inflammatory Bowel Diseases.

PubMed

Torres, Joana; Caprioli, Flavio; Katsanos, Konstantinos H; Lobatón, Triana; Micic, Dejan; Zerôncio, Marco; Van Assche, Gert; Lee, James C; Lindsay, James O; Rubin, David T; Panaccione, Remo; Colombel, Jean-Frédéric

2016-12-01

Efforts to slow or prevent the progressive course of inflammatory bowel diseases [IBD] include early and intensive monitoring and treatment of patients at higher risk for complications. It is therefore essential to identify high-risk patients - both at diagnosis and throughout disease course. As a part of an IBD Ahead initiative, we conducted a comprehensive literature review to identify predictors of long-term IBD prognosis and generate draft expert summary statements. Statements were refined at national meetings of IBD experts in 32 countries and were finalized at an international meeting in November 2014. Patients with Crohn's disease presenting at a young age or with extensive anatomical involvement, deep ulcerations, ileal/ileocolonic involvement, perianal and/or severe rectal disease or penetrating/stenosing behaviour should be regarded as high risk for complications. Patients with ulcerative colitis presenting at young age, with extensive colitis and frequent flare-ups needing steroids or hospitalization present increased risk for colectomy or future hospitalization. Smoking status, concurrent primary sclerosing cholangitis and concurrent infections may impact the course of disease. Current genetic and serological markers lack accuracy for clinical use. Simple demographic and clinical features can guide the clinician in identifying patients at higher risk for disease complications at diagnosis and throughout disease course. However, many of these risk factors have been identified retrospectively and lack validation. Appropriately powered prospective studies are required to inform algorithms that can truly predict the risk for disease progression in the individual patient. © European Crohn’s and Colitis Organisation 2016.

Upper arm elevation and repetitive shoulder movements: a general population job exposure matrix based on expert ratings and technical measurements.

PubMed

Dalbøge, Annett; Hansson, Gert-Åke; Frost, Poul; Andersen, Johan Hviid; Heilskov-Hansen, Thomas; Svendsen, Susanne Wulff

2016-08-01

We recently constructed a general population job exposure matrix (JEM), The Shoulder JEM, based on expert ratings. The overall aim of this study was to convert expert-rated job exposures for upper arm elevation and repetitive shoulder movements to measurement scales. The Shoulder JEM covers all Danish occupational titles, divided into 172 job groups. For 36 of these job groups, we obtained technical measurements (inclinometry) of upper arm elevation and repetitive shoulder movements. To validate the expert-rated job exposures against the measured job exposures, we used Spearman rank correlations and the explained variance[Formula: see text] according to linear regression analyses (36 job groups). We used the linear regression equations to convert the expert-rated job exposures for all 172 job groups into predicted measured job exposures. Bland-Altman analyses were used to assess the agreement between the predicted and measured job exposures. The Spearman rank correlations were 0.63 for upper arm elevation and 0.64 for repetitive shoulder movements. The expert-rated job exposures explained 64% and 41% of the variance of the measured job exposures, respectively. The corresponding calibration equations were y=0.5%time+0.16×expert rating and y=27°/s+0.47×expert rating. The mean differences between predicted and measured job exposures were zero due to calibration; the 95% limits of agreement were ±2.9% time for upper arm elevation >90° and ±33°/s for repetitive shoulder movements. The updated Shoulder JEM can be used to present exposure-response relationships on measurement scales. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Dynamic array processing for computationally intensive expert systems in CLIPS

NASA Technical Reports Server (NTRS)

Athavale, N. N.; Ragade, R. K.; Fenske, T. E.; Cassaro, M. A.

1990-01-01

This paper puts forth an architecture for implementing a loop for advanced data structure of arrays in CLIPS. An attempt is made to use multi-field variables in such an architecture to process a set of data during the decision making cycle. Also, current limitations on the expert system shells are discussed in brief in this paper. The resulting architecture is designed to circumvent the current limitations set by the expert system shell and also by the operating environment. Such advanced data structures are needed for tightly coupling symbolic and numeric computation modules.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer.

PubMed

Wu, Abraham J; Bosch, Walter R; Chang, Daniel T; Hong, Theodore S; Jabbour, Salma K; Kleinberg, Lawrence R; Mamon, Harvey J; Thomas, Charles R; Goodman, Karyn A

2015-07-15

Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future. Copyright © 2015 Elsevier Inc. All rights reserved.

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer

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

Wu, Abraham J., E-mail: wua@mskcc.org; Bosch, Walter R.; Chang, Daniel T.

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophagealmore » cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future.« less

Adaptability of expert visual anticipation in baseball batting.

PubMed

Müller, Sean; Fadde, Peter J; Harbaugh, Allen G

2017-09-01

By manipulating stimulus variation in terms of opponent pitcher actions, this study investigated the capability of expert (n = 30) and near-expert (n = 95) professional baseball batters to adapt anticipation skill when using the video simulation temporal occlusion paradigm. Participants watched in-game footage of two pitchers, one after the other, that was temporally occluded at ball release and various points during ball flight. They were required to make a written prediction of pitch types and locations. Per cent accuracy was calculated for pitch type, for pitch location, and for type and location combined. Results indicated that experts and near-experts could adapt their anticipation to predict above guessing level across both pitchers, but adaptation to the left-handed pitcher was poorer than the right-handed pitcher. Small-to-moderate effect sizes were found in terms of superior adaptation by experts over near-experts at the ball release and early ball flight occlusion conditions. The findings of this study extend theoretical and applied knowledge of expertise in striking sports. Practical application of the instruments and findings are discussed in terms of applied researchers, practitioners and high-performance staff in professional sporting organisations.

Renal replacement therapy in adult and pediatric intensive care : Recommendations by an expert panel from the French Intensive Care Society (SRLF) with the French Society of Anesthesia Intensive Care (SFAR) French Group for Pediatric Intensive Care Emergencies (GFRUP) the French Dialysis Society (SFD).

PubMed

Vinsonneau, Christophe; Allain-Launay, Emma; Blayau, Clarisse; Darmon, Michael; Ducheyron, Damien; Gaillot, Theophile; Honore, Patrick M; Javouhey, Etienne; Krummel, Thierry; Lahoche, Annie; Letacon, Serge; Legrand, Matthieu; Monchi, Mehran; Ridel, Christophe; Robert, René; Schortgen, Frederique; Souweine, Bertrand; Vaillant, Patrick; Velly, Lionel; Osman, David; Van Vong, Ly

2015-12-01

Acute renal failure (ARF) in critically ill patients is currently very frequent and requires renal replacement therapy (RRT) in many patients. During the last 15 years, several studies have considered important issues regarding the use of RRT in ARF, like the time to initiate the therapy, the dialysis dose, the types of catheter, the choice of technique, and anticoagulation. However, despite an abundant literature, conflicting results do not provide evidence on RRT implementation. We present herein recommendations for the use of RRT in adult and pediatric intensive care developed with the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system by an expert group of French Intensive Care Society (SRLF), with the participation of the French Society of Anesthesia and Intensive Care (SFAR), the French Group for Pediatric Intensive Care and Emergencies (GFRUP), and the French Dialysis Society (SFD). The recommendations cover 4 fields: criteria for RRT initiation, technical aspects (access routes, membranes, anticoagulation, reverse osmosis water), practical aspects (choice of the method, peritoneal dialysis, dialysis dose, adjustments), and safety (procedures and training, dialysis catheter management, extracorporeal circuit set-up). These recommendations have been designed on a practical point of view to provide guidance for intensivists in their daily practice.

Investigation of Perceptual-Motor Behavior Across the Expert Athlete to Disabled Patient Skill Continuum can Advance Theory and Practical Application.

PubMed

Müller, Sean; Vallence, Ann-Maree; Winstein, Carolee

2017-12-14

A framework is presented of how theoretical predictions can be tested across the expert athlete to disabled patient skill continuum. Common-coding theory is used as the exemplar to discuss sensory and motor system contributions to perceptual-motor behavior. Behavioral and neural studies investigating expert athletes and patients recovering from cerebral stroke are reviewed. They provide evidence of bi-directional contributions of visual and motor systems to perceptual-motor behavior. Majority of this research is focused on perceptual-motor performance or learning, with less on transfer. The field is ripe for research designed to test theoretical predictions across the expert athlete to disabled patient skill continuum. Our view has implications for theory and practice in sports science, physical education, and rehabilitation.

Passive acquisition of CLIPS rules

NASA Technical Reports Server (NTRS)

Kovarik, Vincent J., Jr.

1991-01-01

The automated acquisition of knowledge by machine has not lived up to expectations, and knowledge engineering remains a human intensive task. Part of the reason for the lack of success is the difference in the cognitive focus of the expert. The expert must shift his or her focus from the subject domain to that of the representation environment. In doing so this cognitive shift introduces opportunity for errors and omissions. Presented here is work that observes the expert interact with a simulation of the domain. The system logs changes in the simulation objects and the expert's actions in response to those changes. This is followed by the application of inductive reasoning to move the domain specific rules observed to general domain rules.

CRN5EXP: Expert system for statistical quality control

NASA Technical Reports Server (NTRS)

Hentea, Mariana

1991-01-01

The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.

High-Quality Carbohydrates and Physical Performance

PubMed Central

Kanter, Mitch

2018-01-01

While all experts agreed that protein needs for performance are likely greater than believed in past generations, particularly for strength training athletes, and that dietary fat could sustain an active person through lower-intensity training bouts, current research still points to carbohydrate as an indispensable energy source for high-intensity performance. PMID:29449746

Total Habilitation: A Concept Whose Time Has Come--Reactions to Four Responses.

ERIC Educational Resources Information Center

Drash, Philip W.; Raver, Sharon A.

1987-01-01

The original authors address several concerns expressed in four responses to their article: terminology; the need for expert and intensive pedagogy (including early intensive language training); pessimistic attitudes; the need for caution in setting total habilitation as a goal; and a research model. (KM)

International expert statement on training standards for critical care ultrasonography.

PubMed

2011-07-01

Training in ultrasound techniques for intensive care medicine physicians should aim at achieving competencies in three main areas: (1) general critical care ultrasound (GCCUS), (2) "basic" critical care echocardiography (CCE), and (3) advanced CCE. A group of 29 experts representing the European Society of Intensive Care Medicine (ESICM) and 11 other critical care societies worldwide worked on a potential framework for organizing training adapted to each area of competence. This framework is mainly aimed at defining minimal requirements but is by no means rigid or restrictive: each training organization can be adapted according to resources available. There was 100% agreement among the participants that general critical care ultrasound and "basic" critical care echocardiography should be mandatory in the curriculum of intensive care unit (ICU) physicians. It is the role of each critical care society to support the implementation of training in GCCUS and basic CCE in its own country.

Automatically rating trainee skill at a pediatric laparoscopic suturing task.

PubMed

Oquendo, Yousi A; Riddle, Elijah W; Hiller, Dennis; Blinman, Thane A; Kuchenbecker, Katherine J

2018-04-01

Minimally invasive surgeons must acquire complex technical skills while minimizing patient risk, a challenge that is magnified in pediatric surgery. Trainees need realistic practice with frequent detailed feedback, but human grading is tedious and subjective. We aim to validate a novel motion-tracking system and algorithms that automatically evaluate trainee performance of a pediatric laparoscopic suturing task. Subjects (n = 32) ranging from medical students to fellows performed two trials of intracorporeal suturing in a custom pediatric laparoscopic box trainer after watching a video of ideal performance. The motions of the tools and endoscope were recorded over time using a magnetic sensing system, and both tool grip angles were recorded using handle-mounted flex sensors. An expert rated the 63 trial videos on five domains from the Objective Structured Assessment of Technical Skill (OSATS), yielding summed scores from 5 to 20. Motion data from each trial were processed to calculate 280 features. We used regularized least squares regression to identify the most predictive features from different subsets of the motion data and then built six regression tree models that predict summed OSATS score. Model accuracy was evaluated via leave-one-subject-out cross-validation. The model that used all sensor data streams performed best, achieving 71% accuracy at predicting summed scores within 2 points, 89% accuracy within 4, and a correlation of 0.85 with human ratings. 59% of the rounded average OSATS score predictions were perfect, and 100% were within 1 point. This model employed 87 features, including none based on completion time, 77 from tool tip motion, 3 from tool tip visibility, and 7 from grip angle. Our novel hardware and software automatically rated previously unseen trials with summed OSATS scores that closely match human expert ratings. Such a system facilitates more feedback-intensive surgical training and may yield insights into the fundamental components of surgical skill.

Development and Evaluation of an Expert System for Diagnosing Pest Damage of Red Pine

Treesearch

Daniel L Schmoldt; George L. Martin

1989-01-01

An expert system for diagnosing pest damage of red pine stands in Wisconsin, PREDICT, runs on IBM or compatible microcomputers and is designed to be useful for field foresters with no advanced training in forest pathology or entomology. PREDICT recognizes 28 damaging agents including species of mammals, insects, and pathogens, as well as two types of abiotic damage....

End points for validating early warning scores in the context of rapid response systems: a Delphi consensus study.

PubMed

Pedersen, N E; Oestergaard, D; Lippert, A

2016-05-01

When investigating early warning scores and similar physiology-based risk stratification tools, death, cardiac arrest and intensive care unit admission are traditionally used as end points. A large proportion of the patients identified by these end points cannot be saved, even with optimal treatment. This could pose a limitation to studies using these end points. We studied current expert opinion on end points for validating tools for the identification of patients in hospital wards at risk of imminent critical illness. The Delphi consensus methodology was used. We identified 22 experts based on objective criteria; 17 participated in the study. Each expert panel member's suggestions for end points were collected and distributed to the entire expert panel in anonymised form. The experts reviewed, rated and commented the suggested end points through the rounds in the Delphi process, and the experts' combined rating of the usefulness of each suggestion was established. A gross list of 86 suggestions for end points, relating to 13 themes, was produced. No items were uniformly recognised as ideal. The themes cardiac arrest, death, and level of care contained the items receiving highest ratings. End points relating to death, cardiac arrest and intensive care unit admission currently comprise the most obvious compromises for investigating early warning scores and similar risk stratification tools. Additional end points from the gross list of suggested end points could become feasible with the increased availability of large data sets with a multitude of recorded parameters. © 2015 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Intensive physical activity and alexithymia: results from swimmers' discourse analysis.

PubMed

Allegre, Benjamin; Noel-Jorand, Marie-Christine; Souville, Marc; Pellegrin, Liliane; Therme, Pierre

2007-06-01

The aim of this study was to describe and understand the relationship of swimmers' practice intensity and alexithymia features in discourse. This study investigated psychological processes in two groups of male swimmers training at different intensities. The first group was composed of 10 Expert amateurs (M age = 19.5 yr., SD = 1.9), who were competing at the national or international level and trained 22 hours per week. The second group was composed of 10 Amateur swimmers (M age = 20.5 yr., SD = 1.4), who competed at the regional level and trained 6 hours per week. The discourse of swimmers was analysed using the ALCESTE (Analyse de Lexèmes Coocurents dans les Enoncés Simples d'un Texte) method of discourse analysis. Discourse analysis was performed on speech samples produced by swimmers. All the swimmers showed alexithymic verbal behaviour as regards both the means of expression used and the feelings and emotions expressed. This lack of articulateness was more pronounced in the Expert than in the Amateur group. The difference of alexithymic features in correlation with the intensity of sport practice raises the question of the health benefits of intense sports practice and the need for psychological assessment of athletes.

Adaptation and validation of the REGEN expert system for the Central Appalachians

Treesearch

Lance A. Vickers; Thomas R. Fox; David L. Loftis; David A. Boucugnani

2011-01-01

REGEN is an expert system that predicts future species composition at the onset of stem exclusion using preharvest stand conditions. To extend coverage into hardwood stands of the Central Appalachians, we developed REGEN knowledge bases for four site qualities (xeric, subxeric, submesic, mesic) based on relevant literature and expert opinion. Data were collected from...

The 2014 updated version of the Confusion Assessment Method for the Intensive Care Unit compared to the 5th version of the Diagnostic and Statistical Manual of Mental Disorders and other current methods used by intensivists.

PubMed

Chanques, Gérald; Ely, E Wesley; Garnier, Océane; Perrigault, Fanny; Eloi, Anaïs; Carr, Julie; Rowan, Christine M; Prades, Albert; de Jong, Audrey; Moritz-Gasser, Sylvie; Molinari, Nicolas; Jaber, Samir

2018-03-01

One third of patients admitted to an intensive care unit (ICU) will develop delirium. However, delirium is under-recognized by bedside clinicians without the use of delirium screening tools, such as the Intensive Care Delirium Screening Checklist (ICDSC) or the Confusion Assessment Method for the ICU (CAM-ICU). The CAM-ICU was updated in 2014 to improve its use by clinicians throughout the world. It has never been validated compared to the new reference standard, the Diagnostic and Statistical Manual of Mental Disorders 5th version (DSM-5). We made a prospective psychometric study in a 16-bed medical-surgical ICU of a French academic hospital, to measure the diagnostic performance of the 2014 updated CAM-ICU compared to the DSM-5 as the reference standard. We included consecutive adult patients with a Richmond Agitation Sedation Scale (RASS) ≥ -3, without preexisting cognitive disorders, psychosis or cerebral injury. Delirium was independently assessed by neuropsychological experts using an operationalized approach to DSM-5, by investigators using the CAM-ICU and the ICDSC, by bedside clinicians and by ICU patients. The sensitivity, specificity, positive and negative predictive values were calculated considering neuropsychologist DSM-5 assessments as the reference standard (primary endpoint). CAM-ICU inter-observer agreement, as well as that between delirium diagnosis methods and the reference standard, was summarized using κ coefficients, which were subsequently compared using the Z-test. Delirium was diagnosed by experts in 38% of the 108 patients included for analysis. The CAM-ICU had a sensitivity of 83%, a specificity of 100%, a positive predictive value of 100% and a negative predictive value of 91%. Compared to the reference standard, the CAM-ICU had a significantly (p < 0.05) higher agreement (κ = 0.86 ± 0.05) than the physicians,' residents' and nurses' diagnoses (κ = 0.65 ± 0.09; 0.63 ± 0.09; 0.61 ± 0.09, respectively), as well as the patient's own impression of feeling delirious (κ = 0.02 ± 0.11). Differences between the ICDSC (κ = 0.69 ± 0.07) and CAM-ICU were not significant (p = 0.054). The CAM-ICU demonstrated a high reliability for inter-observer agreement (κ = 0.87 ± 0.06). The 2014 updated version of the CAM-ICU is valid according to DSM-5 criteria and reliable regarding inter-observer agreement in a research setting. Delirium remains under-recognized by bedside clinicians.

Seeking help in the shadow of doubt: the sensemaking processes underlying how nurses decide whom to ask for advice.

PubMed

Hofmann, David A; Lei, Zhike; Grant, Adam M

2009-09-01

Although scholars often assume that individuals seek out experts when they need help, recent research suggests that seeking help from experts can be costly. The authors propose that perceiving potential help providers as accessible or trustworthy can reduce the costs of seeking help and thus encourage individuals to seek help from experts. They further predict that perceptions of potential help providers' expertise, accessibility, and trustworthiness are shaped by their experience, formal roles, and organizational commitment. They investigated their theoretical model in a study of 146 nurses on the front lines of healthcare. They found that the decision to seek out help depends on help-seekers' perceptions of experts' accessibility and trustworthiness, and that these perceptions are predicted by experience, formal roles, and affective organizational commitment. Theoretical and practical implications are discussed.

Differentiating experts' anticipatory skills in beach volleyball.

PubMed

Cañal-Bruland, Rouwen; Mooren, Merel; Savelsbergh, Geert J P

2011-12-01

In this study, we examined how perceptual-motor expertise and watching experience contribute to anticipating the outcome of opponents' attacking actions in beach volleyball. To this end, we invited 8 expert beach volleyball players, 8 expert coaches, 8 expert referees, and 8 control participants with no beach volleyball experience to watch videos of attack sequences that were occluded at three different times and to predict the outcome of these situations. Results showed that expert players and coaches (who were both perceptual-motor experts) outperformed the expert referees (who were watching experts but did not have the same motor expertise) and the control group in the latest occlusion condition (i.e., at spiker-ball contact). This finding suggests that perceptual-motor expertise may contribute to successful action anticipation in beach volleyball.

Closed-loop control for cardiopulmonary management and intensive care unit sedation using digital imaging

NASA Astrophysics Data System (ADS)

Gholami, Behnood

This dissertation introduces a new problem in the delivery of healthcare, which could result in lower cost and a higher quality of medical care as compared to the current healthcare practice. In particular, a framework is developed for sedation and cardiopulmonary management for patients in the intensive care unit. A method is introduced to automatically detect pain and agitation in nonverbal patients, specifically in sedated patients in the intensive care unit, using their facial expressions. Furthermore, deterministic as well as probabilistic expert systems are developed to suggest the appropriate drug dose based on patient sedation level. Patients in the intensive care unit who require mechanical ventilation due to acute respiratory failure also frequently require the administration of sedative agents. The need for sedation arises both from patient anxiety due to the loss of personal control and the unfamiliar and intrusive environment of the intensive care unit, and also due to pain or other variants of noxious stimuli. In this dissertation, we develop a rule-based expert system for cardiopulmonary management and intensive care unit sedation. Furthermore, we use probability theory to quantify uncertainty and to extend the proposed rule-based expert system to deal with more realistic situations. Pain assessment in patients who are unable to verbally communicate is a challenging problem. The fundamental limitations in pain assessment stem from subjective assessment criteria, rather than quantifiable, measurable data. The relevance vector machine (RVM) classification technique is a Bayesian extension of the support vector machine (SVM) algorithm which achieves comparable performance to SVM while providing posterior probabilities for class memberships and a sparser model. In this dissertation, we use the RVM classification technique to distinguish pain from non-pain as well as assess pain intensity levels. We also correlate our results with the pain intensity assessed by expert and non-expert human examiners. Next, we consider facial expression recognition using an unsupervised learning framework. We show that different facial expressions reside on distinct subspaces if the manifold is unfolded. In particular, semi-definite embedding is used to reduce the dimensionality and unfold the manifold of facial images. Next, generalized principal component analysis is used to fit a series of subspaces to the data points and associate each data point to a subspace. Data points that belong to the same subspace are shown to belong to the same facial expression. In clinical intensive care unit practice sedative/analgesic agents are titrated to achieve a specific level of sedation. The level of sedation is currently based on clinical scoring systems. Examples include the motor activity assessment scale (MAAS), the Richmond agitation-sedation scale (RASS), and the modified Ramsay sedation scale (MRSS). In general, the goal of the clinician is to find the drug dose that maintains the patient at a sedation score corresponding to a moderately sedated state. In this research, we use pharmacokinetic and pharmacodynamic modeling to find an optimal drug dosing control policy to drive the patient to a desired MRSS score. Atrial fibrillation, a cardiac arrhythmia characterized by unsynchronized electrical activity in the atrial chambers of the heart, is a rapidly growing problem in modern societies. One treatment, referred to as catheter ablation, targets specific parts of the left atrium for radio frequency ablation using an intracardiac catheter. As a first step towards the general solution to the computer-assisted segmentation of the left atrial wall, we use shape learning and shape-based image segmentation to identify the endocardial wall of the left atrium in the delayed-enhancement magnetic resonance images. (Abstract shortened by UMI.)

Psychological tools for knowledge acquisition

NASA Technical Reports Server (NTRS)

Rueter, Henry H.; Olson, Judith Reitman

1988-01-01

Knowledge acquisition is said to be the biggest bottleneck in the development of expert systems. The problem is getting the knowledge out of the expert's head and into a computer. In cognitive psychology, characterizing metal structures and why experts are good at what they do is an important research area. Is there some way that the tools that psychologists have developed to uncover mental structure can be used to benefit knowledge engineers? We think that the way to find out is to browse through the psychologist's toolbox to see what there is in it that might be of use to knowledge engineers. Expert system developers have relied on two standard methods for extracting knowledge from the expert: (1) the knowledge engineer engages in an intense bout of interviews with the expert or experts, or (2) the knowledge engineer becomes an expert himself, relying on introspection to uncover the basis of his own expertise. Unfortunately, these techniques have the difficulty that often the expert himself isn't consciously aware of the basis of his expertise. If the expert himself isn't conscious of how he solves problems, introspection is useless. Cognitive psychology has faced similar problems for many years and has developed exploratory methods that can be used to discover cognitive structure from simple data.

Combining Decision Rules from Classification Tree Models and Expert Assessment to Estimate Occupational Exposure to Diesel Exhaust for a Case-Control Study

PubMed Central

Friesen, Melissa C.; Wheeler, David C.; Vermeulen, Roel; Locke, Sarah J.; Zaebst, Dennis D.; Koutros, Stella; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Malats, Nuria; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Rothman, Nathanial; Stewart, Patricia A.; Kogevinas, Manolis; Silverman, Debra T.

2016-01-01

Objectives: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study. Methods: First, previously extracted CT decision rules were used to obtain initial ordinal (0–3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule’s agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions. Results: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81–0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42–0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09–0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available. Conclusions: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study. PMID:26732820

Towards an Online Seizure Advisory System-An Adaptive Seizure Prediction Framework Using Active Learning Heuristics.

PubMed

Karuppiah Ramachandran, Vignesh Raja; Alblas, Huibert J; Le, Duc V; Meratnia, Nirvana

2018-05-24

In the last decade, seizure prediction systems have gained a lot of attention because of their enormous potential to largely improve the quality-of-life of the epileptic patients. The accuracy of the prediction algorithms to detect seizure in real-world applications is largely limited because the brain signals are inherently uncertain and affected by various factors, such as environment, age, drug intake, etc., in addition to the internal artefacts that occur during the process of recording the brain signals. To deal with such ambiguity, researchers transitionally use active learning, which selects the ambiguous data to be annotated by an expert and updates the classification model dynamically. However, selecting the particular data from a pool of large ambiguous datasets to be labelled by an expert is still a challenging problem. In this paper, we propose an active learning-based prediction framework that aims to improve the accuracy of the prediction with a minimum number of labelled data. The core technique of our framework is employing the Bernoulli-Gaussian Mixture model (BGMM) to determine the feature samples that have the most ambiguity to be annotated by an expert. By doing so, our approach facilitates expert intervention as well as increasing medical reliability. We evaluate seven different classifiers in terms of the classification time and memory required. An active learning framework built on top of the best performing classifier is evaluated in terms of required annotation effort to achieve a high level of prediction accuracy. The results show that our approach can achieve the same accuracy as a Support Vector Machine (SVM) classifier using only 20 % of the labelled data and also improve the prediction accuracy even under the noisy condition.

Learning from the Experts: Gaining Insights into Best Practice during the Acquisition of Three Novel Motor Skills

ERIC Educational Resources Information Center

Hodges, Nicola J.; Edwards, Christopher; Luttin, Shaun; Bowcock, Alison

2011-01-01

The amount and quality of practice predicts expertise, yet optimal conditions of practice have primarily been explored with novice learners. Ten expert musicians and ten novices practiced disc-throwing skills under self-regulated conditions. A third novice group practiced with the same schedule as the music experts (yoked). The groups did not…

Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models

PubMed Central

2017-01-01

We describe a fully data driven model that learns to perform a retrosynthetic reaction prediction task, which is treated as a sequence-to-sequence mapping problem. The end-to-end trained model has an encoder–decoder architecture that consists of two recurrent neural networks, which has previously shown great success in solving other sequence-to-sequence prediction tasks such as machine translation. The model is trained on 50,000 experimental reaction examples from the United States patent literature, which span 10 broad reaction types that are commonly used by medicinal chemists. We find that our model performs comparably with a rule-based expert system baseline model, and also overcomes certain limitations associated with rule-based expert systems and with any machine learning approach that contains a rule-based expert system component. Our model provides an important first step toward solving the challenging problem of computational retrosynthetic analysis. PMID:29104927

The capability of static and dynamic features to distinguish competent from genuinely expert practitioners in pediatric diagnosis.

PubMed

Loveday, Thomas; Wiggins, Mark W; Searle, Ben J; Festa, Marino; Schell, David

2013-02-01

The authors describe the development of a new, more objective method of distinguishing experienced competent nonexpert from expert practitioners within pediatric intensive care. Expert performance involves the acquisition and use of refined feature-event associations (cues) in the operational environment. Competent non-experts, although experienced, possess rudimentary cue associations in memory. Thus, they cannot respond as efficiently or as reliably as their expert counterparts, particularly when key diagnostic information is unavailable, such as that provided by dynamic cues. This study involved the application of four distinct tasks in which the use of relevant cues could be expected to increase both the accuracy and the efficiency of diagnostic performance. These tasks included both static and dynamic stimuli that were varied systematically. A total of 50 experienced pediatric intensive staff took part in the study. The sample clustered into two levels across the tasks: Participants who performed at a consistently high level throughout the four tasks were labeled experts, and participants who performed at a lower level throughout the tasks were labeled competent nonexperts. The groups differed in their responses to the diagnostic scenarios presented in two of the tasks and their ability to maintain performance in the absence of dynamic features. Experienced pediatricians can be decomposed into two groups on the basis of their capacity to acquire and use cues; these groups differ in their diagnostic accuracy and in their ability to maintain performance in the absence of dynamic features. The tasks may be used to identify practitioners who are failing to acquire expertise at a rate consistent with their experience, position, or training. This information may be used to guide targeted training efforts.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

PubMed

Harmouche, Rola; Subbanna, Nagesh K; Collins, D Louis; Arnold, Douglas L; Arbel, Tal

2015-05-01

In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

NASA Astrophysics Data System (ADS)

Santosa, I.; Romla, L.; Herawati, S.

2018-01-01

Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

Sherlock Holmes: an expert's view of expertise.

PubMed

André, Didierjean; Fernand, Gobet

2008-02-01

In recent years, there has been an intense research effort to understand the cognitive processes and structures underlying expert behaviour. Work in different fields, including scientific domains, sports, games and mnemonics, has shown that there are vast differences in perceptual abilities between experts and novices, and that these differences may underpin other cognitive differences in learning, memory and problem solving. In this article, we evaluate the progress made in the last years through the eyes of an outstanding, albeit fictional, expert: Sherlock Holmes. We first use the Sherlock Holmes character to illustrate expert processes as described by current research and theories. In particular, the role of perception, as well as the nature and influence of expert knowledge, are all present in the description of Conan Doyle's hero. In the second part of the article, we discuss a number of issues that current research on expertise has barely addressed. These gaps include, for example, several forms of reasoning, the influence of emotions on cognition, and the effect of age on experts' knowledge and cognitive processes. Thus, although nearly 120-year-old, Conan Doyle's books show remarkable illustrations of expert behaviour, including the coverage of themes that have mostly been overlooked by current research.

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage.

PubMed

Brady, A S; Belk, K E; LeValley, S B; Dalsted, N L; Scanga, J A; Tatum, J D; Smith, G C

2003-06-01

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective means for pricing carcasses in a value-based marketing system.

Experts correctly describe demography associated with historical decline of the endangered Indiana bat, but not recent period of stationarity

USGS Publications Warehouse

Thogmartin, Wayne E.; Sanders-Reed, Carol A.; Szymanski, Jennifer; Pruitt, Lori; Runge, Michael C.

2017-01-01

Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat (Myotis sodalis) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.

The architecture of the chess player's brain.

PubMed

Hänggi, Jürgen; Brütsch, Karin; Siegel, Adrian M; Jäncke, Lutz

2014-09-01

The game of chess can be seen as a typical example for an expertise task requiring domain-specific training and experience. Despite intensive behavioural studies the neural underpinnings of chess performance and expertise are not entirely understood. A few functional neuroimaging studies have shown that expert chess players recruit different psychological functions and activate different brain areas while they are engaged in chess-related activities. Based on this functional literature, we predicted to find morphological differences in a network comprised by parietal and frontal areas and especially the occipito-temporal junction (OTJ), fusiform gyrus, and caudate nucleus. Twenty expert chess players and 20 control subjects were investigated using voxel-based and surface-based morphometry as well as diffusion tensor imaging. Grey matter volume and cortical thickness were reduced in chess players compared with those of control men in the OTJ and precunei. The volumes of both caudate nuclei were not different between groups, but correlated inversely with the years of chess playing experience. Mean diffusivity was increased in chess players compared with that of controls in the left superior longitudinal fasciculus and the Elo score (a chess tournament ranking) was inversely related to mean diffusivity within the right superior longitudinal fasciculus. To the best of our knowledge we showed for the first time that there are specific differences in grey and white matter morphology between chess players and control subjects in brain regions associated with cognitive functions important for playing chess. Whether these anatomical alterations are the cause or consequence of the intensive and long-term chess training and practice remains to be shown in future studies. Copyright © 2014 Elsevier Ltd. All rights reserved.

The roles of deliberate practice and innate ability in developing expertise: evidence and implications.

PubMed

Kulasegaram, Kulamakan M; Grierson, Lawrence E M; Norman, Geoffrey R

2013-10-01

Medical education research focuses extensively on experience and deliberate practice (DP) as key factors in the development of expert performance. The research on DP minimises the role of individual ability in expert performance. This claim ignores a large body of research supporting the importance of innate individual cognitive differences. We review the relationship between DP and an innate individual ability, working memory (WM) capacity, to illustrate how both DP and individual ability predict expert performance. This narrative review examines the relationship between DP and WM in accounting for expert performance. Studies examining DP, WM and individual differences were identified through a targeted search. Although all studies support extensive DP as a factor in explaining expertise, much research suggests individual cognitive differences, such as WM capacity, predict expert performance after controlling for DP. The extent to which this occurs may be influenced by the nature of the task under study and the cognitive processes used by experts. The importance of WM capacity is greater for tasks that are non-routine or functionally complex. Clinical reasoning displays evidence of this task-dependent importance of individual ability. No single factor is both necessary and sufficient in explaining expertise, and individual abilities such as WM can be important. These individual abilities are likely to contribute to expert performance in clinical settings. Medical education research and practice should identify the individual differences in novices and experts that are important to clinical performance. © 2013 John Wiley & Sons Ltd.

An expert system for spectroscopic analysis of rocket engine plumes

NASA Technical Reports Server (NTRS)

Reese, Greg; Valenti, Elizabeth; Alphonso, Keith; Holladay, Wendy

1991-01-01

The expert system described in this paper analyzes spectral emissions of rocket engine exhaust plumes and shows major promise for use in engine health diagnostics. Plume emission spectroscopy is an important tool for diagnosing engine anomalies, but it is time-consuming and requires highly skilled personnel. The expert system was created to alleviate such problems. The system accepts a spectral plot in the form of wavelength vs intensity pairs and finds the emission peaks in the spectrum, lists the elemental emitters present in the data and deduces the emitter that produced each peak. The system consists of a conventional language component and a commercially available inference engine that runs on an Apple Macintosh computer. The expert system has undergone limited preliminary testing. It detects elements well and significantly decreases analysis time.

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge- intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.

Prediction of absolute infrared intensities for the fundamental vibrations of H2O2

NASA Technical Reports Server (NTRS)

Rogers, J. D.; Hillman, J. J.

1981-01-01

Absolute infrared intensities are predicted for the vibrational bands of gas-phase H2O2 by the use of a hydrogen atomic polar tensor transferred from the hydroxyl hydrogen atom of CH3OH. These predicted intensities are compared with intensities predicted by the use of a hydrogen atomic polar tensor transferred from H2O. The predicted relative intensities agree well with published spectra of gas-phase H2O2, and the predicted absolute intensities are expected to be accurate to within at least a factor of two. Among the vibrational degrees of freedom, the antisymmetric O-H bending mode nu(6) is found to be the strongest with a calculated intensity of 60.5 km/mole. The torsional band, a consequence of hindered rotation, is found to be the most intense fundamental with a predicted intensity of 120 km/mole. These results are compared with the recent absolute intensity determinations for the nu(6) band.

Design of an expert system for the development and formulation of push-pull osmotic pump tablets containing poorly water-soluble drugs.

PubMed

Zhang, Zhi-hong; Dong, Hong-ye; Peng, Bo; Liu, Hong-fei; Li, Chun-lei; Liang, Min; Pan, Wei-san

2011-05-30

The purpose of this article was to build an expert system for the development and formulation of push-pull osmotic pump tablets (PPOP). Hundreds of PPOP formulations were studied according to different poorly water-soluble drugs and pharmaceutical acceptable excipients. The knowledge base including database and rule base was built based on the reported results of hundreds of PPOP formulations containing different poorly water-soluble drugs and pharmaceutical excipients and the experiences available from other researchers. The prediction model of release behavior was built using back propagation (BP) neural network, which is good at nonlinear mapping and learning function. Formulation design model was established based on the prediction model of release behavior, which was the nucleus of the inference engine. Finally, the expert system program was constructed by VB.NET associating with SQL Server. Expert system is one of the most popular aspects in artificial intelligence. To date there is no expert system available for the formulation of controlled release dosage forms yet. Moreover, osmotic pump technology (OPT) is gradually getting consummate all over the world. It is meaningful to apply expert system on OPT. Famotidine, a water insoluble drug was chosen as the model drug to validate the applicability of the developed expert system. Copyright © 2011 Elsevier B.V. All rights reserved.

A review of fracture mechanics life technology

NASA Technical Reports Server (NTRS)

Besuner, P. M.; Harris, D. O.; Thomas, J. M.

1986-01-01

Lifetime prediction technology for structural components subjected to cyclic loads is examined. The central objectives of the project are: (1) to report the current state of the art, and (2) recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

A review of fracture mechanics life technology

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Besuner, P. M.; Harris, D. O.

1985-01-01

Current lifetime prediction technology for structural components subjected to cyclic loads was reviewed. The central objectives of the project were to report the current state of and recommend future development of fracture mechanics-based analytical tools for modeling and forecasting subcritical fatigue crack growth in structures. Of special interest to NASA was the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. A survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology were conducted. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include: development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Myocardial scar segmentation from magnetic resonance images using convolutional neural network

NASA Astrophysics Data System (ADS)

Zabihollahy, Fatemeh; White, James A.; Ukwatta, Eranga

2018-02-01

Accurate segmentation of the myocardial fibrosis or scar may provide important advancements for the prediction and management of malignant ventricular arrhythmias in patients with cardiovascular disease. In this paper, we propose a semi-automated method for segmentation of myocardial scar from late gadolinium enhancement magnetic resonance image (LGE-MRI) using a convolutional neural network (CNN). In contrast to image intensitybased methods, CNN-based algorithms have the potential to improve the accuracy of scar segmentation through the creation of high-level features from a combination of convolutional, detection and pooling layers. Our developed algorithm was trained using 2,336,703 image patches extracted from 420 slices of five 3D LGE-MR datasets, then validated on 2,204,178 patches from a testing dataset of seven 3D LGE-MR images including 624 slices, all obtained from patients with chronic myocardial infarction. For evaluation of the algorithm, we compared the algorithmgenerated segmentations to manual delineations by experts. Our CNN-based method reported an average Dice similarity coefficient (DSC), precision, and recall of 94.50 +/- 3.62%, 96.08 +/- 3.10%, and 93.96 +/- 3.75% as the accuracy of segmentation, respectively. As compared to several intensity threshold-based methods for scar segmentation, the results of our developed method have a greater agreement with manual expert segmentation.

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

Estrogen receptor expert system overview and examples

EPA Science Inventory

The estrogen receptor expert system (ERES) is a rule-based system developed to prioritize chemicals based upon their potential for binding to the ER. The ERES was initially developed to predict ER affinity of chemicals from two specific EPA chemical inventories, antimicrobial pe...

Using the Delphi method to develop nursing-sensitive quality indicators for the NICU.

PubMed

Chen, Lin; Huang, Li-Hua; Xing, Mei-Yuan; Feng, Zhi-Xian; Shao, Le-Wen; Zhang, Mei-Yun; Shao, Rong-Ya

2017-02-01

To develop nursing-sensitive quality indicators consistent with current medical practices in Chinese neonatal intensive care units. The development of nursing-sensitive quality indicators has become a top priority in nursing management. To the best of our knowledge, there has been no objective, scientific and sensitive evaluation of the quality of neonatal intensive care unit nursing in China. A modified Delphi technique was used to seek opinions from experts about what should be used and prioritised as indicators of quality care in neonatal intensive care unit nursing. Based on a literature review, we identified 21 indicators of nursing-sensitive quality in the neonatal intensive care unit. Our group of 11 consultants chose 13 indicators to be discussed using the Delphi method. In October and November 2014, 39 neonatal intensive care unit experts in 18 tertiary hospitals spread across six provinces participated in two rounds of Delphi panels. Of the 13 indicators discussed, 11 were identified as indicators of nursing-sensitive quality in the neonatal intensive care unit: rate of nosocomial infections, rate of accidental endotracheal extubation, rate of errors in medication administration, rate of treatment for pain, rate of peripheral venous extravasation, rate of compliance with handwashing techniques, incidence of pressure ulcers, incidence of noise, the bed-to-care ratio, the proportion of nurses with greater than five years neonatal intensive care unit experience and incidence of retinopathy. The 11 neonatal intensive care unit nursing-sensitive indicators identified by the Delphi method integrated with basic Chinese practices provide a basis for nursing management and the monitoring of nursing quality. This study identified nursing-sensitive quality indicators for neonatal intensive care unit care that are suitable for current clinical practice in China. © 2016 John Wiley & Sons Ltd.

Computer-assisted expert case definition in electronic health records.

PubMed

Walker, Alexander M; Zhou, Xiaofeng; Ananthakrishnan, Ashwin N; Weiss, Lisa S; Shen, Rongjun; Sobel, Rachel E; Bate, Andrew; Reynolds, Robert F

2016-02-01

To describe how computer-assisted presentation of case data can lead experts to infer machine-implementable rules for case definition in electronic health records. As an illustration the technique has been applied to obtain a definition of acute liver dysfunction (ALD) in persons with inflammatory bowel disease (IBD). The technique consists of repeatedly sampling new batches of case candidates from an enriched pool of persons meeting presumed minimal inclusion criteria, classifying the candidates by a machine-implementable candidate rule and by a human expert, and then updating the rule so that it captures new distinctions introduced by the expert. Iteration continues until an update results in an acceptably small number of changes to form a final case definition. The technique was applied to structured data and terms derived by natural language processing from text records in 29,336 adults with IBD. Over three rounds the technique led to rules with increasing predictive value, as the experts identified exceptions, and increasing sensitivity, as the experts identified missing inclusion criteria. In the final rule inclusion and exclusion terms were often keyed to an ALD onset date. When compared against clinical review in an independent test round, the derived final case definition had a sensitivity of 92% and a positive predictive value of 79%. An iterative technique of machine-supported expert review can yield a case definition that accommodates available data, incorporates pre-existing medical knowledge, is transparent and is open to continuous improvement. The expert updates to rules may be informative in themselves. In this limited setting, the final case definition for ALD performed better than previous, published attempts using expert definitions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The influence of expertise on brain activation of the action observation network during anticipation of tennis and volleyball serves.

PubMed

Balser, Nils; Lorey, Britta; Pilgramm, Sebastian; Naumann, Tim; Kindermann, Stefan; Stark, Rudolf; Zentgraf, Karen; Williams, A Mark; Munzert, Jörn

2014-01-01

In many daily activities, and especially in sport, it is necessary to predict the effects of others' actions in order to initiate appropriate responses. Recently, researchers have suggested that the action-observation network (AON) including the cerebellum plays an essential role during such anticipation, particularly in sport expert performers. In the present study, we examined the influence of task-specific expertise on the AON by investigating differences between two expert groups trained in different sports while anticipating action effects. Altogether, 15 tennis and 16 volleyball experts anticipated the direction of observed tennis and volleyball serves while undergoing functional magnetic resonance imaging (fMRI). The expert group in each sport acted as novice controls in the other sport with which they had only little experience. When contrasting anticipation in both expertise conditions with the corresponding untrained sport, a stronger activation of AON areas (SPL, SMA), and particularly of cerebellar structures, was observed. Furthermore, the neural activation within the cerebellum and the SPL was linearly correlated with participant's anticipation performance, irrespective of the specific expertise. For the SPL, this relationship also holds when an expert performs a domain-specific anticipation task. Notably, the stronger activation of the cerebellum as well as of the SMA and the SPL in the expertise conditions suggests that experts rely on their more fine-tuned perceptual-motor representations that have improved during years of training when anticipating the effects of others' actions in their preferred sport. The association of activation within the SPL and the cerebellum with the task achievement suggests that these areas are the predominant brain sites involved in fast motor predictions. The SPL reflects the processing of domain-specific contextual information and the cerebellum the usage of a predictive internal model to solve the anticipation task.

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches.

PubMed

Nugent, Frank J; Comyns, Thomas M; Warrington, Giles D

2017-06-01

The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches' perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches' perspective which was not currently available in the research literature.

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches

PubMed Central

Nugent, Frank J; Comyns, Thomas M; Warrington, Giles D

2017-01-01

Abstract The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches’ perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches’ perspective which was not currently available in the research literature. PMID:28713467

Tools and technologies for expert systems: A human factors perspective

NASA Technical Reports Server (NTRS)

Rajaram, Navaratna S.

1987-01-01

It is widely recognized that technologies based on artificial intelligence (AI), especially expert systems, can make significant contributions to the productivity and effectiveness of operations of information and knowledge intensive organizations such as NASA. At the same time, these being relatively new technologies, there is the problem of transfering technology to key personnel of such organizations. The problems of examining the potential of expert systems and of technology transfer is addressed in the context of human factors applications. One of the topics of interest was the investigation of the potential use of expert system building tools, particularly NEXPERT as a technology transfer medium. Two basic conclusions were reached in this regard. First, NEXPERT is an excellent tool for rapid prototyping of experimental expert systems, but not ideal as a delivery vehicle. Therefore, it is not a substitute for general purpose system implementation languages such a LISP or C. This assertion probably holds for nearly all such tools on the market today. Second, an effective technology transfer mechanism is to formulate and implement expert systems for problems which members of the organization in question can relate to. For this purpose, the LIghting EnGineering Expert (LIEGE) was implemented using NEXPERT as the tool for technology transfer and to illustrate the value of expert systems to the activities of the Man-System Division.

Targeted temperature management in the ICU: guidelines from a French expert panel.

PubMed

Cariou, Alain; Payen, Jean-François; Asehnoune, Karim; Audibert, Gerard; Botte, Astrid; Brissaud, Olivier; Debaty, Guillaume; Deltour, Sandrine; Deye, Nicolas; Engrand, Nicolas; Francony, Gilles; Legriel, Stéphane; Levy, Bruno; Meyer, Philippe; Orban, Jean-Christophe; Renolleau, Sylvain; Vigue, Bernard; De Saint Blanquat, Laure; Mathien, Cyrille; Velly, Lionel

2017-12-01

Over the recent period, the use of induced hypothermia has gained an increasing interest for critically ill patients, in particular in brain-injured patients. The term "targeted temperature management" (TTM) has now emerged as the most appropriate when referring to interventions used to reach and maintain a specific level temperature for each individual. TTM may be used to prevent fever, to maintain normothermia, or to lower core temperature. This treatment is widely used in intensive care units, mostly as a primary neuroprotective method. Indications are, however, associated with variable levels of evidence based on inhomogeneous or even contradictory literature. Our aim was to conduct a systematic analysis of the published data in order to provide guidelines. We present herein recommendations for the use of TTM in adult and paediatric critically ill patients developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method. These guidelines were conducted by a group of experts from the French Intensive Care Society (Société de Réanimation de Langue Française [SRLF]) and the French Society of Anesthesia and Intensive Care Medicine (Société Francaise d'Anesthésie Réanimation [SFAR]) with the participation of the French Emergency Medicine Association (Société Française de Médecine d'Urgence [SFMU]), the French Group for Pediatric Intensive Care and Emergencies (Groupe Francophone de Réanimation et Urgences Pédiatriques [GFRUP]), the French National Association of Neuro-Anesthesiology and Critical Care (Association Nationale de Neuro-Anesthésie Réanimation Française [ANARLF]), and the French Neurovascular Society (Société Française Neurovasculaire [SFNV]). Fifteen experts and two coordinators agreed to consider questions concerning TTM and its practical implementation in five clinical situations: cardiac arrest, traumatic brain injury, stroke, other brain injuries, and shock. This resulted in 30 recommendations: 3 recommendations were strong (Grade 1), 13 were weak (Grade 2), and 14 were experts' opinions. After two rounds of rating and various amendments, a strong agreement from voting participants was obtained for all 30 (100%) recommendations, which are exposed in the present article.

Comparison of climate envelope models developed using expert-selected variables versus statistical selection

USGS Publications Warehouse

Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

2017-01-01

Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (<40%) between the two methods Despite these differences in variable sets (expert versus statistical), models had high performance metrics (>0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable selection is a useful first step, especially when there is a need to model a large number of species or expert knowledge of the species is limited. Expert input can then be used to refine models that seem unrealistic or for species that experts believe are particularly sensitive to change. It also emphasizes the importance of using multiple models to reduce uncertainty and improve map outputs for conservation planning. Where outputs overlap or show the same direction of change there is greater certainty in the predictions. Areas of disagreement can be used for learning by asking why the models do not agree, and may highlight areas where additional on-the-ground data collection could improve the models.

Predicting couple therapy outcomes based on speech acoustic features

PubMed Central

Nasir, Md; Baucom, Brian Robert; Narayanan, Shrikanth

2017-01-01

Automated assessment and prediction of marital outcome in couples therapy is a challenging task but promises to be a potentially useful tool for clinical psychologists. Computational approaches for inferring therapy outcomes using observable behavioral information obtained from conversations between spouses offer objective means for understanding relationship dynamics. In this work, we explore whether the acoustics of the spoken interactions of clinically distressed spouses provide information towards assessment of therapy outcomes. The therapy outcome prediction task in this work includes detecting whether there was a relationship improvement or not (posed as a binary classification) as well as discerning varying levels of improvement or decline in the relationship status (posed as a multiclass recognition task). We use each interlocutor’s acoustic speech signal characteristics such as vocal intonation and intensity, both independently and in relation to one another, as cues for predicting the therapy outcome. We also compare prediction performance with one obtained via standardized behavioral codes characterizing the relationship dynamics provided by human experts as features for automated classification. Our experiments, using data from a longitudinal clinical study of couples in distressed relations, showed that predictions of relationship outcomes obtained directly from vocal acoustics are comparable or superior to those obtained using human-rated behavioral codes as prediction features. In addition, combining direct signal-derived features with manually coded behavioral features improved the prediction performance in most cases, indicating the complementarity of relevant information captured by humans and machine algorithms. Additionally, considering the vocal properties of the interlocutors in relation to one another, rather than in isolation, showed to be important for improving the automatic prediction. This finding supports the notion that behavioral outcome, like many other behavioral aspects, is closely related to the dynamics and mutual influence of the interlocutors during their interaction and their resulting behavioral patterns. PMID:28934302

The use of subjective expert opinions in cost optimum design of aerospace structures. [probabilistic failure models

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Hanagud, S.

1975-01-01

The results of two questionnaires sent to engineering experts are statistically analyzed and compared with objective data from Saturn V design and testing. Engineers were asked how likely it was for structural failure to occur at load increments above and below analysts' stress limit predictions. They were requested to estimate the relative probabilities of different failure causes, and of failure at each load increment given a specific cause. Three mathematical models are constructed based on the experts' assessment of causes. The experts' overall assessment of prediction strength fits the Saturn V data better than the models do, but a model test option (T-3) based on the overall assessment gives more design change likelihood to overstrength structures than does an older standard test option. T-3 compares unfavorably with the standard option in a cost optimum structural design problem. The report reflects a need for subjective data when objective data are unavailable.

Meta-knowledge for charity: Learnings from a non-market-based prediction platform for climate scientists

NASA Astrophysics Data System (ADS)

Kriss, P.

2016-12-01

We present the results from Vision Prize, an online platform for capturing expert opinion on climate risks and solutions. Expert panelists provided their own opinions, and also predicted the views of their scientific colleagues. This approach (Prelec, 2004 Nature) gives new insight into the level of scientific consensus on various issues, which in some cases may be just as important as knowing the majority view. Questions ranged from causal attributions of past events to predictions about future risks and beliefs about possible solutions. Across all topics, we find that our expert participants agree with each other more than they think they do, often in surprising ways. Data collection for the Vision Prize project was run in collaboration with Environmental Research Web (IOP). Panelists were pre-screened to ensure they have relevant expertise and independently collected h-scores provide an approximate measure of research impact of those giving each response. Charity prizes were awarded for exceptional meta-knowledge, according to Prelec's algorithm.

Parameterization of the InVEST Crop Pollination Model to spatially predict abundance of wild blueberry (Vaccinium angustifolium Aiton) native bee pollinators in Maine, USA

USGS Publications Warehouse

Groff, Shannon C.; Loftin, Cynthia S.; Drummond, Frank; Bushmann, Sara; McGill, Brian J.

2016-01-01

Non-native honeybees historically have been managed for crop pollination, however, recent population declines draw attention to pollination services provided by native bees. We applied the InVEST Crop Pollination model, developed to predict native bee abundance from habitat resources, in Maine's wild blueberry crop landscape. We evaluated model performance with parameters informed by four approaches: 1) expert opinion; 2) sensitivity analysis; 3) sensitivity analysis informed model optimization; and, 4) simulated annealing (uninformed) model optimization. Uninformed optimization improved model performance by 29% compared to expert opinion-informed model, while sensitivity-analysis informed optimization improved model performance by 54%. This suggests that expert opinion may not result in the best parameter values for the InVEST model. The proportion of deciduous/mixed forest within 2000 m of a blueberry field also reliably predicted native bee abundance in blueberry fields, however, the InVEST model provides an efficient tool to estimate bee abundance beyond the field perimeter.

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Development and Validation of an Instrument to Assess the Implementation of Family-Centred Care in Traditional Open Bay Neonatal Intensive Care Units

ERIC Educational Resources Information Center

Al-Motlaq, Mohammad A.; Abuidhail, Jamila; Salameh, Taghreed; Awwad, Wesam

2017-01-01

Objective: To develop an instrument to study family-centred care (FCC) in traditional open bay Neonatal Intensive Care Units (NICUs). Methods: The development process involved constructing instrument's items, establishing content validity by an expert panel and testing the instrument for validity and reliability with a convenience sample of 25…

Investigation of gene expressions in differentiated cell derived bone marrow stem cells during bone morphogenetic protein-4 treatments with Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zafari, Jaber; Jouni, Fatemeh Javani; Ahmadvand, Ali; Abdolmaleki, Parviz; Soodi, Malihe; Zendehdel, Rezvan

2017-02-01

A model was set up to predict the differentiation patterns based on the data extracted from FTIR spectroscopy. For this reason, bone marrow stem cells (BMSCs) were differentiated to primordial germ cells (PGCs). Changes in cellular macromolecules in the time of 0, 24, 48, 72, and 96 h of differentiation, as different steps of the differentiation procedure were investigated by using FTIR spectroscopy. Also, the expression of pluripotency (Oct-4, Nanog and c-Myc) and specific genes (Mvh, Stella and Fragilis) were investigated by real-time PCR. However, the expression of genes in five steps of differentiation was predicted by FTIR spectroscopy. FTIR spectra showed changes in the template of band intensities at different differentiation steps. There are increasing changes in the stepwise differentiation procedure for the ratio area of CH2, which is symmetric to CH2 asymmetric stretching. An ensemble of expert methods, including regression tree (RT), boosting algorithm (BA), and generalized regression neural network (GRNN), was the best method to predict the gene expression by FTIR spectroscopy. In conclusion, the model was able to distinguish the pattern of different steps from cell differentiation by using some useful features extracted from FTIR spectra.

A study of occurrence rates of Electromagnetic Interference (EMI) to aircraft with a focus on HIRF (external) High Intensity Radiated Fields

NASA Technical Reports Server (NTRS)

Shooman, Martin L.

1994-01-01

This report presents the methodology and results of a subjective study done by Polytechnic University to investigate Electromagnetic Interference (EMI) events on aircraft. The results cover various types of EMI from on-board aircraft systems, passenger carry-on devices, and externally generated disturbances. The focus of the study, however, was on externally generated EMI, termed High Intensity Radiated Fields (HIRF), from radars, radio and television transmitters, and other man-made emitters of electromagnetic energy. The study methodology used an anonymous questionnaire distributed to experts to gather the data. This method is known as the Delphi or Consensus Estimation technique. The questionnaire was sent to an expert population of 230 and there were 57 respondents. Details of the questionnaire, a few anecdotes, and the statistical results of the study are presented.

Hazard perception, risk perception, and the need for decontamination by residents exposed to soil pollution: the role of sustainability and the limits of expert knowledge.

PubMed

Vandermoere, Frédéric

2008-04-01

This case study examines the hazard and risk perception and the need for decontamination according to people exposed to soil pollution. Using an ecological-symbolic approach (ESA), a multidisciplinary model is developed that draws upon psychological and sociological perspectives on risk perception and includes ecological variables by using data from experts' risk assessments. The results show that hazard perception is best predicted by objective knowledge, subjective knowledge, estimated knowledge of experts, and the assessed risks. However, experts' risk assessments induce an increase in hazard perception only when residents know the urgency of decontamination. Risk perception is best predicted by trust in the risk management. Additionally, need for decontamination relates to hazard perception, risk perception, estimated knowledge of experts, and thoughts about sustainability. In contrast to the knowledge deficit model, objective and subjective knowledge did not significantly relate to risk perception and need for decontamination. The results suggest that residents can make a distinction between hazards in terms of the seriousness of contamination on the one hand, and human health risks on the other hand. Moreover, next to the importance of social determinants of environmental risk perception, this study shows that the output of experts' risk assessments-or the objective risks-can create a hazard awareness rather than an alarming risk consciousness, despite residents' distrust of scientific knowledge.

Mining data from hemodynamic simulations for generating prediction and explanation models.

PubMed

Bosnić, Zoran; Vračar, Petar; Radović, Milos D; Devedžić, Goran; Filipović, Nenad D; Kononenko, Igor

2012-03-01

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain. © 2012 IEEE

A rule-based expert system for chemical prioritization using effects-based chemical categories

EPA Science Inventory

A rule-based expert system (ES) was developed to predict chemical binding to the estrogen receptor (ER) patterned on the research approaches championed by Gilman Veith to whom this article and journal issue are dedicated. The ERES was built to be mechanistically-transparent and m...

How Experts Practice: A Novel Test of Deliberate Practice Theory

ERIC Educational Resources Information Center

Coughlan, Edward K.; Williams, A. Mark; McRobert, Allistair P.; Ford, Paul R.

2014-01-01

Performance improvement is thought to occur through engagement in deliberate practice. Deliberate practice is predicted to be challenging, effortful, and not inherently enjoyable. Expert and intermediate level Gaelic football players executed two types of kicks during an acquisition phase and pre-, post-, and retention tests. During acquisition,…

Aeroaging - A New Collaboration between Life Sciences Experts and Aerospace Engineers.

PubMed

Vellas, M; Fualdes, C; Morley, J E; Dray, C; Rodriguez-Manas, L; Meyer, A; Michel, L; Rolland, Y; Gourinat, Y

2017-01-01

An open discussion between experts from life sciences and aeronautics has been held in order to investigate how both area of research overlap and could be relevant to each other, precisely on the topic of aging. Similarities in aging processes and prediction methodologies have been identified between human aging and aircraft aging. Two axis of collaboration have been raised: 1) The identification of the determinants in Aircraft aging (structural aging). 2) The development of P4 Systems medicine inspired new methodologies in the predictive maintenance.

Scalable methodology for large scale building energy improvement: Relevance of calibration in model-based retrofit analysis

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

Heo, Yeonsook; Augenbroe, Godfried; Graziano, Diane

2015-05-01

The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustratesmore » both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.« less

Semi-automated image analysis for the assessment of megafaunal densities at the Arctic deep-sea observatory HAUSGARTEN.

PubMed

Schoening, Timm; Bergmann, Melanie; Ontrup, Jörg; Taylor, James; Dannheim, Jennifer; Gutt, Julian; Purser, Autun; Nattkemper, Tim W

2012-01-01

Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS.

Semi-Automated Image Analysis for the Assessment of Megafaunal Densities at the Arctic Deep-Sea Observatory HAUSGARTEN

PubMed Central

Schoening, Timm; Bergmann, Melanie; Ontrup, Jörg; Taylor, James; Dannheim, Jennifer; Gutt, Julian; Purser, Autun; Nattkemper, Tim W.

2012-01-01

Megafauna play an important role in benthic ecosystem function and are sensitive indicators of environmental change. Non-invasive monitoring of benthic communities can be accomplished by seafloor imaging. However, manual quantification of megafauna in images is labor-intensive and therefore, this organism size class is often neglected in ecosystem studies. Automated image analysis has been proposed as a possible approach to such analysis, but the heterogeneity of megafaunal communities poses a non-trivial challenge for such automated techniques. Here, the potential of a generalized object detection architecture, referred to as iSIS (intelligent Screening of underwater Image Sequences), for the quantification of a heterogenous group of megafauna taxa is investigated. The iSIS system is tuned for a particular image sequence (i.e. a transect) using a small subset of the images, in which megafauna taxa positions were previously marked by an expert. To investigate the potential of iSIS and compare its results with those obtained from human experts, a group of eight different taxa from one camera transect of seafloor images taken at the Arctic deep-sea observatory HAUSGARTEN is used. The results show that inter- and intra-observer agreements of human experts exhibit considerable variation between the species, with a similar degree of variation apparent in the automatically derived results obtained by iSIS. Whilst some taxa (e. g. Bathycrinus stalks, Kolga hyalina, small white sea anemone) were well detected by iSIS (i. e. overall Sensitivity: 87%, overall Positive Predictive Value: 67%), some taxa such as the small sea cucumber Elpidia heckeri remain challenging, for both human observers and iSIS. PMID:22719868

Expert system technology

NASA Technical Reports Server (NTRS)

Prince, Mary Ellen

1987-01-01

The expert system is a computer program which attempts to reproduce the problem-solving behavior of an expert, who is able to view problems from a broad perspective and arrive at conclusions rapidly, using intuition, shortcuts, and analogies to previous situations. Expert systems are a departure from the usual artificial intelligence approach to problem solving. Researchers have traditionally tried to develop general modes of human intelligence that could be applied to many different situations. Expert systems, on the other hand, tend to rely on large quantities of domain specific knowledge, much of it heuristic. The reasoning component of the system is relatively simple and straightforward. For this reason, expert systems are often called knowledge based systems. The report expands on the foregoing. Section 1 discusses the architecture of a typical expert system. Section 2 deals with the characteristics that make a problem a suitable candidate for expert system solution. Section 3 surveys current technology, describing some of the software aids available for expert system development. Section 4 discusses the limitations of the latter. The concluding section makes predictions of future trends.

Multiple neural network approaches to clinical expert systems

NASA Astrophysics Data System (ADS)

Stubbs, Derek F.

1990-08-01

We briefly review the concept of computer aided medical diagnosis and more extensively review the the existing literature on neural network applications in the field. Neural networks can function as simple expert systems for diagnosis or prognosis. Using a public database we develop a neural network for the diagnosis of a major presenting symptom while discussing the development process and possible approaches. MEDICAL EXPERTS SYSTEMS COMPUTER AIDED DIAGNOSIS Biomedicine is an incredibly diverse and multidisciplinary field and it is not surprising that neural networks with their many applications are finding more and more applications in the highly non-linear field of biomedicine. I want to concentrate on neural networks as medical expert systems for clinical diagnosis or prognosis. Expert Systems started out as a set of computerized " ifthen" rules. Everything was reduced to boolean logic and the promised land of computer experts was said to be in sight. It never came. Why? First the computer code explodes as the number of " ifs" increases. All the " ifs" have to interact. Second experts are not very good at reducing expertise to language. It turns out that experts recognize patterns and have non-verbal left-brain intuition decision processes. Third learning by example rather than learning by rule is the way natural brains works and making computers work by rule-learning is hideously labor intensive. Neural networks can learn from example. They learn the results

Effect of sex and carcass weight on sensory quality of goat meat of Cabrito Transmontano.

PubMed

Rodrigues, S; Teixeira, A

2009-02-01

The main purpose of this work was the characterization of Cabrito Transmontana goat kid carcass and meat, which is a Protected Origin Designation product. The effects of sex and carcass weight were studied. Sensory attributes of toughness, juiciness, flavor intensity, flavor quality, odor intensity, fiber presence (stringy), sweet intensity, and overall acceptability were evaluated in 60 males and females allocated to 3 carcass weight groups: 4, 6, and 8 kg. Sensory quality of meat was evaluated by a trained taste panel of 11 experts in 5 sessions. Generalized Procrustes analysis was performed, and 93% of total variability was explained by the 2 first factors (axes). Correlation between sensory traits and factors 1 and 2 allowed the factors to be renamed as toughness/aroma and juiciness/acceptability, respectively. Procrustes analysis indicated that a sex effect was detected by experts. Meat from males presented greater juiciness, flavor quality, and general acceptability than did meat from females. Cabrito Transmontano Protected Origin Designation includes animals from 4 to 9 kg of carcass weight. However, differences among them can be important, because the taste panel found differences between animals from distinct carcass weight ranges. Lighter weight carcasses were considered more tender with less flavor and odor intensity than heavier carcasses.

Sports specialization in young athletes: evidence-based recommendations.

PubMed

Jayanthi, Neeru; Pinkham, Courtney; Dugas, Lara; Patrick, Brittany; Labella, Cynthia

2013-05-01

Sports specialization is intense training in 1 sport while excluding others. Sports specialization in early to middle childhood has become increasingly common. While most experts agree that some degree of sports specialization is necessary to achieve elite levels, there is some debate as to whether such intense practice time must begin during early childhood and to the exclusion of other sports to maximize potential for success. There is a concern that sports specialization before adolescence may be deleterious to a young athlete. PubMed and OVID were searched for English-language articles from 1990 to 2011 discussing sports specialization, expert athletes, or elite versus novice athletes, including original research articles, consensus opinions, and position statements. For most sports, there is no evidence that intense training and specialization before puberty are necessary to achieve elite status. Risks of early sports specialization include higher rates of injury, increased psychological stress, and quitting sports at a young age. Sports specialization occurs along a continuum. Survey tools are being developed to identify where athletes fall along the spectrum of specialization. Some degree of sports specialization is necessary to develop elite-level skill development. However, for most sports, such intense training in a single sport to the exclusion of others should be delayed until late adolescence to optimize success while minimizing injury, psychological stress, and burnout.

Do short courses in evidence based medicine improve knowledge and skills? Validation of Berlin questionnaire and before and after study of courses in evidence based medicine

PubMed Central

Fritsche, L; Greenhalgh, T; Falck-Ytter, Y; Neumayer, H-H; Kunz, R

2002-01-01

Objective To develop and validate an instrument for measuring knowledge and skills in evidence based medicine and to investigate whether short courses in evidence based medicine lead to a meaningful increase in knowledge and skills. Design Development and validation of an assessment instrument and before and after study. Setting Various postgraduate short courses in evidence based medicine in Germany. Participants The instrument was validated with experts in evidence based medicine, postgraduate doctors, and medical students. The effect of courses was assessed by postgraduate doctors from medical and surgical backgrounds. Intervention Intensive 3 day courses in evidence based medicine delivered through tutor facilitated small groups. Main outcome measure Increase in knowledge and skills. Results The questionnaire distinguished reliably between groups with different expertise in evidence based medicine. Experts attained a threefold higher average score than students. Postgraduates who had not attended a course performed better than students but significantly worse than experts. Knowledge and skills in evidence based medicine increased after the course by 57% (mean score before course 6.3 (SD 2.9) v 9.9 (SD 2.8), P<0.001). No difference was found among experts or students in absence of an intervention. Conclusions The instrument reliably assessed knowledge and skills in evidence based medicine. An intensive 3 day course in evidence based medicine led to a significant increase in knowledge and skills. What is already known on this topicNumerous observational studies have investigated the impact of teaching evidence based medicine to healthcare professionals, with conflicting resultsMost of the studies were of poor methodological qualityWhat this study addsAn instrument assessing basic knowledge and skills required for practising evidence based medicine was developed and validatedAn intensive 3 day course on evidence based medicine for doctors from various backgrounds and training level led to a clinically meaningful improvement of knowledge and skills PMID:12468485

Common problems in the elicitation and analysis of expert opinion affecting probabilistic safety assessments

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

Meyer, M.A.; Booker, J.M.

1990-01-01

Expert opinion is frequently used in probabilistic safety assessment (PSA), particularly in estimating low probability events. In this paper, we discuss some of the common problems encountered in eliciting and analyzing expert opinion data and offer solutions or recommendations. The problems are: that experts are not naturally Bayesian. People fail to update their existing information to account for new information as it becomes available, as would be predicted by the Bayesian philosophy; that experts cannot be fully calibrated. To calibrate experts, the feedback from the known quantities must be immediate, frequent, and specific to the task; that experts are limitedmore » in the number of things that they can mentally juggle at a time to 7 {plus minus} 2; that data gatherers and analysts can introduce bias by unintentionally causing an altering of the expert's thinking or answers; that the level of detail the data, or granularity, can affect the analyses; and the conditioning effect poses difficulties in gathering and analyzing of the expert data. The data that the expert gives can be conditioned on a variety of factors that can affect the analysis and the interpretation of the results. 31 refs.« less

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

PubMed

Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

2002-05-01

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

Predicting landscape connectivity for the Asian elephant in its largest remaining subpopulation

Treesearch

J.-P. Puyravaud; Samuel Cushman; P. Davidar; D. Madappa

2016-01-01

Landscape connectivity between protected areas is crucial for the conservation of megafauna. But often, corridor identification relies on expert knowledge that is subjective and not spatially synoptic. Landscape analysis allows generalization of expert knowledge when satellite tracking or genetic data are not available. The Nilgiri Biosphere Reserve in southern India...

Classification of Word Levels with Usage Frequency, Expert Opinions and Machine Learning

ERIC Educational Resources Information Center

Sohsah, Gihad N.; Ünal, Muhammed Esad; Güzey, Onur

2015-01-01

Educational applications for language teaching can utilize the language levels of words to target proficiency levels of students. This paper and the accompanying data provide a methodology for making educational standard-aligned language-level predictions for all English words. The methodology involves expert opinions on language levels and…

Underwater Munitions Expert System to Predict Mobility and Burial

DTIC Science & Technology

2017-11-14

exposure and aggregation for underwater munitions. 15. SUBJECT TERMS Underwater Munitions, Mobility, Burial, Application Programmer Interface...Munitions Expert System: Demonstration and Evaluation Report Acronyms API – Application Programmer Interface APL – Applied Physics...comparisons and traditional metrics such as the coefficient of correlation. The summary statistic for the comparisons of burial results

Foveal and peripheral fields of vision influences perceptual skill in anticipating opponents' attacking position in volleyball.

PubMed

Schorer, Jörg; Rienhoff, Rebecca; Fischer, Lennart; Baker, Joseph

2013-09-01

The importance of perceptual-cognitive expertise in sport has been repeatedly demonstrated. In this study we examined the role of different sources of visual information (i.e., foveal versus peripheral) in anticipating volleyball attack positions. Expert (n = 11), advanced (n = 13) and novice (n = 16) players completed an anticipation task that involved predicting the location of volleyball attacks. Video clips of volleyball attacks (n = 72) were spatially and temporally occluded to provide varying amounts of information to the participant. In addition, participants viewed the attacks under three visual conditions: full vision, foveal vision only, and peripheral vision only. Analysis of variance revealed significant between group differences in prediction accuracy with higher skilled players performing better than lower skilled players. Additionally, we found significant differences between temporal and spatial occlusion conditions. Both of those factors interacted separately, but not combined with expertise. Importantly, for experts the sum of both fields of vision was superior to either source in isolation. Our results suggest different sources of visual information work collectively to facilitate expert anticipation in time-constrained sports and reinforce the complexity of expert perception.

Mediating the Cognitive Walkthrough with Patient Groups to achieve Personalized Health in Chronic Disease Self-Management System Evaluation.

PubMed

Georgsson, Mattias; Kushniruk, Andre

2016-01-01

The cognitive walkthrough (CW) is a task-based, expert inspection usability evaluation method involving benefits such as cost effectiveness and efficiency. A drawback of the method is that it doesn't involve the user perspective from real users but instead is based on experts' predictions about the usability of the system and how users interact. In this paper, we propose a way of involving the user in an expert evaluation method by modifying the CW with patient groups as mediators. This along with other modifications include a dual domain session facilitator, specific patient groups and three different phases: 1) a preparation phase where suitable tasks are developed by a panel of experts and patients, validated through the content validity index 2) a patient user evaluation phase including an individual and collaborative process part 3) an analysis and coding phase where all data is digitalized and synthesized making use of Qualitative Data Analysis Software (QDAS) to determine usability deficiencies. We predict that this way of evaluating will utilize the benefits of the expert methods, also providing a way of including the patient user of these self-management systems. Results from this prospective study should provide evidence of the usefulness of this method modification.

A clinical decision support system prototype for cardiovascular intensive care.

PubMed

Lau, F

1994-08-01

This paper describes the development and validation of a decision-support system prototype that can help manage hypovolemic hypotension in the Cardiovascular Intensive Care Unit (CVICU). The prototype uses physiologic pattern-matching, therapeutic protocols, computational drug-dosage response modeling and expert reasoning heuristics in its selection of intervention strategies and choices. As part of model testing, the prototype simulated real-time operation by processing historical physiologic and intervention data on a patient sequentially, generating alerts on questionable data, critiques of interventions instituted and recommendations on preferred interventions. Bench-testing with 399 interventions from 13 historical cases showed therapies for bleeding and fluid replacement proposed by the prototype were significantly more consistent (p < 0.0001) than those instituted by the staff when compared against expert critiques (80% versus 44%). This study has demonstrated the feasibility of formalizing hemodynamic management of CVICU patients in a manner that may be implemented and evaluated in a clinical setting.

A Semi-automated Approach to Create Purposeful Mechanistic Datasets from Heterogeneous Data: Data Mining Towards the in silico Predictions for Oestrogen Receptor Modulation and Teratogenicity.

PubMed

Bashir Surfraz, M; Fowkes, Adrian; Plante, Jeffrey P

2017-08-01

The need to find an alternative to costly animal studies for developmental and reproductive toxicity testing has shifted the focus considerably to the assessment of in vitro developmental toxicology models and the exploitation of pharmacological data for relevant molecular initiating events. We hereby demonstrate how automation can be applied successfully to handle heterogeneous oestrogen receptor data from ChEMBL. Applying expert-derived thresholds to specific bioactivities allowed an activity call to be attributed to each data entry. Human intervention further improved this mechanistic dataset which was mined to develop structure-activity relationship alerts and an expert model covering 45 chemical classes for the prediction of oestrogen receptor modulation. The evaluation of the model using FDA EDKB and Tox21 data was quite encouraging. This model can also provide a teratogenicity prediction along with the additional information it provides relevant to the query compound, all of which will require careful assessment of potential risk by experts. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

PubMed Central

Bennett, Kristin P.

2014-01-01

We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC) clades. The proposed knowledge-based Bayesian network (KBBN) treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes), since these are routinely gathered from MTBC isolates of tuberculosis (TB) patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web. PMID:24864238

A Statistical Evaluation of the Diagnostic Performance of MEDAS-The Medical Emergency Decision Assistance System

PubMed Central

Georgakis, D. Christine; Trace, David A.; Naeymi-Rad, Frank; Evens, Martha

1990-01-01

Medical expert systems require comprehensive evaluation of their diagnostic accuracy. The usefulness of these systems is limited without established evaluation methods. We propose a new methodology for evaluating the diagnostic accuracy and the predictive capacity of a medical expert system. We have adapted to the medical domain measures that have been used in the social sciences to examine the performance of human experts in the decision making process. Thus, in addition to the standard summary measures, we use measures of agreement and disagreement, and Goodman and Kruskal's λ and τ measures of predictive association. This methodology is illustrated by a detailed retrospective evaluation of the diagnostic accuracy of the MEDAS system. In a study using 270 patients admitted to the North Chicago Veterans Administration Hospital, diagnoses produced by MEDAS are compared with the discharge diagnoses of the attending physicians. The results of the analysis confirm the high diagnostic accuracy and predictive capacity of the MEDAS system. Overall, the agreement of the MEDAS system with the “gold standard” diagnosis of the attending physician has reached a 90% level.

System of experts for intelligent data management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1993-01-01

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

System of Experts for Intelligent Data Management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1992-01-01

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Ask-the-expert: Active Learning Based Knowledge Discovery Using the Expert

NASA Technical Reports Server (NTRS)

Das, Kamalika; Avrekh, Ilya; Matthews, Bryan; Sharma, Manali; Oza, Nikunj

2017-01-01

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the backend. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

Ask-the-Expert: Active Learning Based Knowledge Discovery Using the Expert

NASA Technical Reports Server (NTRS)

Das, Kamalika

2017-01-01

Often the manual review of large data sets, either for purposes of labeling unlabeled instances or for classifying meaningful results from uninteresting (but statistically significant) ones is extremely resource intensive, especially in terms of subject matter expert (SME) time. Use of active learning has been shown to diminish this review time significantly. However, since active learning is an iterative process of learning a classifier based on a small number of SME-provided labels at each iteration, the lack of an enabling tool can hinder the process of adoption of these technologies in real-life, in spite of their labor-saving potential. In this demo we present ASK-the-Expert, an interactive tool that allows SMEs to review instances from a data set and provide labels within a single framework. ASK-the-Expert is powered by an active learning algorithm for training a classifier in the back end. We demonstrate this system in the context of an aviation safety application, but the tool can be adopted to work as a simple review and labeling tool as well, without the use of active learning.

An Experience Sampling Study of Physical Activity and Positive Affect: Investigating the Role of Situational Motivation and Perceived Intensity Across Time.

PubMed

Guérin, Eva; Fortier, Michelle S; Sweet, Shane N

2013-04-18

The nature of the association between physical activity and positive affect is complex, prompting experts to recommend continued examination of moderating variables. The main purpose of this 2-week field study was to examine the influence of situational motivational regulations from self-determination theory (SDT) on changes in positive affect from pre- to post- to 3-hours post-physical activity. Another purpose was to clarify the relationship between physical activity intensity [i.e., Ratings of Perceived Exertion (RPE)] and positive affect at the stated time points. This study employed an experience sampling design using electronic questionnaires. Sixty-six healthy and active, multiple-role women provided recurrent assessments of their physical activity, situational motivation, and positive affect in their everyday lives over a 14-day period. Specifically, measures were obtained at the three time points of interest (i.e., pre-, post-, 3-hours post-physical activity). The data were analyzed using multilevel modeling. Results showed that intrinsic motivation was related to post-physical activity positive affect while the influence of identified regulation appeared 3-hours post-physical activity. In addition, RPE, which was significantly predicted by levels of introjection, was more strongly associated with an increase in positive affect post-physical activity than three hours later. The theoretical implications of these findings vis-à vis SDT, namely in regards to a viable motivational sequence predicting the influence of physical activity on affective states, are discussed. The findings regarding the differential influences of RPE and motivational regulations carries applications for facilitating women's well-being.

The influence of expertise on brain activation of the action observation network during anticipation of tennis and volleyball serves

PubMed Central

Balser, Nils; Lorey, Britta; Pilgramm, Sebastian; Naumann, Tim; Kindermann, Stefan; Stark, Rudolf; Zentgraf, Karen; Williams, A. Mark; Munzert, Jörn

2014-01-01

In many daily activities, and especially in sport, it is necessary to predict the effects of others' actions in order to initiate appropriate responses. Recently, researchers have suggested that the action–observation network (AON) including the cerebellum plays an essential role during such anticipation, particularly in sport expert performers. In the present study, we examined the influence of task-specific expertise on the AON by investigating differences between two expert groups trained in different sports while anticipating action effects. Altogether, 15 tennis and 16 volleyball experts anticipated the direction of observed tennis and volleyball serves while undergoing functional magnetic resonance imaging (fMRI). The expert group in each sport acted as novice controls in the other sport with which they had only little experience. When contrasting anticipation in both expertise conditions with the corresponding untrained sport, a stronger activation of AON areas (SPL, SMA), and particularly of cerebellar structures, was observed. Furthermore, the neural activation within the cerebellum and the SPL was linearly correlated with participant's anticipation performance, irrespective of the specific expertise. For the SPL, this relationship also holds when an expert performs a domain-specific anticipation task. Notably, the stronger activation of the cerebellum as well as of the SMA and the SPL in the expertise conditions suggests that experts rely on their more fine-tuned perceptual-motor representations that have improved during years of training when anticipating the effects of others' actions in their preferred sport. The association of activation within the SPL and the cerebellum with the task achievement suggests that these areas are the predominant brain sites involved in fast motor predictions. The SPL reflects the processing of domain-specific contextual information and the cerebellum the usage of a predictive internal model to solve the anticipation task. PMID:25136305

Use of cccupancy models to evaluate expert knowledge-based species-habitat relationships

USGS Publications Warehouse

Iglecia, Monica N.; Collazo, Jaime A.; McKerrow, Alexa

2012-01-01

Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

Brazilian recommendations of mechanical ventilation 2013. Part 2

PubMed Central

2014-01-01

Perspectives on invasive and noninvasive ventilatory support for critically ill patients are evolving, as much evidence indicates that ventilation may have positive effects on patient survival and the quality of the care provided in intensive care units in Brazil. For those reasons, the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB) and the Brazilian Thoracic Society (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT), represented by the Mechanical Ventilation Committee and the Commission of Intensive Therapy, respectively, decided to review the literature and draft recommendations for mechanical ventilation with the goal of creating a document for bedside guidance as to the best practices on mechanical ventilation available to their members. The document was based on the available evidence regarding 29 subtopics selected as the most relevant for the subject of interest. The project was developed in several stages, during which the selected topics were distributed among experts recommended by both societies with recent publications on the subject of interest and/or significant teaching and research activity in the field of mechanical ventilation in Brazil. The experts were divided into pairs that were charged with performing a thorough review of the international literature on each topic. All the experts met at the Forum on Mechanical Ventilation, which was held at the headquarters of AMIB in São Paulo on August 3 and 4, 2013, to collaboratively draft the final text corresponding to each sub-topic, which was presented to, appraised, discussed and approved in a plenary session that included all 58 participants and aimed to create the final document. PMID:25410835

Brazilian recommendations of mechanical ventilation 2013. Part I

PubMed Central

Barbas, Carmen Sílvia Valente; Ísola, Alexandre Marini; Farias, Augusto Manoel de Carvalho; Cavalcanti, Alexandre Biasi; Gama, Ana Maria Casati; Duarte, Antonio Carlos Magalhães; Vianna, Arthur; Serpa, Ary; Bravim, Bruno de Arruda; Pinheiro, Bruno do Valle; Mazza, Bruno Franco; de Carvalho, Carlos Roberto Ribeiro; Toufen, Carlos; David, Cid Marcos Nascimento; Taniguchi, Corine; Mazza, Débora Dutra da Silveira; Dragosavac, Desanka; Toledo, Diogo Oliveira; Costa, Eduardo Leite; Caser, Eliana Bernardete; Silva, Eliezer; Amorim, Fabio Ferreira; Saddy, Felipe; Galas, Filomena Regina Barbosa Gomes; Silva, Gisele Sampaio; de Matos, Gustavo Faissol Janot; Emmerich, João Claudio; Valiatti, Jorge Luis dos Santos; Teles, José Mario Meira; Victorino, Josué Almeida; Ferreira, Juliana Carvalho; Prodomo, Luciana Passuello do Vale; Hajjar, Ludhmila Abrahão; Martins, Luiz Cláudio; Malbouisson, Luiz Marcelo Sá; Vargas, Mara Ambrosina de Oliveira; Reis, Marco Antonio Soares; Amato, Marcelo Brito Passos; Holanda, Marcelo Alcântara; Park, Marcelo; Jacomelli, Marcia; Tavares, Marcos; Damasceno, Marta Cristina Paulette; Assunção, Murillo Santucci César; Damasceno, Moyzes Pinto Coelho Duarte; Youssef, Nazah Cherif Mohamad; Teixeira, Paulo José Zimmermann; Caruso, Pedro; Duarte, Péricles Almeida Delfino; Messeder, Octavio; Eid, Raquel Caserta; Rodrigues, Ricardo Goulart; de Jesus, Rodrigo Francisco; Kairalla, Ronaldo Adib; Justino, Sandra; Nemer, Sérgio Nogueira; Romero, Simone Barbosa; Amado, Verônica Moreira

2014-01-01

Perspectives on invasive and noninvasive ventilatory support for critically ill patients are evolving, as much evidence indicates that ventilation may have positive effects on patient survival and the quality of the care provided in intensive care units in Brazil. For those reasons, the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB) and the Brazilian Thoracic Society (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT), represented by the Mechanical Ventilation Committee and the Commission of Intensive Therapy, respectively, decided to review the literature and draft recommendations for mechanical ventilation with the goal of creating a document for bedside guidance as to the best practices on mechanical ventilation available to their members. The document was based on the available evidence regarding 29 subtopics selected as the most relevant for the subject of interest. The project was developed in several stages, during which the selected topics were distributed among experts recommended by both societies with recent publications on the subject of interest and/or significant teaching and research activity in the field of mechanical ventilation in Brazil. The experts were divided into pairs that were charged with performing a thorough review of the international literature on each topic. All the experts met at the Forum on Mechanical Ventilation, which was held at the headquarters of AMIB in São Paulo on August 3 and 4, 2013, to collaboratively draft the final text corresponding to each sub-topic, which was presented to, appraised, discussed and approved in a plenary session that included all 58 participants and aimed to create the final document. PMID:25028944

Brazilian recommendations of mechanical ventilation 2013. Part 2

PubMed Central

Barbas, Carmen Sílvia Valente; Ísola, Alexandre Marini; Farias, Augusto Manoel de Carvalho; Cavalcanti, Alexandre Biasi; Gama, Ana Maria Casati; Duarte, Antonio Carlos Magalhães; Vianna, Arthur; Serpa Neto, Ary; Bravim, Bruno de Arruda; Pinheiro, Bruno do Valle; Mazza, Bruno Franco; de Carvalho, Carlos Roberto Ribeiro; Toufen Júnior, Carlos; David, Cid Marcos Nascimento; Taniguchi, Corine; Mazza, Débora Dutra da Silveira; Dragosavac, Desanka; Toledo, Diogo Oliveira; Costa, Eduardo Leite; Caser, Eliana Bernadete; Silva, Eliezer; Amorim, Fabio Ferreira; Saddy, Felipe; Galas, Filomena Regina Barbosa Gomes; Silva, Gisele Sampaio; de Matos, Gustavo Faissol Janot; Emmerich, João Claudio; Valiatti, Jorge Luis dos Santos; Teles, José Mario Meira; Victorino, Josué Almeida; Ferreira, Juliana Carvalho; Prodomo, Luciana Passuello do Vale; Hajjar, Ludhmila Abrahão; Martins, Luiz Claudio; Malbouisson, Luis Marcelo Sá; Vargas, Mara Ambrosina de Oliveira; Reis, Marco Antonio Soares; Amato, Marcelo Brito Passos; Holanda, Marcelo Alcântara; Park, Marcelo; Jacomelli, Marcia; Tavares, Marcos; Damasceno, Marta Cristina Paulette; Assunção, Murillo Santucci César; Damasceno, Moyzes Pinto Coelho Duarte; Youssef, Nazah Cherif Mohamed; Teixeira, Paulo José Zimmermann; Caruso, Pedro; Duarte, Péricles Almeida Delfino; Messeder, Octavio; Eid, Raquel Caserta; Rodrigues, Ricardo Goulart; de Jesus, Rodrigo Francisco; Kairalla, Ronaldo Adib; Justino, Sandra; Nemer, Sergio Nogueira; Romero, Simone Barbosa; Amado, Verônica Moreira

2014-01-01

Perspectives on invasive and noninvasive ventilatory support for critically ill patients are evolving, as much evidence indicates that ventilation may have positive effects on patient survival and the quality of the care provided in intensive care units in Brazil. For those reasons, the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB) and the Brazilian Thoracic Society (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT), represented by the Mechanical Ventilation Committee and the Commission of Intensive Therapy, respectively, decided to review the literature and draft recommendations for mechanical ventilation with the goal of creating a document for bedside guidance as to the best practices on mechanical ventilation available to their members. The document was based on the available evidence regarding 29 subtopics selected as the most relevant for the subject of interest. The project was developed in several stages, during which the selected topics were distributed among experts recommended by both societies with recent publications on the subject of interest and/or significant teaching and research activity in the field of mechanical ventilation in Brazil. The experts were divided into pairs that were charged with performing a thorough review of the international literature on each topic. All the experts met at the Forum on Mechanical Ventilation, which was held at the headquarters of AMIB in São Paulo on August 3 and 4, 2013, to collaboratively draft the final text corresponding to each sub-topic, which was presented to, appraised, discussed and approved in a plenary session that included all 58 participants and aimed to create the final document. PMID:25295817

Brazilian recommendations of mechanical ventilation 2013. Part I

PubMed Central

2014-01-01

Perspectives on invasive and noninvasive ventilatory support for critically ill patients are evolving, as much evidence indicates that ventilation may have positive effects on patient survival and the quality of the care provided in intensive care units in Brazil. For those reasons, the Brazilian Association of Intensive Care Medicine (Associação de Medicina Intensiva Brasileira - AMIB) and the Brazilian Thoracic Society (Sociedade Brasileira de Pneumologia e Tisiologia - SBPT), represented by the Mechanical Ventilation Committee and the Commission of Intensive Therapy, respectively, decided to review the literature and draft recommendations for mechanical ventilation with the goal of creating a document for bedside guidance as to the best practices on mechanical ventilation available to their members. The document was based on the available evidence regarding 29 subtopics selected as the most relevant for the subject of interest. The project was developed in several stages, during which the selected topics were distributed among experts recommended by both societies with recent publications on the subject of interest and/or significant teaching and research activity in the field of mechanical ventilation in Brazil. The experts were divided into pairs that were charged with performing a thorough review of the international literature on each topic. All the experts met at the Forum on Mechanical Ventilation, which was held at the headquarters of AMIB in São Paulo on August 3 and 4, 2013, to collaboratively draft the final text corresponding to each sub-topic, which was presented to, appraised, discussed and approved in a plenary session that included all 58 participants and aimed to create the final document. PMID:25210957

Technical challenges related to implementation of a formula one real time data acquisition and analysis system in a paediatric intensive care unit.

PubMed

Matam, B Rajeswari; Duncan, Heather

2018-06-01

Most existing, expert monitoring systems do not provide the real time continuous analysis of the monitored physiological data that is necessary to detect transient or combined vital sign indicators nor do they provide long term storage of the data for retrospective analyses. In this paper we examine the feasibility of implementing a long term data storage system which has the ability to incorporate real-time data analytics, the system design, report the main technical issues encountered, the solutions implemented and the statistics of the data recorded. McLaren Electronic Systems expertise used to continually monitor and analyse the data from F1 racing cars in real time was utilised to implement a similar real-time data recording platform system adapted with real time analytics to suit the requirements of the intensive care environment. We encountered many technical (hardware and software) implementation challenges. However there were many advantages of the system once it was operational. They include: (1) The ability to store the data for long periods of time enabling access to historical physiological data. (2) The ability to alter the time axis to contract or expand periods of interest. (3) The ability to store and review ECG morphology retrospectively. (4) Detailed post event (cardiac/respiratory arrest or other clinically significant deteriorations in patients) data can be reviewed clinically as opposed to trend data providing valuable clinical insight. Informed mortality and morbidity reviews can be conducted. (5) Storage of waveform data capture to use for algorithm development for adaptive early warning systems. Recording data from bed-side monitors in intensive care/wards is feasible. It is possible to set up real time data recording and long term storage systems. These systems in future can be improved with additional patient specific metrics which predict the status of a patient thus paving the way for real time predictive monitoring.

Diabetes Treatment Breakthrough.

ERIC Educational Resources Information Center

Baker, Shelly; And Others

1993-01-01

Eight experts in visual impairment respond briefly to reports that intensive monitoring of blood glucose levels by persons with diabetes can lead to a 70% reduction in the progression of detectable diabetic retinopathy. Comments are generally optimistic, though some cautions are raised. (DB)

The prospects for hybrid electric vehicles, 2005-2020 : results of a Delphi Study.

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

Ng, H. K.; Santini, D. J.; Vyas, A. D.

1999-07-22

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among US automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future ''top-selling'' HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, withmore » methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020. Survey respondents view batteries as the component that contributes the most to the HEV cost increment. The mean projection for battery-alone range is 49 km in 2005, 70 km in 2010, and 92 km in 2020. Responding to a question relating to their personal vision of the most desirable HEV and its likely characteristics when introduced in the US market in the next decade, the experts predicted their ''vision'' HEV to have attributes very similar to those of the ''top-selling'' HEV. However, the ''vision'' HEV would cost significantly less. The experts projected attributes of three leading batteries for HEVs and projected acceleration times on battery power alone. The resulting battery packs are evaluated, and their initial and replacement costs are analyzed. These and several other opinions are summarized.« less

Catching on it early: Bodily and brain anticipatory mechanisms for excellence in sport.

PubMed

Abreu, Ana M; Candidi, Matteo; Aglioti, Salvatore M

2017-01-01

Programming and executing a subsequent move is inherently linked to the ability to anticipate the actions of others when interacting. Such fundamental social ability is particularly important in sport. Here, we discuss the possible mechanisms behind the highly sophisticated anticipation skills that characterize experts. We contend that prediction in sports might rely on a finely tuned perceptual system that endows experts with a fast, partially unconscious, pickup of relevant cues. Furthermore, we discuss the role of the multimodal, perceptuomotor, multiple-duty cells (mirror neurons) that play an important function in action anticipation by means of an inner motor simulation process. Finally, we suggest the role of predictive coding, interoception, and the enteric nervous system as the processual and biological support for intuition and "gut feelings" in sports-the missing link that might explain outstanding expert performance based on action anticipation. © 2017 Elsevier B.V. All rights reserved.

An expert system for prediction of aquatic toxicity of contaminants

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino, Dora R. May; Frank, Anthony M.; Hushon, Judith M.

1990-01-01

The National Fisheries Research Center-Great Lakes has developed an interactive computer program in muLISP that runs on an IBM-compatible microcomputer and uses a linear solvation energy relationship (LSER) to predict acute toxicity to four representative aquatic species from the detailed structure of an organic molecule. Using the SMILES formalism for a chemical structure, the expert system identifies all structural components and uses a knowledge base of rules based on an LSER to generate four structure-related parameter values. A separate module then relates these values to toxicity. The system is designed for rapid screening of potential chemical hazards before laboratory or field investigations are conducted and can be operated by users with little toxicological background. This is the first expert system based on LSER, relying on the first comprehensive compilation of rules and values for the estimation of LSER parameters.

ARGES: an Expert System for Fault Diagnosis Within Space-Based ECLS Systems

NASA Technical Reports Server (NTRS)

Pachura, David W.; Suleiman, Salem A.; Mendler, Andrew P.

1988-01-01

ARGES (Atmospheric Revitalization Group Expert System) is a demonstration prototype expert system for fault management for the Solid Amine, Water Desorbed (SAWD) CO2 removal assembly, associated with the Environmental Control and Life Support (ECLS) System. ARGES monitors and reduces data in real time from either the SAWD controller or a simulation of the SAWD assembly. It can detect gradual degradations or predict failures. This allows graceful shutdown and scheduled maintenance, which reduces crew maintenance overhead. Status and fault information is presented in a user interface that simulates what would be seen by a crewperson. The user interface employs animated color graphics and an object oriented approach to provide detailed status information, fault identification, and explanation of reasoning in a rapidly assimulated manner. In addition, ARGES recommends possible courses of action for predicted and actual faults. ARGES is seen as a forerunner of AI-based fault management systems for manned space systems.

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population

PubMed Central

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

Purpose To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). Methods 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into “no glaucoma”, “possible glaucoma” and “probable glaucoma” was defined as “gold standard”. A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. Results 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Conclusion Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations. PMID:27479301

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population.

PubMed

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into "no glaucoma", "possible glaucoma" and "probable glaucoma" was defined as "gold standard". A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations.

WHEN AND WHY DO HEDGEHOGS AND FOXES DIFFER?

PubMed

Keil, Frank C

2010-01-01

Philip E. Tetlock's finding that "hedgehog" experts (those with one big theory) are worse predictors than "foxes" (those with multiple, less comprehensive theories) offers fertile ground for future research. Are experts as likely to exhibit hedgehog- or fox-like tendencies in areas that call for explanatory, diagnostic, and skill-based expertise-as they did when Tetlock called on experts to make predictions? Do particular domains of expertise curtail or encourage different styles of expertise? Can we trace these different styles to childhood? Finally, can we nudge hedgehogs to be more like foxes? Current research can only grope at the answers to these questions, but they are essential to gauging the health of expert political judgment.

Experts and the Operational Bias of Television News: The Case of the Persian Gulf War.

ERIC Educational Resources Information Center

Steele, Janet E.

1995-01-01

Finds that news organizations chose expert sources to interpret the news during the Persian Gulf War according to how well their specialized knowledge conformed with television's "operational bias," or an emphasis on players, policies, and predictions of what will happen next. Argues that these processes undermine the ideals of balance…

AN EXPERT SYSTEM FOR HYDRODYNAMIC MIXING ZONE ANAYLSIS OF CONVENTIONAL AND TOXIC SUBMERGED SINGLE PORT DISCHARGES (CORMIX1)

EPA Science Inventory

U.S. water quality policy includes the concept of a mixing zone, a limited area or volume of water where the initial dilution of a discharge occurs. he Cornell Mixing Zone Expert System (CORMIX1) was developed to predict the dilution and trajectory of a submerged single port disc...

Predicting and explaining the movement of mesoscale oceanographic features using CLIPS

NASA Technical Reports Server (NTRS)

Bridges, Susan; Chen, Liang-Chun; Lybanon, Matthew

1994-01-01

The Naval Research Laboratory has developed an oceanographic expert system that describes the evolution of mesoscale features in the Gulf Stream region of the northwest Atlantic Ocean. These features include the Gulf Stream current and the warm and cold core eddies associated with the Gulf Stream. An explanation capability was added to the eddy prediction component of the expert system in order to allow the system to justify the reasoning process it uses to make predictions. The eddy prediction and explanation components of the system have recently been redesigned and translated from OPS83 to C and CLIPS and the new system is called WATE (Where Are Those Eddies). The new design has improved the system's readability, understandability and maintainability and will also allow the system to be incorporated into the Semi-Automated Mesoscale Analysis System which will eventually be embedded into the Navy's Tactical Environmental Support System, Third Generation, TESS(3).

Reliability and criterion-related validity testing (construct) of the Endotracheal Suction Assessment Tool (ESAT©).

PubMed

Davies, Kylie; Bulsara, Max K; Ramelet, Anne-Sylvie; Monterosso, Leanne

2018-05-01

To establish criterion-related construct validity and test-retest reliability for the Endotracheal Suction Assessment Tool© (ESAT©). Endotracheal tube suction performed in children can significantly affect clinical stability. Previously identified clinical indicators for endotracheal tube suction were used as criteria when designing the ESAT©. Content validity was reported previously. The final stages of psychometric testing are presented. Observational testing was used to measure construct validity and determine whether the ESAT© could guide "inexperienced" paediatric intensive care nurses' decision-making regarding endotracheal tube suction. Test-retest reliability of the ESAT© was performed at two time points. The researchers and paediatric intensive care nurse "experts" developed 10 hypothetical clinical scenarios with predetermined endotracheal tube suction outcomes. "Experienced" (n = 12) and "inexperienced" (n = 14) paediatric intensive care nurses were presented with the scenarios and the ESAT© guiding decision-making about whether to perform endotracheal tube suction for each scenario. Outcomes were compared with those predetermined by the "experts" (n = 9). Test-retest reliability of the ESAT© was measured at two consecutive time points (4 weeks apart) with "experienced" and "inexperienced" paediatric intensive care nurses using the same scenarios and tool to guide decision-making. No differences were observed between endotracheal tube suction decisions made by "experts" (n = 9), "inexperienced" (n = 14) and "experienced" (n = 12) nurses confirming the tool's construct validity. No differences were observed between groups for endotracheal tube suction decisions at T1 and T2. Criterion-related construct validity and test-retest reliability of the ESAT© were demonstrated. Further testing is recommended to confirm reliability in the clinical setting with the "inexperienced" nurse to guide decision-making related to endotracheal tube suction. The ESAT© is the first validated tool to systematically guide endotracheal nursing practice for the "inexperienced" nurse. © 2018 John Wiley & Sons Ltd.

Sensory representation of typicality of Cabernet franc wines related to phenolic composition: impact of ripening stage and maceration time.

PubMed

Cadot, Yves; Caillé, Soline; Samson, Alain; Barbeau, Gérard; Cheynier, Véronique

2012-06-30

Phenolics are responsible for important sensory properties of red wines, including colour, astringency, and possibly bitterness. From a technical viewpoint, the harvest date and the maceration duration are critical decisions for producing red wine with a distinctive style. But little is known about the evolution of phenolics and of their extractability during ripening to predict the composition of the wine and related sensory properties. The aim of this study was to understand the relationship between the sensory profile of the wines and (i) the ripening stage of the berries (harvest date) and (ii) the extraction time (maceration duration). Phenolic acids, flavonols, anthocyanins and proanthocyanidins of Vitis Vinifera var. Cabernet franc were measured in grapes and in wines from two stages of maturity and with two maceration durations. Phenolic composition was analysed by high performance liquid chromatography, after fractionation and thiolysis for proanthocyanidins. The distinctive style of wines was investigated by descriptive analysis (trained panel), Just About Right profiles and typicality assessment (wine expert panel). Relationships between phenolics and sensory attributes were established by multidimensional analysis, and phenolics were classified according to sensory data by ANOVA and PLS regressions. Astringency, bitterness, colour intensity and alcohol significantly increased with ripening and astringency and colour intensity increased with maceration time. Grape anthocyanins increased and thiolysis yield significantly decreased with ripening. In wine, proanthocyanidins increased, and mean degree of polymerisation and thiolysis yield decreased with longer extraction time. The high impact of harvest date on the sensory profiles could be due to changes in anthocyanin and sugar contents, but also to an evolution of proanthocyanidins. Moreover, proanthocyanidin composition was affected by maceration time as suggested by the decrease of thiolysis yield. Our results suggest that the wine sensory quality established by the expert panel, is linked as expected to grape quality at harvest, reflected by sugar and anthocyanin contents, but also by thiolysis yield, which requires elucidation. Copyright © 2012 Elsevier B.V. All rights reserved.

Development of a Job-Exposure Matrix (AsbJEM) to Estimate Occupational Exposure to Asbestos in Australia.

PubMed

van Oyen, Svein C; Peters, Susan; Alfonso, Helman; Fritschi, Lin; de Klerk, Nicholas H; Reid, Alison; Franklin, Peter; Gordon, Len; Benke, Geza; Musk, Arthur W

2015-07-01

Occupational exposure data on asbestos are limited and poorly integrated in Australia so that estimates of disease risk and attribution of disease causation are usually calculated from data that are not specific for local conditions. To develop a job-exposure matrix (AsbJEM) to estimate occupational asbestos exposure levels in Australia, making optimal use of the available exposure data. A dossier of all available exposure data in Australia and information on industry practices and controls was provided to an expert panel consisting of three local industrial hygienists with thorough knowledge of local and international work practices. The expert panel estimated asbestos exposures for combinations of occupation, industry, and time period. Intensity and frequency grades were estimated to enable the calculation of annual exposure levels for each occupation-industry combination for each time period. Two indicators of asbestos exposure intensity (mode and peak) were used to account for different patterns of exposure between occupations. Additionally, the probable type of asbestos fibre was determined for each situation. Asbestos exposures were estimated for 537 combinations of 224 occupations and 60 industries for four time periods (1943-1966; 1967-1986; 1987-2003; ≥2004). Workers in the asbestos manufacturing, shipyard, and insulation industries were estimated to have had the highest average exposures. Up until 1986, 46 occupation-industry combinations were estimated to have had exposures exceeding the current Australian exposure standard of 0.1 f ml(-1). Over 90% of exposed occupations were considered to have had exposure to a mixture of asbestos varieties including crocidolite. The AsbJEM provides empirically based quantified estimates of asbestos exposure levels for Australian jobs since 1943. This exposure assessment application will contribute to improved understanding and prediction of asbestos-related diseases and attribution of disease causation. © The Author 2015. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Application of predictive modelling techniques in industry: from food design up to risk assessment.

PubMed

Membré, Jeanne-Marie; Lambert, Ronald J W

2008-11-30

In this communication, examples of applications of predictive microbiology in industrial contexts (i.e. Nestlé and Unilever) are presented which cover a range of applications in food safety from formulation and process design to consumer safety risk assessment. A tailor-made, private expert system, developed to support safe product/process design assessment is introduced as an example of how predictive models can be deployed for use by non-experts. Its use in conjunction with other tools and software available in the public domain is discussed. Specific applications of predictive microbiology techniques are presented relating to investigations of either growth or limits to growth with respect to product formulation or process conditions. An example of a probabilistic exposure assessment model for chilled food application is provided and its potential added value as a food safety management tool in an industrial context is weighed against its disadvantages. The role of predictive microbiology in the suite of tools available to food industry and some of its advantages and constraints are discussed.

Chapter 1. Introduction. Recommendations and standard operating procedures for intensive care unit and hospital preparations for an influenza epidemic or mass disaster.

PubMed

Sprung, Charles L; Cohen, Robert; Adini, Bruria

2010-04-01

In December 2007, the European Society of Intensive Care Medicine established a Task Force to develop standard operating procedures (SOPs) for operating intensive care units (ICU) during an influenza epidemic or mass disaster. To provide direction for health care professionals in the preparation and management of emergency ICU situations during an influenza epidemic or mass disaster, standardize activities, and promote coordination and communication among the medical teams. Based on a literature review and contributions of content experts, a list of essential categories for managing emergency situations in the ICU were identified. Based on three cycles of a modified Delphi process, consensus was achieved regarding the categories. A primary author along with an expert group drafted SOPs for each category. Based on the Delphi cycles, the following key topics were found to be important for emergency preparedness: triage, infrastructure, essential equipment, manpower, protection of staff and patients, medical procedures, hospital policy, coordination and collaboration with interface units, registration and reporting, administrative policies and education. The draft SOPs serve as benchmarks for emergency preparedness and response of ICUs to emergencies or outbreak of pandemics.

Predicting microbiologically defined infection in febrile neutropenic episodes in children: global individual participant data multivariable meta-analysis

PubMed Central

Phillips, Robert S; Sung, Lillian; Amman, Roland A; Riley, Richard D; Castagnola, Elio; Haeusler, Gabrielle M; Klaassen, Robert; Tissing, Wim J E; Lehrnbecher, Thomas; Chisholm, Julia; Hakim, Hana; Ranasinghe, Neil; Paesmans, Marianne; Hann, Ian M; Stewart, Lesley A

2016-01-01

Background: Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one. Methods: The ‘Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation. Results: Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically ‘severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711–0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses. Conclusions: This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making. PMID:26954719

International Society of Geriatric Oncology Consensus on Geriatric Assessment in Older Patients With Cancer

PubMed Central

Wildiers, Hans; Heeren, Pieter; Puts, Martine; Topinkova, Eva; Janssen-Heijnen, Maryska L.G.; Extermann, Martine; Falandry, Claire; Artz, Andrew; Brain, Etienne; Colloca, Giuseppe; Flamaing, Johan; Karnakis, Theodora; Kenis, Cindy; Audisio, Riccardo A.; Mohile, Supriya; Repetto, Lazzaro; Van Leeuwen, Barbara; Milisen, Koen; Hurria, Arti

2014-01-01

Purpose To update the International Society of Geriatric Oncology (SIOG) 2005 recommendations on geriatric assessment (GA) in older patients with cancer. Methods SIOG composed a panel with expertise in geriatric oncology to develop consensus statements after literature review of key evidence on the following topics: rationale for performing GA; findings from a GA performed in geriatric oncology patients; ability of GA to predict oncology treatment–related complications; association between GA findings and overall survival (OS); impact of GA findings on oncology treatment decisions; composition of a GA, including domains and tools; and methods for implementing GA in clinical care. Results GA can be valuable in oncology practice for following reasons: detection of impairment not identified in routine history or physical examination, ability to predict severe treatment-related toxicity, ability to predict OS in a variety of tumors and treatment settings, and ability to influence treatment choice and intensity. The panel recommended that the following domains be evaluated in a GA: functional status, comorbidity, cognition, mental health status, fatigue, social status and support, nutrition, and presence of geriatric syndromes. Although several combinations of tools and various models are available for implementation of GA in oncology practice, the expert panel could not endorse one over another. Conclusion There is mounting data regarding the utility of GA in oncology practice; however, additional research is needed to continue to strengthen the evidence base. PMID:25071125

International Society of Geriatric Oncology consensus on geriatric assessment in older patients with cancer.

PubMed

Wildiers, Hans; Heeren, Pieter; Puts, Martine; Topinkova, Eva; Janssen-Heijnen, Maryska L G; Extermann, Martine; Falandry, Claire; Artz, Andrew; Brain, Etienne; Colloca, Giuseppe; Flamaing, Johan; Karnakis, Theodora; Kenis, Cindy; Audisio, Riccardo A; Mohile, Supriya; Repetto, Lazzaro; Van Leeuwen, Barbara; Milisen, Koen; Hurria, Arti

2014-08-20

To update the International Society of Geriatric Oncology (SIOG) 2005 recommendations on geriatric assessment (GA) in older patients with cancer. SIOG composed a panel with expertise in geriatric oncology to develop consensus statements after literature review of key evidence on the following topics: rationale for performing GA; findings from a GA performed in geriatric oncology patients; ability of GA to predict oncology treatment–related complications; association between GA findings and overall survival (OS); impact of GA findings on oncology treatment decisions; composition of a GA, including domains and tools; and methods for implementing GA in clinical care. GA can be valuable in oncology practice for following reasons: detection of impairment not identified in routine history or physical examination, ability to predict severe treatment-related toxicity, ability to predict OS in a variety of tumors and treatment settings, and ability to influence treatment choice and intensity. The panel recommended that the following domains be evaluated in a GA: functional status, comorbidity, cognition, mental health status, fatigue, social status and support, nutrition, and presence of geriatric syndromes. Although several combinations of tools and various models are available for implementation of GA in oncology practice, the expert panel could not endorse one over another. There is mounting data regarding the utility of GA in oncology practice; however, additional research is needed to continue to strengthen the evidence base.

Knowledge-based operation and management of communications systems

NASA Technical Reports Server (NTRS)

Heggestad, Harold M.

1988-01-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

The Montreux definition of neonatal ARDS: biological and clinical background behind the description of a new entity.

PubMed

De Luca, Daniele; van Kaam, Anton H; Tingay, David G; Courtney, Sherry E; Danhaive, Olivier; Carnielli, Virgilio P; Zimmermann, Luc J; Kneyber, Martin C J; Tissieres, Pierre; Brierley, Joe; Conti, Giorgio; Pillow, Jane J; Rimensberger, Peter C

2017-08-01

Acute respiratory distress syndrome (ARDS) is undefined in neonates, despite the long-standing existing formal recognition of ARDS syndrome in later life. We describe the Neonatal ARDS Project: an international, collaborative, multicentre, and multidisciplinary project which aimed to produce an ARDS consensus definition for neonates that is applicable from the perinatal period. The definition was created through discussions between five expert members of the European Society for Paediatric and Neonatal Intensive Care; four experts of the European Society for Paediatric Research; two independent experts from the USA and two from Australia. This Position Paper provides the first consensus definition for neonatal ARDS (called the Montreux definition). We also provide expert consensus that mechanisms causing ARDS in adults and older children-namely complex surfactant dysfunction, lung tissue inflammation, loss of lung volume, increased shunt, and diffuse alveolar damage-are also present in several critical neonatal respiratory disorders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Knowledge-based operation and management of communications systems

NASA Astrophysics Data System (ADS)

Heggestad, Harold M.

1988-11-01

Expert systems techniques are being applied in operation and control of the Defense Communications System (DCS), which has the mission of providing reliable worldwide voice, data and message services for U.S. forces and commands. Thousands of personnel operate DCS facilities, and many of their functions match the classical expert system scenario: complex, skill-intensive environments with a full spectrum of problems in training and retention, cost containment, modernization, and so on. Two of these functions are: (1) fault isolation and restoral of dedicated circuits at Tech Control Centers, and (2) network management for the Defense Switched Network (the modernized dial-up voice system currently replacing AUTOVON). An expert system for the first of these is deployed for evaluation purposes at Andrews Air Force Base, and plans are being made for procurement of operational systems. In the second area, knowledge obtained with a sophisticated simulator is being embedded in an expert system. The background, design and status of both projects are described.

Sports Specialization in Young Athletes

PubMed Central

Jayanthi, Neeru; Pinkham, Courtney; Dugas, Lara; Patrick, Brittany; LaBella, Cynthia

2013-01-01

Context: Sports specialization is intense training in 1 sport while excluding others. Sports specialization in early to middle childhood has become increasingly common. While most experts agree that some degree of sports specialization is necessary to achieve elite levels, there is some debate as to whether such intense practice time must begin during early childhood and to the exclusion of other sports to maximize potential for success. There is a concern that sports specialization before adolescence may be deleterious to a young athlete. Evidence Acquisition: PubMed and OVID were searched for English-language articles from 1990 to 2011 discussing sports specialization, expert athletes, or elite versus novice athletes, including original research articles, consensus opinions, and position statements. Results: For most sports, there is no evidence that intense training and specialization before puberty are necessary to achieve elite status. Risks of early sports specialization include higher rates of injury, increased psychological stress, and quitting sports at a young age. Sports specialization occurs along a continuum. Survey tools are being developed to identify where athletes fall along the spectrum of specialization. Conclusion: Some degree of sports specialization is necessary to develop elite-level skill development. However, for most sports, such intense training in a single sport to the exclusion of others should be delayed until late adolescence to optimize success while minimizing injury, psychological stress, and burnout. PMID:24427397

Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

PubMed Central

Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

Development and validation of an observation tool for the assessment of nursing pain management practices in intensive care unit in a standardized clinical simulation setting.

PubMed

Gosselin, Emilie; Bourgault, Patricia; Lavoie, Stephan; Coleman, Robin-Marie; Méziat-Burdin, Anne

2014-12-01

Pain management in the intensive care unit is often inadequate. There is no tool available to assess nursing pain management practices. The aim of this study was to develop and validate a measuring tool to assess nursing pain management in the intensive care unit during standardized clinical simulation. A literature review was performed to identify relevant components demonstrating optimal pain management in adult intensive care units and to integrate them in an observation tool. This tool was submitted to an expert panel and pretested. It was then used to assess pain management practice during 26 discrete standardized clinical simulation sessions with intensive care nurses. The Nursing Observation Tool for Pain Management (NOTPaM) contains 28 statements grouped into 8 categories, which are grouped into 4 dimensions: subjective assessment, objective assessment, interventions, and reassessment. The tool's internal consistency was calculated at a Cronbach's alpha of 0.436 for the whole tool; the alpha varies from 0.328 to 0.518 for each dimension. To evaluate the inter-rater reliability, intra-class correlation coefficient was used, which was calculated at 0.751 (p < .001) for the whole tool, with variations from 0.619 to 0.920 (p < .01) between dimensions. The expert panel was satisfied with the content and face validity of the tool. The psychometric qualities of the NOTPaM developed in this study are satisfactory. However, the tool could be improved with slight modifications. Nevertheless, it was useful in assessing intensive care nurses' pain management in a standardized clinical simulation. The NOTPaM is the first tool created for this purpose. Copyright © 2014 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

Climate Prediction Center - Expert Assessments: East Pacific Hurricane

Science.gov Websites

influence seasonal eastern Pacific hurricane activity, along with climate model forecasts. The outlook also National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map Administration (NOAA) Climate Prediction Center (CPC), and is produced in collaboration with scientists from the

A topological substructural molecular design approach for predicting mutagenesis end-points of alpha, beta-unsaturated carbonyl compounds.

PubMed

Pérez-Garrido, Alfonso; Helguera, Aliuska Morales; López, Gabriel Caravaca; Cordeiro, M Natália D S; Escudero, Amalio Garrido

2010-01-31

Chemically reactive, alpha, beta-unsaturated carbonyl compounds are common environmental pollutants able to produce a wide range of adverse effects, including, e.g. mutagenicity. This toxic property can often be related to chemical structure, in particular to specific molecular substructures or fragments (alerts), which can then be used in specialized software or expert systems for predictive purposes. In the past, there have been many attempts to predict the mutagenicity of alpha, beta-unsaturated carbonyl compounds through quantitative structure activity relationships (QSAR) but considering only one exclusive endpoint: the Ames test. Besides, even though those studies give a comprehensive understanding of the phenomenon, they do not provide substructural information that could be useful forward improving expert systems based on structural alerts (SAs). This work reports an evaluation of classification models to probe the mutagenic activity of alpha, beta-unsaturated carbonyl compounds over two endpoints--the Ames and mammalian cell gene mutation tests--based on linear discriminant analysis along with the topological Substructure molecular design (TOPS-MODE) approach. The obtained results showed the better ability of the TOPS-MODE approach in flagging structural alerts for the mutagenicity of these compounds compared to the expert system TOXTREE. Thus, the application of the present QSAR models can aid toxicologists in risk assessment and in prioritizing testing, as well as in the improvement of expert systems, such as the TOXTREE software, where SAs are implemented. 2009 Elsevier Ireland Ltd. All rights reserved.

Referral Consultant: An Expert System for Guiding Teachers in Referring Students for Special Education Placement. Final Report.

ERIC Educational Resources Information Center

Baer, Richard; And Others

In light of evidence indicating that referral itself often predicts student placement, an expert system was designed to assist educators to reduce bias in the process of referring students with suspected disabilities. A preliminary review of the literature looks at teacher perceptions as a predictor of handicapping conditions, referral bias, and…

Expertise facilitates the transfer of anticipation skill across domains.

PubMed

Rosalie, Simon M; Müller, Sean

2014-02-01

It is unclear whether perceptual-motor skill transfer is based upon similarity between the learning and transfer domains per identical elements theory, or facilitated by an understanding of underlying principles in accordance with general principle theory. Here, the predictions of identical elements theory, general principle theory, and aspects of a recently proposed model for the transfer of perceptual-motor skill with respect to expertise in the learning and transfer domains are examined. The capabilities of expert karate athletes, near-expert karate athletes, and novices to anticipate and respond to stimulus skills derived from taekwondo and Australian football were investigated in ecologically valid contexts using an in situ temporal occlusion paradigm and complex whole-body perceptual-motor skills. Results indicated that the karate experts and near-experts are as capable of using visual information to anticipate and guide motor skill responses as domain experts and near-experts in the taekwondo transfer domain, but only karate experts could perform like domain experts in the Australian football transfer domain. Findings suggest that transfer of anticipation skill is based upon expertise and an understanding of principles but may be supplemented by similarities that exist between the stimulus and response elements of the learning and transfer domains.

Expert elicitation survey on future wind energy costs

DOE PAGES

Wiser, Ryan; Jenni, Karen; Seel, Joachim; ...

2016-09-12

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends - in part - on the future costs of both onshore and offshore wind. In this paper, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions bymore » 2030 and 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R & D and industry strategy.« less

Expert elicitation survey on future wind energy costs

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

Wiser, Ryan; Jenni, Karen; Seel, Joachim

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends -- in part -- on the future costs of both onshore and offshore wind. Here, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions by 2030 andmore » 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R&D and industry strategy.« less

Expert elicitation survey on future wind energy costs

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

Wiser, Ryan; Jenni, Karen; Seel, Joachim

Wind energy supply has grown rapidly over the last decade. However, the long-term contribution of wind to future energy supply, and the degree to which policy support is necessary to motivate higher levels of deployment, depends - in part - on the future costs of both onshore and offshore wind. In this paper, we summarize the results of an expert elicitation survey of 163 of the world's foremost wind experts, aimed at better understanding future costs and technology advancement possibilities. Results suggest significant opportunities for cost reductions, but also underlying uncertainties. Under the median scenario, experts anticipate 24-30% reductions bymore » 2030 and 35-41% reductions by 2050 across the three wind applications studied. Costs could be even lower: experts predict a 10% chance that reductions will be more than 40% by 2030 and more than 50% by 2050. Insights gained through expert elicitation complement other tools for evaluating cost-reduction potential, and help inform policy and planning, R & D and industry strategy.« less

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

WHEN AND WHY DO HEDGEHOGS AND FOXES DIFFER?

PubMed Central

Keil, Frank C.

2011-01-01

Philip E. Tetlock’s finding that “hedgehog” experts (those with one big theory) are worse predictors than “foxes” (those with multiple, less comprehensive theories) offers fertile ground for future research. Are experts as likely to exhibit hedgehog- or fox-like tendencies in areas that call for explanatory, diagnostic, and skill-based expertise—as they did when Tetlock called on experts to make predictions? Do particular domains of expertise curtail or encourage different styles of expertise? Can we trace these different styles to childhood? Finally, can we nudge hedgehogs to be more like foxes? Current research can only grope at the answers to these questions, but they are essential to gauging the health of expert political judgment. PMID:21698070

Use (and abuse) of expert elicitation in support of decision making for public policy

PubMed Central

Morgan, M. Granger

2014-01-01

The elicitation of scientific and technical judgments from experts, in the form of subjective probability distributions, can be a valuable addition to other forms of evidence in support of public policy decision making. This paper explores when it is sensible to perform such elicitation and how that can best be done. A number of key issues are discussed, including topics on which there are, and are not, experts who have knowledge that provides a basis for making informed predictive judgments; the inadequacy of only using qualitative uncertainty language; the role of cognitive heuristics and of overconfidence; the choice of experts; the development, refinement, and iterative testing of elicitation protocols that are designed to help experts to consider systematically all relevant knowledge when they make their judgments; the treatment of uncertainty about model functional form; diversity of expert opinion; and when it does or does not make sense to combine judgments from different experts. Although it may be tempting to view expert elicitation as a low-cost, low-effort alternative to conducting serious research and analysis, it is neither. Rather, expert elicitation should build on and use the best available research and analysis and be undertaken only when, given those, the state of knowledge will remain insufficient to support timely informed assessment and decision making. PMID:24821779

Nordic guidelines for neuraxial blocks in disturbed haemostasis from the Scandinavian Society of Anaesthesiology and Intensive Care Medicine.

PubMed

Breivik, H; Bang, U; Jalonen, J; Vigfússon, G; Alahuhta, S; Lagerkranser, M

2010-01-01

Central neuraxial blocks (CNBs) for surgery and analgesia are an important part of anaesthesia practice in the Nordic countries. More active thromboprophylaxis with potent antihaemostatic drugs has increased the risk of bleeding into the spinal canal. National guidelines for minimizing this risk in patients who benefit from such blocks vary in their recommendations for safe practice. The Scandinavian Society of Anaesthesiology and Intensive Care Medicine (SSAI) appointed a task force of experts to establish a Nordic consensus on recommendations for best clinical practice in providing effective and safe CNBs in patients with an increased risk of bleeding. We performed a literature search and expert evaluation of evidence for (1) the possible benefits of CNBs on the outcome of anaesthesia and surgery, for (2) risks of spinal bleeding from hereditary and acquired bleeding disorders and antihaemostatic drugs used in surgical patients for thromboprophylaxis, for (3) risk evaluation in published case reports, and for (4) recommendations in published national guidelines. Proposals from the taskforce were available for feedback on the SSAI web-page during the summer of 2008. Neuraxial blocks can improve comfort and reduce morbidity (strong evidence) and mortality (moderate evidence) after surgical procedures. Haemostatic disorders, antihaemostatic drugs, anatomical abnormalities of the spine and spinal blood vessels, elderly patients, and renal and hepatic impairment are risk factors for spinal bleeding (strong evidence). Published national guidelines are mainly based on experts' opinions (weak evidence). The task force reached a consensus on Nordic guidelines, mainly based on our experts' opinions, but we acknowledge different practices in heparinization during vascular surgery and peri-operative administration of non-steroidal anti-inflammatory drugs during neuraxial blocks. Experts from the five Nordic countries offer consensus recommendations for safe clinical practice of neuraxial blocks and how to minimize the risks of serious complications from spinal bleeding. A brief version of the recommendations is available on http://www.ssai.info.

Psychophysiological Approach To Support Of Cosmonauts Performance Reliability

NASA Astrophysics Data System (ADS)

Nechaev, A. P.

Space flight factors may effect negatively on psychophysiological state (PPS) and work capacity of crewmembers, lead to errors in tasks performance. Such errors cannot be entirely prevented during "crew-spacecraft" system designing and/or crewmembers training as they are consequence of a human "psychophysiological troubles". In the present investigation we paid special attention to work and rest schedule (WRS) intensity due to sleep-wake rhythm disturbances and crewmembers overload may cause PPS aggravation. By methods of the correlation analysis of the data collected during 9 "Mir" missions (18 Russian cosmonauts, 226 flight weeks) the significant (p<0.05) interrelations between WRS intensity and cosmonauts PPS as well as between cosmonauts PPS and crewmembers errors (CE) frequency have been established. It allows to consider WRS intensity as "the controlling factor" in relation to crewmember's PPS. Quantitative characteristics of these interrelations have been also determined. This findings have been used for development of algorithm of crewmember's PPS management with the purpose of decrease in CE frequency. The algorithm can be briefly described in the following kind. On the basis of the analysis of crew forthcoming work experts should assess WRS intensity, possible crewmembers PPS alterations, and expected CE frequency. If CE frequency is allowable the management may be limited to recommendations that operative vigilance increase. If CE frequency is higher allowable it is necessary to carry out the measures on crewmembers PPS normalization by means of decrease in WRS intensity. The algorithm is intended for use in the on-ground expert system of psychophysiological support of cosmonauts performance.

Respiratory support in patients with acute respiratory distress syndrome: an expert opinion.

PubMed

Chiumello, Davide; Brochard, Laurent; Marini, John J; Slutsky, Arthur S; Mancebo, Jordi; Ranieri, V Marco; Thompson, B Taylor; Papazian, Laurent; Schultz, Marcus J; Amato, Marcelo; Gattinoni, Luciano; Mercat, Alain; Pesenti, Antonio; Talmor, Daniel; Vincent, Jean-Louis

2017-09-12

Acute respiratory distress syndrome (ARDS) is a common condition in intensive care unit patients and remains a major concern, with mortality rates of around 30-45% and considerable long-term morbidity. Respiratory support in these patients must be optimized to ensure adequate gas exchange while minimizing the risks of ventilator-induced lung injury. The aim of this expert opinion document is to review the available clinical evidence related to ventilator support and adjuvant therapies in order to provide evidence-based and experience-based clinical recommendations for the management of patients with ARDS.

The effects of musical training on structural brain development: a longitudinal study.

PubMed

Hyde, Krista L; Lerch, Jason; Norton, Andrea; Forgeard, Marie; Winner, Ellen; Evans, Alan C; Schlaug, Gottfried

2009-07-01

Long-term instrumental music training is an intense, multisensory and motor experience that offers an ideal opportunity to study structural brain plasticity in the developing brain in correlation with behavioral changes induced by training. Here, for the first time, we demonstrate structural brain changes after only 15 months of musical training in early childhood, which were correlated with improvements in musically relevant motor and auditory skills. These findings shed light on brain plasticity, and suggest that structural brain differences in adult experts (whether musicians or experts in other areas) are likely due to training-induced brain plasticity.

Spelling is Just a Click Away - A User-Centered Brain-Computer Interface Including Auto-Calibration and Predictive Text Entry.

PubMed

Kaufmann, Tobias; Völker, Stefan; Gunesch, Laura; Kübler, Andrea

2012-01-01

Brain-computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP-BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user's daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP-BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP-BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.

Spelling is Just a Click Away – A User-Centered Brain–Computer Interface Including Auto-Calibration and Predictive Text Entry

PubMed Central

Kaufmann, Tobias; Völker, Stefan; Gunesch, Laura; Kübler, Andrea

2012-01-01

Brain–computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP–BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user’s daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP–BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP–BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix. PMID:22833713

What defines an Expert? - Uncertainty in the interpretation of seismic data

NASA Astrophysics Data System (ADS)

Bond, C. E.

2008-12-01

Studies focusing on the elicitation of information from experts are concentrated primarily in economics and world markets, medical practice and expert witness testimonies. Expert elicitation theory has been applied in the natural sciences, most notably in the prediction of fluid flow in hydrological studies. In the geological sciences expert elicitation has been limited to theoretical analysis with studies focusing on the elicitation element, gaining expert opinion rather than necessarily understanding the basis behind the expert view. In these cases experts are defined in a traditional sense, based for example on: standing in the field, no. of years of experience, no. of peer reviewed publications, the experts position in a company hierarchy or academia. Here traditional indicators of expertise have been compared for significance on affective seismic interpretation. Polytomous regression analysis has been used to assess the relative significance of length and type of experience on the outcome of a seismic interpretation exercise. Following the initial analysis the techniques used by participants to interpret the seismic image were added as additional variables to the analysis. Specific technical skills and techniques were found to be more important for the affective geological interpretation of seismic data than the traditional indicators of expertise. The results of a seismic interpretation exercise, the techniques used to interpret the seismic and the participant's prior experience have been combined and analysed to answer the question - who is and what defines an expert?

As of 2012, what are the key predictive risk factors for pressure ulcers? Developing French guidelines for clinical practice.

PubMed

Michel, J-M; Willebois, S; Ribinik, P; Barrois, B; Colin, D; Passadori, Y

2012-10-01

An evaluation of predictive risk factors for pressure ulcers is essential in development of a preventive strategy on admission to hospitals and/or nursing homes. Identification of the predictive factors for pressure ulcers as of 2012. Systematic review of the literature querying the databases PASCAL Biomed, Cochrane Library and PubMed from 2000 through 2010. Immobility should be considered as a predictive risk factor for pressure ulcers (grade B). Undernutrition/malnutrition may also be a predictive risk factor for pressure ulcers (grade C). Even if the level of evidence is low, once these risk factors have been detected, management is essential. Sensitizing and mobilizing health care teams requires training in ways of tracking and screening. According to the experts, risk scales should be used. As decision aids, they should always be balanced and complemented by the clinical judgment of the treatment team. According to experts, it is important to know and predictively evaluate risk of pressure ulcers at the time of hospital admission. The predictive risk factors found in this study are identical to those highlighted at the 2001 consensus conference of which was PERSE was the promoter. Copyright © 2012. Published by Elsevier Masson SAS.

Microtiming in Swing and Funk affects the body movement behavior of music expert listeners.

PubMed

Kilchenmann, Lorenz; Senn, Olivier

2015-01-01

The theory of Participatory Discrepancies (or PDs) claims that minute temporal asynchronies (microtiming) in music performance are crucial for prompting bodily entrainment in listeners, which is a fundamental effect of the "groove" experience. Previous research has failed to find evidence to support this theory. The present study tested the influence of varying PD magnitudes on the beat-related body movement behavior of music listeners. 160 participants (79 music experts, 81 non-experts) listened to 12 music clips in either Funk or Swing style. These stimuli were based on two audio recordings (one in each style) of expert drum and bass duo performances. In one series of six clips, the PDs were downscaled from their originally performed magnitude to complete quantization in steps of 20%. In another series of six clips, the PDs were upscaled from their original magnitude to double magnitude in steps of 20%. The intensity of the listeners' beat-related head movement was measured using video-based motion capture technology and Fourier analysis. A mixed-design Four-Factor ANOVA showed that the PD manipulations had a significant effect on the expert listeners' entrainment behavior. The experts moved more when listening to stimuli with PDs that were downscaled by 60% compared to completely quantized stimuli. This finding offers partial support for PD theory: PDs of a certain magnitude do augment entrainment in listeners. But the effect was found to be small to moderately sized, and it affected music expert listeners only.

Microtiming in Swing and Funk affects the body movement behavior of music expert listeners

PubMed Central

Kilchenmann, Lorenz; Senn, Olivier

2015-01-01

The theory of Participatory Discrepancies (or PDs) claims that minute temporal asynchronies (microtiming) in music performance are crucial for prompting bodily entrainment in listeners, which is a fundamental effect of the “groove” experience. Previous research has failed to find evidence to support this theory. The present study tested the influence of varying PD magnitudes on the beat-related body movement behavior of music listeners. 160 participants (79 music experts, 81 non-experts) listened to 12 music clips in either Funk or Swing style. These stimuli were based on two audio recordings (one in each style) of expert drum and bass duo performances. In one series of six clips, the PDs were downscaled from their originally performed magnitude to complete quantization in steps of 20%. In another series of six clips, the PDs were upscaled from their original magnitude to double magnitude in steps of 20%. The intensity of the listeners' beat-related head movement was measured using video-based motion capture technology and Fourier analysis. A mixed-design Four-Factor ANOVA showed that the PD manipulations had a significant effect on the expert listeners' entrainment behavior. The experts moved more when listening to stimuli with PDs that were downscaled by 60% compared to completely quantized stimuli. This finding offers partial support for PD theory: PDs of a certain magnitude do augment entrainment in listeners. But the effect was found to be small to moderately sized, and it affected music expert listeners only. PMID:26347694

The Prediction of Item Parameters Based on Classical Test Theory and Latent Trait Theory

ERIC Educational Resources Information Center

Anil, Duygu

2008-01-01

In this study, the prediction power of the item characteristics based on the experts' predictions on conditions try-out practices cannot be applied was examined for item characteristics computed depending on classical test theory and two-parameters logistic model of latent trait theory. The study was carried out on 9914 randomly selected students…

A pediatric FOUR score coma scale: interrater reliability and predictive validity.

PubMed

Czaikowski, Brianna L; Liang, Hong; Stewart, C Todd

2014-04-01

The Full Outline of UnResponsiveness (FOUR) Score is a coma scale that consists of four components (eye and motor response, brainstem reflexes, and respiration). It was originally validated among the adult population and recently in a pediatric population. To enhance clinical assessment of pediatric intensive care unit patients, including those intubated and/or sedated, at our children's hospital, we modified the FOUR Score Scale for this population. This modified scale would provide many of the same advantages as the original, such as interrater reliability, simplicity, and elimination of the verbal component that is not compatible with the Glasgow Coma Scale (GCS), creating a more valuable neurological assessment tool for the nursing community. Our goal was to potentially provide greater information than the formally used GCS when assessing critically ill, neurologically impaired patients, including those sedated and/or intubated. Experienced pediatric intensive care unit nurses were trained as "expert raters." Two different nurses assessed each subject using the Pediatric FOUR Score Scale (PFSS), GCS, and Richmond Agitation Sedation Scale at three different time points. Data were compared with the Pediatric Cerebral Performance Category (PCPC) assessed by another nurse. Our hypothesis was that the PFSS and PCPC should highly correlate and the GCS and PCPC should correlate lower. Study results show that the PFSS is excellent for interrater reliability for trained nurse-rater pairs and prediction of poor outcome and in-hospital mortality, under various situations, but there were no statistically significant differences between the PFSS and the GCS. However, the PFSS does have the potential to provide greater neurological assessment in the intubated and/or sedated patient based on the outcomes of our study.

Generalizable Aspects of the Development of Expertise in Ballet across Countries and Cultures: A Perspective from the Expert-Performance Approach

ERIC Educational Resources Information Center

Hutchinson, Carla U.; Sachs-Ericsson, Natalie J.; Ericsson, K. Anders

2013-01-01

The expert-performance approach guided the collection of survey data on the developmental history of elite professional ballet dancers from three different countries/cultures (USA, Mexico, and Russia). The level of ballet expertise attained by age 18 was found to be uniquely predicted by only two factors, namely the total number of accumulated…

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Expert panel consensus recommendations for home blood pressure monitoring in Asia: the Hope Asia Network.

PubMed

Park, Sungha; Buranakitjaroen, Peera; Chen, Chen-Huan; Chia, Yook-Chin; Divinagracia, Romeo; Hoshide, Satoshi; Shin, Jinho; Siddique, Saulat; Sison, Jorge; Soenarta, Arieska Ann; Sogunuru, Guru Prasad; Tay, Jam Chin; Turana, Yuda; Wang, Ji-Guang; Zhang, Yuqing; Kario, Kazuomi

2018-04-01

Hypertension is the leading cause of mortality throughout Asia. Home blood pressure monitoring has the potential to improve hypertension control and is a useful adjunct to conventional office blood pressure measurements due to its diagnostic accuracy and prognostic value in predicting cardiovascular outcomes. At present, there are no region-specific guidelines addressing the use of home blood pressure monitoring in Asia. Therefore, an expert panel was convened to address the use of home blood pressure monitoring and develop key recommendations to help guide clinical practice throughout the Asia region. The resulting recommendations support the use of home blood pressure monitoring with a validated device as an accurate adjunct for diagnosing hypertension and predicting cardiovascular outcome. Diagnosis and treatment of hypertension should still be guided by conventional office/clinic blood pressure measurements. The expert panel encourages the incorporation of home blood pressure monitoring into local clinical guidelines and offers practical recommendations to ensure continuity of care where a validated home blood pressure device is not available.

"The cough game": are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed

Lewicky-Gaupp, Christina; Blaivas, Jerry; Clark, Amanda; McGuire, Edward J; Schaer, Gabriel; Tumbarello, Julie; Tunn, Ralf; DeLancey, John O L

2009-02-01

This study was carried out to determine whether five experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The five experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Correct responses ranged from 45.7% to 65.8% (mean 57.4 +/- 7.6). Sensitivity was 53.0 +/- 8.8% and specificity 61.2 +/- 12.4%. The positive predictive value was 48.8 +/- 8.2% and negative predictive value was 65.0 +/- 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40-0.50]. Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound.

“The Cough Game”: Are there characteristic urethrovesical movement patterns associated with stress incontinence?

PubMed Central

LEWICKY-GAUPP, Christina; BLAIVAS, Jerry; CLARK, Amanda; McGUIRE, Edward J.; SCHAER, Gabriel; TUMBARELLO, Julie; TUNN, Ralf; DeLANCEY, John O.L.

2009-01-01

Introduction and Hypothesis To determine if 5 experts in female stress urinary incontinence (SUI) could discover a pattern of urethrovesical movement characteristic of SUI on dynamic perineal ultrasound. Methods A secondary analysis of data from a case-control study was performed. Ultrasounds from 31 cases (daily SUI) and 42 controls (continent volunteers) of similar age and parity were analyzed. Perineal ultrasound was performed during a single cough. The 5 experts, blinded to continence status and urodynamics, classified each woman as stress continent or incontinent. Results Correct responses ranged from 45.7% to 65.8% (mean 57.4 ± 7.6). Sensitivity was 53.0 ± 8.8% and specificity 61.2 ± 12.4%. The positive predictive value was 48.8 ± 8.2% and negative predictive value was 65.0 ± 7.3%. Inter-rater reliability, evaluated by Cohen's kappa statistic, averaged 0.47 [95% CI 0.40 – 0.50]. Conclusions Experts could not identify a pattern of urethrovesical movement characteristic of SUI on ultrasound. PMID:18850057

Automated robot-assisted surgical skill evaluation: Predictive analytics approach.

PubMed

Fard, Mahtab J; Ameri, Sattar; Darin Ellis, R; Chinnam, Ratna B; Pandya, Abhilash K; Klein, Michael D

2018-02-01

Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise. Eight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise - novice and expert. Three classification methods - k-nearest neighbours, logistic regression and support vector machines - are applied. The result shows that the proposed framework can classify surgeons' expertise as novice or expert with an accuracy of 82.3% for knot tying and 89.9% for a suturing task. This study demonstrates and evaluates the ability of machine learning methods to automatically classify expert and novice surgeons using global movement features. Copyright © 2017 John Wiley & Sons, Ltd.

Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes.

PubMed

Alaa, Ahmed M; Yoon, Jinsung; Hu, Scott; van der Schaar, Mihaela

2018-01-01

In this paper, we develop a personalized real-time risk scoring algorithm that provides timely and granular assessments for the clinical acuity of ward patients based on their (temporal) lab tests and vital signs; the proposed risk scoring system ensures timely intensive care unit admissions for clinically deteriorating patients. The risk scoring system is based on the idea of sequential hypothesis testing under an uncertain time horizon. The system learns a set of latent patient subtypes from the offline electronic health record data, and trains a mixture of Gaussian Process experts, where each expert models the physiological data streams associated with a specific patient subtype. Transfer learning techniques are used to learn the relationship between a patient's latent subtype and her static admission information (e.g., age, gender, transfer status, ICD-9 codes, etc). Experiments conducted on data from a heterogeneous cohort of 6321 patients admitted to Ronald Reagan UCLA medical center show that our score significantly outperforms the currently deployed risk scores, such as the Rothman index, MEWS, APACHE, and SOFA scores, in terms of timeliness, true positive rate, and positive predictive value. Our results reflect the importance of adopting the concepts of personalized medicine in critical care settings; significant accuracy and timeliness gains can be achieved by accounting for the patients' heterogeneity. The proposed risk scoring methodology can confer huge clinical and social benefits on a massive number of critically ill inpatients who exhibit adverse outcomes including, but not limited to, cardiac arrests, respiratory arrests, and septic shocks.

Do clinicians prescribe exercise similarly in patients with different cardiovascular diseases? Findings from the EAPC EXPERT working group survey.

PubMed

Hansen, Dominique; Rovelo Ruiz, Gustavo; Doherty, Patrick; Iliou, Marie-Christine; Vromen, Tom; Hinton, Sally; Frederix, Ines; Wilhelm, Matthias; Schmid, Jean-Paul; Abreu, Ana; Ambrosetti, Marco; Garcia-Porrero, Esteban; Coninx, Karin; Dendale, Paul

2018-05-01

Background Although disease-specific exercise guidelines for cardiovascular disease (CVD) are widely available, it remains uncertain whether these different exercise guidelines are integrated properly for patients with different CVDs. The aim of this study was to assess the inter-clinician variance in exercise prescription for patients with various CVDs and to compare these prescriptions with recommendations from the EXercise Prescription in Everyday practice and Rehabilitative Training (EXPERT) tool, a digital decision support system for integrated state-of-the-art exercise prescription in CVD. Design The study was a prospective observational survey. Methods Fifty-three CV rehabilitation clinicians from nine European countries were asked to prescribe exercise intensity (based on percentage of peak heart rate (HR peak )), frequency, session duration, programme duration and exercise type (endurance or strength training) for the same five patients. Exercise prescriptions were compared between clinicians, and relationships with clinician characteristics were studied. In addition, these exercise prescriptions were compared with recommendations from the EXPERT tool. Results A large inter-clinician variance was found for prescribed exercise intensity (median (interquartile range (IQR)): 83 (13) % of HR peak ), frequency (median (IQR): 4 (2) days/week), session duration (median (IQR): 45 (18) min/session), programme duration (median (IQR): 12 (18) weeks), total exercise volume (median (IQR): 1215 (1961) peak-effort training hours) and prescription of strength training exercises (prescribed in 78% of all cases). Moreover, clinicians' exercise prescriptions were significantly different from those of the EXPERT tool ( p < 0.001). Conclusions This study reveals significant inter-clinician variance in exercise prescription for patients with different CVDs and disagreement with an integrated state-of-the-art system for exercise prescription, justifying the need for standardization efforts regarding integrated exercise prescription in CV rehabilitation.

[Increasing Number of Road Traffic Fatalities in Germany - Turnaround or Snap-Shot].

PubMed

Brand, S; Schmucker, U; Lob, G; Haasper, C; Juhra, C; Hell, W; Rieth, P; Matthes, G

2017-04-01

Introduction: For the first time since 20 years, the number of road accident fatalities in 2011 increased on German roads compared to earlier periods. Methods and Results: The presented paper submitted by the expert group for accident prevention investigates and discusses possible reasons for the observed increase in road traffic fatalities. Results: Climate changes as well as changes in economic environment, and technological progress in car and passenger safety are identified as possible reasons for the observed increase. Discussion: Mentioning the "Decade of Action for Road Safety" initiated by the UNO and coordinated by the WHO, the overall goal is a worldwide reduction of accident related road fatalities. But prognostic calculations predict an asymptotic approximation to a limit of road fatalities. To achieve a reduction by half until 2020 intense collaboration and disproportional expenditure are necessary. Conclusion: From the authors' point of view the current increase of traffic fatalities in Germany is rated as a snapshot rather than a turnaround. Georg Thieme Verlag KG Stuttgart · New York.

Blood biomarkers of kidney transplant rejection, an endless search?

PubMed

Jacquemont, Lola; Soulillou, Jean-Paul; Degauque, Nicolas

2017-07-01

The tailoring of immunosuppressive treatment is recognized as a promising strategy to improve long-term kidney graft outcome. To guide the standard care of transplant recipients, physicians need objective biomarkers that can identify an ongoing pathology with the graft or low intensity signals that will be later evolved to accelerated transplant rejection. The early identification of 'high-risk /low-risk' patients enables the adjustment of standard of caring, including managing the frequency of clinical visits and the immunosuppression dosing. Given their ease of availability and the compatibility with a large technical array, blood-based biomarkers have been widely scrutinized for use as potential predictive and diagnostic biomarkers. Areas covered: Here, the authors report on non-invasive biomarkers, such as modification of immune cell subsets and mRNA and miRNA profiles, identified in the blood of kidney transplant recipients collected before or after transplantation. Expert commentary: Combined with functional tests, the identification of biomarkers will improve our understanding of pathological processes and will contribute to a global improvement in clinical management.

Overview of the status of predictive computer models for skin sensitization (JRC Expert meeting on pre- and pro-haptens )

EPA Science Inventory

No abstract was prepared or requested. This is a short presentation aiming to present a status of what in silico models and approaches exists in the prediction of skin sensitization potential and/or potency.

Smallholder farms as stepping stone corridors for crop-raiding elephant in northern Tanzania: integration of Bayesian expert system and network simulator.

PubMed

Pittiglio, Claudia; Skidmore, Andrew K; van Gils, Hein A M J; McCall, Michael K; Prins, Herbert H T

2014-03-01

Crop-raiding elephants affect local livelihoods, undermining conservation efforts. Yet, crop-raiding patterns are poorly understood, making prediction and protection difficult. We hypothesized that raiding elephants use corridors between daytime refuges and farmland. Elephant counts, crop-raiding records, household surveys, Bayesian expert system, and least-cost path simulation were used to predict four alternative categories of daily corridors: (1) footpaths, (2) dry river beds, (3) stepping stones along scattered small farms, and (4) trajectories of shortest distance to refuges. The corridor alignments were compared in terms of their minimum cumulative resistance to elephant movement and related to crop-raiding zones quantified by a kernel density function. The "stepping stone" corridors predicted the crop-raiding patterns. Elephant presence was confirmed along these corridors, demonstrating that small farms located between refuges and contiguous farmland increase habitat connectivity for elephant. Our analysis successfully predicted elephant occurrence in farmland where daytime counts failed to detect nocturnal presence. These results have conservation management implications.

Combination and selection of traffic safety expert judgments for the prevention of driving risks.

PubMed

Cabello, Enrique; Conde, Cristina; de Diego, Isaac Martín; Moguerza, Javier M; Redchuk, Andrés

2012-11-02

In this paper, we describe a new framework to combine experts’ judgments for the prevention of driving risks in a cabin truck. In addition, the methodology shows how to choose among the experts the one whose predictions fit best the environmental conditions. The methodology is applied over data sets obtained from a high immersive cabin truck simulator in natural driving conditions. A nonparametric model, based in Nearest Neighbors combined with Restricted Least Squared methods is developed. Three experts were asked to evaluate the driving risk using a Visual Analog Scale (VAS), in order to measure the driving risk in a truck simulator where the vehicle dynamics factors were stored. Numerical results show that the methodology is suitable for embedding in real time systems.

The safety characterization of future plastic and composite intensive vehicles (PCIVs): a workshop for subject matter experts.

DOT National Transportation Integrated Search

2008-08-04

Mr. Keeler welcomed the workshop participants and noted that this research project was included in the 2007 Points of Pride 1 because it will facilitate the design and development of lighter, more fuelefficient, and safer next generation vehicl...

Learning the Lessons and Moving Ahead

ERIC Educational Resources Information Center

Grush, Mary

2007-01-01

Despite intensive security measures, institutions are still suffering breaches--sometimes quite painful and costly ones. After a major breach was reported at UCLA this past November, the author spoke with "Educause" security expert Rodney Petersen, to get his perspective and advice for higher education leadership. This article presents…

A revised ground-motion and intensity interpolation scheme for shakemap

USGS Publications Warehouse

Worden, C.B.; Wald, D.J.; Allen, T.I.; Lin, K.; Garcia, D.; Cua, G.

2010-01-01

We describe a weighted-average approach for incorporating various types of data (observed peak ground motions and intensities and estimates from groundmotion prediction equations) into the ShakeMap ground motion and intensity mapping framework. This approach represents a fundamental revision of our existing ShakeMap methodology. In addition, the increased availability of near-real-time macroseismic intensity data, the development of newrelationships between intensity and peak ground motions, and new relationships to directly predict intensity from earthquake source information have facilitated the inclusion of intensity measurements directly into ShakeMap computations. Our approach allows for the combination of (1) direct observations (ground-motion measurements or reported intensities), (2) observations converted from intensity to ground motion (or vice versa), and (3) estimated ground motions and intensities from prediction equations or numerical models. Critically, each of the aforementioned data types must include an estimate of its uncertainties, including those caused by scaling the influence of observations to surrounding grid points and those associated with estimates given an unknown fault geometry. The ShakeMap ground-motion and intensity estimates are an uncertainty-weighted combination of these various data and estimates. A natural by-product of this interpolation process is an estimate of total uncertainty at each point on the map, which can be vital for comprehensive inventory loss calculations. We perform a number of tests to validate this new methodology and find that it produces a substantial improvement in the accuracy of ground-motion predictions over empirical prediction equations alone.

Plus disease in retinopathy of prematurity: a continuous spectrum of vascular abnormality as basis of diagnostic variability

PubMed Central

Campbell, J. Peter; Kalpathy-Cramer, Jayashree; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D.; Hutcheson, Kelly; Shapiro, Michael J.; Repka, Michael X.; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E.; Chan, R.V. Paul; Chiang, Michael F.

2016-01-01

Objective To identify patterns of inter-expert discrepancy in plus disease diagnosis in retinopathy of prematurity (ROP). Design We developed two datasets of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP study, and determined a consensus reference standard diagnosis (RSD) for each image, based on 3 independent image graders and the clinical exam. We recruited 8 expert ROP clinicians to classify these images and compared the distribution of classifications between experts and the RSD. Subjects, Participants, and/or Controls Images obtained during routine ROP screening in neonatal intensive care units. 8 participating experts with >10 years of clinical ROP experience and >5 peer-reviewed ROP publications. Methods, Intervention, or Testing Expert classification of images of plus disease in ROP. Main Outcome Measures Inter-expert agreement (weighted kappa statistic), and agreement and bias on ordinal classification between experts (ANOVA) and the RSD (percent agreement). Results There was variable inter-expert agreement on diagnostic classifications between the 8 experts and the RSD (weighted kappa 0 – 0.75, mean 0.30). RSD agreement ranged from 80 – 94% agreement for the dataset of 100 images, and 29 – 79% for the dataset of 34 images. However, when images were ranked in order of disease severity (by average expert classification), the pattern of expert classification revealed a consistent systematic bias for each expert consistent with unique cut points for the diagnosis of plus disease and pre-plus disease. The two-way ANOVA model suggested a highly significant effect of both image and user on the average score (P<0.05, adjusted R2=0.82 for dataset A, and P< 0.05 and adjusted R2 =0.6615 for dataset B). Conclusions and Relevance There is wide variability in the classification of plus disease by ROP experts, which occurs because experts have different “cut-points” for the amounts of vascular abnormality required for presence of plus and pre-plus disease. This has important implications for research, teaching and patient care for ROP, and suggests that a continuous ROP plus disease severity score may more accurately reflect the behavior of expert ROP clinicians, and may better standardize classification in the future. PMID:27591053

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades.

PubMed

Cannell, R C; Tatum, J D; Belk, K E; Wise, J W; Clayton, R P; Smith, G C

1999-11-01

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.

Cardiac risk stratification in renal transplantation using a form of artificial intelligence.

PubMed

Heston, T F; Norman, D J; Barry, J M; Bennett, W M; Wilson, R A

1997-02-15

The purpose of this study was to determine if an expert network, a form of artificial intelligence, could effectively stratify cardiac risk in candidates for renal transplant. Input into the expert network consisted of clinical risk factors and thallium-201 stress test data. Clinical risk factor screening alone identified 95 of 189 patients as high risk. These 95 patients underwent thallium-201 stress testing, and 53 had either reversible or fixed defects. The other 42 patients were classified as low risk. This algorithm made up the "expert system," and during the 4-year follow-up period had a sensitivity of 82%, specificity of 77%, and accuracy of 78%. An artificial neural network was added to the expert system, creating an expert network. Input into the neural network consisted of both clinical variables and thallium-201 stress test data. There were 5 hidden nodes and the output (end point) was cardiac death. The expert network increased the specificity of the expert system alone from 77% to 90% (p < 0.001), the accuracy from 78% to 89% (p < 0.005), and maintained the overall sensitivity at 88%. An expert network based on clinical risk factor screening and thallium-201 stress testing had an accuracy of 89% in predicting the 4-year cardiac mortality among 189 renal transplant candidates.

Brain mechanisms of persuasion: how 'expert power' modulates memory and attitudes.

PubMed

Klucharev, Vasily; Smidts, Ale; Fernández, Guillén

2008-12-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as 'expert power', is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion.

Brain mechanisms of persuasion: how ‘expert power’ modulates memory and attitudes

PubMed Central

Smidts, Ale; Fernández, Guillén

2008-01-01

Human behaviour is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as ’expert power’, is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging, we probed the neural processes predicting these behavioural effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behaviour, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion. PMID:19015077

Debugging expert systems using a dynamically created hypertext network

NASA Technical Reports Server (NTRS)

Boyle, Craig D. B.; Schuette, John F.

1991-01-01

The labor intensive nature of expert system writing and debugging motivated this study. The hypothesis is that a hypertext based debugging tool is easier and faster than one traditional tool, the graphical execution trace. HESDE (Hypertext Expert System Debugging Environment) uses Hypertext nodes and links to represent the objects and their relationships created during the execution of a rule based expert system. HESDE operates transparently on top of the CLIPS (C Language Integrated Production System) rule based system environment and is used during the knowledge base debugging process. During the execution process HESDE builds an execution trace. Use of facts, rules, and their values are automatically stored in a Hypertext network for each execution cycle. After the execution process, the knowledge engineer may access the Hypertext network and browse the network created. The network may be viewed in terms of rules, facts, and values. An experiment was conducted to compare HESDE with a graphical debugging environment. Subjects were given representative tasks. For speed and accuracy, in eight of the eleven tasks given to subjects, HESDE was significantly better.

The Development of Selective Copying: Children's Learning from an Expert versus Their Mother

ERIC Educational Resources Information Center

Lucas, Amanda J.; Burdett, Emily R. R.; Burgess, Vanessa; Wood, Lara A.; McGuigan, Nicola; Harris, Paul L.; Whiten, Andrew

2017-01-01

This study tested the prediction that, with age, children should rely less on familiarity and more on expertise in their selective social learning. Experiment 1 (N = 50) found that 5- to 6-year-olds copied the technique their mother used to extract a prize from a novel puzzle box, in preference to both a stranger and an established expert. This…

Evidence reasoning method for constructing conditional probability tables in a Bayesian network of multimorbidity.

PubMed

Du, Yuanwei; Guo, Yubin

2015-01-01

The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. In order to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.

Aggregating Data for Computational Toxicology Applications ...

EPA Pesticide Factsheets

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built usi

Future leisure environments

Treesearch

Elwood L. Shafer; George H. Moeller; Russell E. Getty

1974-01-01

As an aid to policy- and decision-making about future environmental problems, a panel of experts was asked to predict the probabilities of future events associated with natural-resource management, wildland-recreation management, environmental pollution, population-workforce-leisure, and urban environments. Though some of the predictions projected to the year 2050 may...

Can Self-Reported Preference for Exercise Intensity Predict Physiologically Defined Self-Selected Exercise Intensity?

ERIC Educational Resources Information Center

Ekkekakis, Panteleimon; Lind, Erik; Joens-Matre, Roxane R.

2006-01-01

Exercise prescription guidelines emphasize the importance of individual preferences for different intensities, but such preferences have not been studied systematically. This study examined the hypothesis that the preference scale of the Preference for and Tolerance of the Intensity of Exercise Questionnaire would predict self-selected exercise…

Expert identification of visual primitives used by CNNs during mammogram classification

NASA Astrophysics Data System (ADS)

Wu, Jimmy; Peck, Diondra; Hsieh, Scott; Dialani, Vandana; Lehman, Constance D.; Zhou, Bolei; Syrgkanis, Vasilis; Mackey, Lester; Patterson, Genevieve

2018-02-01

This work interprets the internal representations of deep neural networks trained for classification of diseased tissue in 2D mammograms. We propose an expert-in-the-loop inter- pretation method to label the behavior of internal units in convolutional neural networks (CNNs). Expert radiologists identify that the visual patterns detected by the units are correlated with meaningful medical phenomena such as mass tissue and calcificated vessels. We demonstrate that several trained CNN models are able to produce explanatory descriptions to support the final classification decisions. We view this as an important first step toward interpreting the internal representations of medical classification CNNs and explaining their predictions.

Complex method to calculate objective assessments of information systems protection to improve expert assessments reliability

NASA Astrophysics Data System (ADS)

Abdenov, A. Zh; Trushin, V. A.; Abdenova, G. A.

2018-01-01

The paper considers the questions of filling the relevant SIEM nodes based on calculations of objective assessments in order to improve the reliability of subjective expert assessments. The proposed methodology is necessary for the most accurate security risk assessment of information systems. This technique is also intended for the purpose of establishing real-time operational information protection in the enterprise information systems. Risk calculations are based on objective estimates of the adverse events implementation probabilities, predictions of the damage magnitude from information security violations. Calculations of objective assessments are necessary to increase the reliability of the proposed expert assessments.

Beef quality grading using machine vision

NASA Astrophysics Data System (ADS)

Jeyamkondan, S.; Ray, N.; Kranzler, Glenn A.; Biju, Nisha

2000-12-01

A video image analysis system was developed to support automation of beef quality grading. Forty images of ribeye steaks were acquired. Fat and lean meat were differentiated using a fuzzy c-means clustering algorithm. Muscle longissimus dorsi (l.d.) was segmented from the ribeye using morphological operations. At the end of each iteration of erosion and dilation, a convex hull was fitted to the image and compactness was measured. The number of iterations was selected to yield the most compact l.d. Match between the l.d. muscle traced by an expert grader and that segmented by the program was 95.9%. Marbling and color features were extracted from the l.d. muscle and were used to build regression models to predict marbling and color scores. Quality grade was predicted using another regression model incorporating all features. Grades predicted by the model were statistically equivalent to the grades assigned by expert graders.

Ironic and Reinvestment Effects in Baseball Pitching: How Information About an Opponent Can Influence Performance Under Pressure.

PubMed

Gray, Rob; Orn, Anders; Woodman, Tim

2017-02-01

Are pressure-induced performance errors in experts associated with novice-like skill execution (as predicted by reinvestment/conscious processing theories) or expert execution toward a result that the performer typically intends to avoid (as predicted by ironic processes theory)? The present study directly compared these predictions using a baseball pitching task with two groups of experienced pitchers. One group was shown only their target, while the other group was shown the target and an ironic (avoid) zone. Both groups demonstrated significantly fewer target hits under pressure. For the target-only group, this was accompanied by significant changes in expertise-related kinematic variables. In the ironic group, the number of pitches thrown in the ironic zone was significantly higher under pressure, and there were no significant changes in kinematics. These results suggest that information about an opponent can influence the mechanisms underlying pressure-induced performance errors.

An expert system for prediction of chemical toxicity

USGS Publications Warehouse

Hickey, James P.; Aldridge, Andrew J.; Passino-Reader, Dora R.; Frank, Anthony M.

1992-01-01

The National Fisheries Research Center- Great Lakes has developed an interactive computer program that uses the structure of an organic molecule to predict its acute toxicity to four aquatic species. The expert system software, written in the muLISP language, identifies the skeletal structures and substituent groups of an organic molecule from a user-supplied standard chemical notation known as a SMILES string, and then generates values for four solvatochromic parameters. Multiple regression equations relate these parameters to the toxicities (expressed as log10LC50s and log10EC50s, along with 95% confidence intervals) for four species. The system is demonstrated by prediction of toxicity for anilide-type pesticides to the fathead minnow (Pimephales promelas). This software is designed for use on an IBM-compatible personal computer by personnel with minimal toxicology background for rapid estimation of chemical toxicity. The system has numerous applications, with much potential for use in the pharmaceutical industry

Automated Predictive Diagnosis (APD): A 3-tiered shell for building expert systems for automated predictions and decision making

NASA Technical Reports Server (NTRS)

Steib, Michael

1991-01-01

The APD software features include: On-line help, Three level architecture, (Logic environments, Setup/Application environment, Data environment), Explanation capability, and File handling. The kinds of experimentation and record keeping that leads to effective expert systems is facilitated by: (1) a library of inferencing modules (in the logic environment); (2) an explanation capability which reveals logic strategies to users; (3) automated file naming conventions; (4) an information retrieval system; and (5) on-line help. These aid with effective use of knowledge, debugging and experimentation. Since the APD software anticipates the logical rules becoming complicated, it is embedded in a production system language (CLIPS) to insure the full power of the production system paradigm of CLIPS and availability of the procedural language C. The development is discussed of the APD software and three example applications: toy, experimental, and operational prototype for submarine maintenance predictions.

Lessons in Leadership

ERIC Educational Resources Information Center

Cooper, Kenneth J.

2012-01-01

The hazing death of Florida A&M (FAMU) drum major Robert Champion and the long-concealed child sexual abuse by Jerry Sandusky at Penn State University have prompted an intense focus within higher education on how campus leaders should respond in times of crisis, particularly one involving suspected criminal activity. Experts say college…

Managing Risk in Complex Adult Professional Learning: The Facilitator's Role

ERIC Educational Resources Information Center

Ince, Amanda

2017-01-01

This article reports on the recognition and management of risk within the context of an intensive literacy intervention professional development programme, designed to enable expert literacy teachers become teacher-educators. The article suggests a conceptual model for recognising risk within professional learning opportunities and skills for…

Diagnosing Expertise: Human Capital, Decision Making, and Performance among Physicians

PubMed Central

Currie, Janet; MacLeod, W. Bentley

2017-01-01

Expert performance is often evaluated assuming that good experts have good outcomes. We examine expertise in medicine and develop a model that allows for two dimensions of physician performance: decision making and procedural skill. Better procedural skill increases the use of intensive procedures for everyone, while better decision making results in a reallocation of procedures from fewer low-risk to high-risk cases. We show that poor diagnosticians can be identified using administrative data and that improving decision making improves birth outcomes by reducing C-section rates at the bottom of the risk distribution and increasing them at the top of the distribution. PMID:29276336

Nutrition Considerations in the Pediatric Cardiac Intensive Care Unit Patient.

PubMed

Justice, Lindsey; Buckley, Jason R; Floh, Alejandro; Horsley, Megan; Alten, Jeffrey; Anand, Vijay; Schwartz, Steven M

2018-05-01

Adequate caloric intake plays a vital role in the course of illness and the recovery of critically ill patients. Nutritional status and nutrient delivery during critical illness have been linked to clinical outcomes such as mortality, incidence of infection, and length of stay. However, feeding practices with critically ill pediatric patients after cardiac surgery are variable. The Pediatric Cardiac Intensive Care Society sought to provide an expert review on provision of nutrition to pediatric cardiac intensive care patients, including caloric requirements, practical considerations for providing nutrition, safety of enteral nutrition in controversial populations, feeding considerations with chylothorax, and the benefits of feeding beyond nutrition. This article addresses these areas of concern and controversy.

[Evaluation of mimetic expression of schizophrenic and depressed patients by the psychiatrist].

PubMed

Schneider, F; Mattes, R; Adam, B; Heimann, H

1992-01-01

Facial videos of schizophrenic and depressive patients and of healthy controls when watching both funny and horror films and during emotionally positive or negative interviews were rated by psychiatrists (experts) and students (novices). The observers' task was to rate joy, fear, sadness, and expressivity on a 7-point unipolar intensity scale. The soundless facial videos were presented to each observer for exactly 2.5 min. The observer groups did not differ significantly in their ratings except for sadness. Psychiatrists consistently rated expressed sadness as less intense than students. Facial expressivity and joy were rated as less intense in both patient groups in comparison with healthy controls. Depressives expressed significantly more sadness.

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

Predicting reintroduction outcomes for highly vulnerable species that do not currently coexist with their key threats.

PubMed

Parlato, Elizabeth H; Armstrong, Doug P

2018-02-17

Predicting reintroduction outcomes before populations are released is inherently challenging. It becomes even more difficult when the species being considered for reintroduction no longer co-exists with the key threats limiting its distribution. However, data from other species facing the same threats can be used to make predictions under these circumstances. We present an integrated Bayesian modelling approach for predicting growth of a reintroduced population at a range of predator densities when no data are available for the species in the presence of that predator. North Island saddlebacks (Philesturnus rufusater) were extirpated from mainland New Zealand by exotic mammalian predators, particularly ship rats (black rats, Rattus rattus), but are now being considered for reintroduction to sites with intensive predator control, creating an opportunity to develop this approach. We initially modeled data from previous saddleback reintroductions to predator-free sites to predict population growth at a new predator-free site while accounting for random variation in vital rates among sites. We then predict population growth at different rat tracking rates (an index of rat density) by incorporating a previously modelled relationship between rat tracking and vital rates of another predator-sensitive species, the North Island robin (Petroica longipes), and account for the greater vulnerability of saddlebacks to rat predation using information on historical declines of both species. The results allow population growth to be predicted as a function of management effort while accounting for uncertainty, allowing formal decision analysis to be used to decide whether to proceed with a reintroduction. Similar approaches could potentially be applied to other situations where data on the species of interest are limited, providing an alternative to decision making based solely on expert judgment. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

[Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network].

PubMed

Noh, Wonjung; Seomun, Gyeongae

2015-06-01

This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

20170921 - An evaluation of selected (Q)SARs/expert systems for the Prediction of Skin Sensitization Potential (ASCCT)

EPA Science Inventory

Predictive testing to characterize substances for their skin sensitization potential has historically been based on animal models such as the Local Lymph Node Assay (LLNA) and the Guinea Pig Maximization Test (GPMT). In recent years, EU regulations have provided a strong incentiv...

STEMing the tide: using ingroup experts to inoculate women's self-concept in science, technology, engineering, and mathematics (STEM).

PubMed

Stout, Jane G; Dasgupta, Nilanjana; Hunsinger, Matthew; McManus, Melissa A

2011-02-01

Three studies tested a stereotype inoculation model, which proposed that contact with same-sex experts (advanced peers, professionals, professors) in academic environments involving science, technology, engineering, and mathematics (STEM) enhances women's self-concept in STEM, attitudes toward STEM, and motivation to pursue STEM careers. Two cross-sectional controlled experiments and 1 longitudinal naturalistic study in a calculus class revealed that exposure to female STEM experts promoted positive implicit attitudes and stronger implicit identification with STEM (Studies 1-3), greater self-efficacy in STEM (Study 3), and more effort on STEM tests (Study 1). Studies 2 and 3 suggested that the benefit of seeing same-sex experts is driven by greater subjective identification and connectedness with these individuals, which in turn predicts enhanced self-efficacy, domain identification, and commitment to pursue STEM careers. Importantly, women's own self-concept benefited from contact with female experts even though negative stereotypes about their gender and STEM remained active. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Holistic processing of musical notation: Dissociating failures of selective attention in experts and novices.

PubMed

Wong, Yetta Kwailing; Gauthier, Isabel

2010-12-01

Holistic processing (i.e., the tendency to process objects as wholes) is associated with face perception and also with expertise individuating novel objects. Surprisingly, recent work also reveals holistic effects in novice observers. It is unclear whether the same mechanisms support holistic effects in experts and in novices. In the present study, we measured holistic processing of music sequences using a selective attention task in participants who vary in music-reading expertise. We found that holistic effects were strategic in novices but were relatively automatic in experts. Correlational analyses revealed that individual holistic effects were predicted by both individual music-reading ability and neural responses for musical notation in the right fusiform face area (rFFA), but in opposite directions for experts and novices, suggesting that holistic effects in the two groups may be of different natures. To characterize expert perception, it is important not only to measure the tendency to process objects as wholes, but also to test whether this effect is dependent on task constraints.

A rule-based expert system applied to moisture durability of building envelopes

DOE PAGES

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.; ...

2018-01-09

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

A rule-based expert system applied to moisture durability of building envelopes

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

Boudreaux, Philip R.; Pallin, Simon B.; Accawi, Gina K.

The moisture durability of an envelope component such as a wall or roof is difficult to predict. Moisture durability depends on all the construction materials used, as well as the climate, orientation, air tightness, and indoor conditions. Modern building codes require more insulation and tighter construction but provide little guidance about how to ensure these energy-efficient assemblies remain moisture durable. Furthermore, as new products and materials are introduced, builders are increasingly uncertain about the long-term durability of their building envelope designs. Oak Ridge National Laboratory and the US Department of Energy’s Building America Program are applying a rule-based expert systemmore » methodology in a web tool to help designers determine whether a given wall design is likely to be moisture durable and provide expert guidance on moisture risk management specific to a wall design and climate. Finally, the expert system is populated with knowledge from both expert judgment and probabilistic hygrothermal simulation results.« less

Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks

NASA Technical Reports Server (NTRS)

Maskey, Manil; Cecil, Dan; Ramachandran, Rahul; Miller, Jeffrey J.

2018-01-01

Estimating tropical cyclone intensity by just using satellite image is a challenging problem. With successful application of the Dvorak technique for more than 30 years along with some modifications and improvements, it is still used worldwide for tropical cyclone intensity estimation. A number of semi-automated techniques have been derived using the original Dvorak technique. However, these techniques suffer from subjective bias as evident from the most recent estimations on October 10, 2017 at 1500 UTC for Tropical Storm Ophelia: The Dvorak intensity estimates ranged from T2.3/33 kt (Tropical Cyclone Number 2.3/33 knots) from UW-CIMSS (University of Wisconsin-Madison - Cooperative Institute for Meteorological Satellite Studies) to T3.0/45 kt from TAFB (the National Hurricane Center's Tropical Analysis and Forecast Branch) to T4.0/65 kt from SAB (NOAA/NESDIS Satellite Analysis Branch). In this particular case, two human experts at TAFB and SAB differed by 20 knots in their Dvorak analyses, and the automated version at the University of Wisconsin was 12 knots lower than either of them. The National Hurricane Center (NHC) estimates about 10-20 percent uncertainty in its post analysis when only satellite based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to tropical cyclone intensity. This study aims to utilize deep learning, the current state of the art in pattern recognition and image recognition, to address the need for an automated and objective tropical cyclone intensity estimation. Deep learning is a multi-layer neural network consisting of several layers of simple computational units. It learns discriminative features without relying on a human expert to identify which features are important. Our study mainly focuses on convolutional neural network (CNN), a deep learning algorithm, to develop an objective tropical cyclone intensity estimation. CNN is a supervised learning algorithm requiring a large number of training data. Since the archives of intensity data and tropical cyclone centric satellite images is openly available for use, the training data is easily created by combining the two. Results, case studies, prototypes, and advantages of this approach will be discussed.

Risk taking in adversarial situations: Civilization differences in chess experts.

PubMed

Chassy, Philippe; Gobet, Fernand

2015-08-01

The projections of experts in politics predict that a new world order will emerge within two decades. Being multipolar, this world will inevitably lead to frictions where civilizations and states will have to decide whether to risk conflict. Very often these decisions are informed if not taken by experts. To estimate risk-taking across civilizations, we examined strategies used in 667,599 chess games played over eleven years by chess experts from 11 different civilizations. We show that some civilizations are more inclined to settle for peace. Similarly, we show that once engaged in the battle, the level of risk taking varies significantly across civilizations, the boldest civilization using the riskiest strategy about 35% more than the most conservative civilization. We discuss which psychological factors might underpin these civilizational differences. Copyright © 2015. Published by Elsevier B.V.

Use of an expert system data analysis manager for space shuttle main engine test evaluation

NASA Technical Reports Server (NTRS)

Abernethy, Ken

1988-01-01

The ability to articulate, collect, and automate the application of the expertise needed for the analysis of space shuttle main engine (SSME) test data would be of great benefit to NASA liquid rocket engine experts. This paper describes a project whose goal is to build a rule-based expert system which incorporates such expertise. Experiential expertise, collected directly from the experts currently involved in SSME data analysis, is used to build a rule base to identify engine anomalies similar to those analyzed previously. Additionally, an alternate method of expertise capture is being explored. This method would generate rules inductively based on calculations made using a theoretical model of the SSME's operation. The latter rules would be capable of diagnosing anomalies which may not have appeared before, but whose effects can be predicted by the theoretical model.

Automatic segmentation for detecting uterine fibroid regions treated with MR-guided high intensity focused ultrasound (MR-HIFU).

PubMed

Antila, Kari; Nieminen, Heikki J; Sequeiros, Roberto Blanco; Ehnholm, Gösta

2014-07-01

Up to 25% of women suffer from uterine fibroids (UF) that cause infertility, pain, and discomfort. MR-guided high intensity focused ultrasound (MR-HIFU) is an emerging technique for noninvasive, computer-guided thermal ablation of UFs. The volume of induced necrosis is a predictor of the success of the treatment. However, accurate volume assessment by hand can be time consuming, and quick tools produce biased results. Therefore, fast and reliable tools are required in order to estimate the technical treatment outcome during the therapy event so as to predict symptom relief. A novel technique has been developed for the segmentation and volume assessment of the treated region. Conventional algorithms typically require user interaction ora priori knowledge of the target. The developed algorithm exploits the treatment plan, the coordinates of the intended ablation, for fully automatic segmentation with no user input. A good similarity to an expert-segmented manual reference was achieved (Dice similarity coefficient = 0.880 ± 0.074). The average automatic segmentation time was 1.6 ± 0.7 min per patient against an order of tens of minutes when done manually. The results suggest that the segmentation algorithm developed, requiring no user-input, provides a feasible and practical approach for the automatic evaluation of the boundary and volume of the HIFU-treated region.

Observed emotion frequency versus intensity as predictors of socioemotional maladjustment.

PubMed

Hernández, Maciel M; Eisenberg, Nancy; Valiente, Carlos; Spinrad, Tracy L; VanSchyndel, Sarah K; Diaz, Anjolii; Berger, Rebecca H; Silva, Kassondra M; Southworth, Jody; Piña, Armando A

2015-12-01

The purpose of this study was to assess whether observed emotional frequency (the proportion of instances an emotion was observed) and intensity (the strength of an emotion when it was observed) uniquely predicted kindergartners' (N = 301) internalizing and externalizing problems. Analyses were tested in a structural equation modeling (SEM) framework with data from multireporters (reports of problem behaviors from teachers and parents) and naturalistic observations of emotion in the fall semester. For observed positive emotion, both frequency and intensity negatively predicted parent- or teacher-reported internalizing symptoms. Anger frequency positively predicted parent- and teacher-reported externalizing symptoms, whereas anger intensity positively predicted parent- and teacher-reported externalizing and parent-reported internalizing symptoms. The findings support the importance of examining both aspects of emotion when predicting maladjustment. (c) 2015 APA, all rights reserved).

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

Pilat, Joseph F

The application of the methodology developed by the GenIV International Forum's (GIF's) Proliferation Resistance and Physical Protection (PR&PP) Working Group is an expert elicitation. Although the framework of the methodology is structured and systematic, it does not by itself constitute or require a formal elicitation. However, formal elicitation can be utilized in the PR&PP context to provide a systematic, credible and transparent qualitative analysis and develop input for quantitative analyses. This section provides an overview of expert elicitations, a discussion of the role formal expert elicitations can play in the PR&PP methodology, an outline of the formal expert elicitation processmore » and a brief practical guide to conducting formal expert elicitations. Expert elicitation is a process utilizing knowledgeable people in cases, for example, when an assessment is needed but physically based data is absent or open to interpretation. More specifically, it can be used to: (1) predict future events; (2) provide estimates on new, rare, complex or poorly understood phenomena; (3) integrate or interpret existing information; or (4) determine what is currently known, how well it is known or what is worth learning in a field. Expert elicitation can be informal or formal. The informal application of expert judgment is frequently used. Although it can produce good results, it often provides demonstrably biased or otherwise flawed answers to problems. This along with the absence of transparency can result in a loss of confidence when experts speak on issues. More formal expert elicitation is a structured process that makes use of people knowledgeable in certain areas to make assessments. The reason for advocating formal use is that the quality and accuracy of expert judgment comes from the completeness of the expert's understanding of the phenomena and the process used to elicit and analyze the data. The use of a more formal process to obtain, lU1derstand and analyze expert judgment has led to an improved acceptance of expert judgment because of the rigor and transparency of the results.« less

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

[Implementation of telemedicine services in the earthquake disaster relief: the best medical experts provide direct medical service to the affected people].

PubMed

Li, Tan-shi; Chai, Jia-ke

2013-05-01

To sum up the experience and significance of the remote medical consultation system used by the PLA General Hospital in 4/20 Sichuan Lushan earthquake medical rescue in 2013. After the Lushan earthquake in April 20, 2013, the expert medical rescue team of the PLA General Hospital immediately took the wireless portable telemedicine system to the converge hospital which had received many wounds in earthquake and had been connected with other hospitals, medical rescue teams and rescue ambulances to open the remote medical consultation system for disaster services including intensive care, emergency treatment, orthopedics, cerebral surgery, hepatobiliary surgery, obstetrics, gynecology and other related professional remote assistance services. The experts put forward the diagnosis and treatment for victims and had a benign interaction between the experts in disaster site and rear experts, as a result improved the ability of treatment of the disaster expert medical team. The PLA General Hospital treated more than 110 patients by remote medical consultation system in the Lushan earthquake and achieved real-time HD consultation and on-site operation guide. The using of remote medical consultation system achieved the connection between multimedia communication system and medical information system of the hospital and the interconnection of video, audio, data and medical services among each united hospitals, which can provide the significant experience of using remote medical consultation system in our disaster medical rescue activities.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, Clarence C., Jr.

1989-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 deg and +/- 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was develolped to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Far-field strains at failure were calculated from the strain intensity factor, and then strengths were calculated from the far-field strains using uniaxial stress-strain curves. The predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only +/- 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Definition of Specific Functions and Procedural Skills Required by Cuban Specialists in Intensive Care and Emergency Medicine.

PubMed

Véliz, Pedro L; Berra, Esperanza M; Jorna, Ana R

2015-07-01

INTRODUCTION Medical specialties' core curricula should take into account functions to be carried out, positions to be filled and populations to be served. The functions in the professional profile for specialty training of Cuban intensive care and emergency medicine specialists do not include all the activities that they actually perform in professional practice. OBJECTIVE Define the specific functions and procedural skills required of Cuban specialists in intensive care and emergency medicine. METHODS The study was conducted from April 2011 to September 2013. A three-stage methodological strategy was designed using qualitative techniques. By purposive maximum variation sampling, 82 professionals were selected. Documentary analysis and key informant criteria were used in the first stage. Two expert groups were formed in the second stage: one used various group techniques (focus group, oral and written brainstorming) and the second used a three-round Delphi method. In the final stage, a third group of experts was questioned in semistructured in-depth interviews, and a two-round Delphi method was employed to assess priorities. RESULTS Ultimately, 78 specific functions were defined: 47 (60.3%) patient care, 16 (20.5%) managerial, 6 (7.7%) teaching, and 9 (11.5%) research. Thirty-one procedural skills were identified. The specific functions and procedural skills defined relate to the profession's requirements in clinical care of the critically ill, management of patient services, teaching and research at the specialist's different occupational levels. CONCLUSIONS The specific functions and procedural skills required of intensive care and emergency medicine specialists were precisely identified by a scientific method. This product is key to improving the quality of teaching, research, administration and patient care in this specialty in Cuba. The specific functions and procedural skills identified are theoretical, practical, methodological and social contributions to inform future curricular reform and to help intensive care specialists enhance their performance in comprehensive patient care. KEYWORDS Intensive care, urgent care, emergency medicine, continuing medical education, curriculum, diagnostic techniques and procedures, medical residency, Cuba.

Intensive care unit-acquired weakness.

PubMed

Griffiths, Richard D; Hall, Jesse B

2010-03-01

Severe weakness is being recognized as a complication that impacts significantly on the pace and degree of recovery and return to former functional status of patients who survive the organ failures that mandate life-support therapies such as mechanical ventilation. Despite the apparent importance of this problem, much remains to be understood about its incidence, causes, prevention, and treatment. Review from literature and an expert round-table. The Brussels Round Table Conference in 2009 convened more than 20 experts in the fields of intensive care, neurology, and muscle physiology to review current understandings of intensive care unit-acquired weakness and to improve clinical outcome. Formal electrophysiological evaluation of patients with intensive care unit-acquired weakness can identify peripheral neuropathies, myopathies, and combinations of these disorders, although the correlation of these findings to weakness measurable at the bedside is not always precise. For routine clinical purposes, bedside assessment of neuromuscular function can be performed but is often confounded by complicating factors such as sedative and analgesic administration. Risk factors for development of intensive care unit-acquired weakness include bed rest itself, sepsis, and corticosteroid exposure. A strong association exists between weakness and long-term ventilator dependence; weakness is a major determinant of patient outcomes after surviving acute respiratory failure and may be present for months, or indefinitely, in the convalescence phase of critical illness. Although much has been learned about the physiology and cell and molecular biology of skeletal and diaphragm dysfunction under conditions of aging, exercise, disuse, and sepsis, the application of these understandings to the bedside requires more study in both bench models and patients. Although a trend toward greater immobilization and sedation of patients has characterized the past several decades of intensive care unit care, recent studies have demonstrated that early physical and occupational therapy, including during the period of intubation and ventilator support, can be safely performed and will likely improve patient outcomes with regard to functional status.

Seismogenic zones and attenuation laws for probabilistic seismic hazard assessment in low deformation area =

NASA Astrophysics Data System (ADS)

Le Goff, Boris

Seismic Hazard Analysis (PSHA), rather than the subjective methodologies that are currently used. This study focuses particularly in the definition of the seismic sources, through the seismotectonic zoning, and the determination of historical earthquake location. An important step in the Probabilistic Seismic Hazard Analysis consists in defining the seismic source model. Such a model expresses the association of the seismicity characteristics with the tectonically-active geological structures evidenced by seismotectonic studies. Given that most of the faults, in low seismic regions, are not characterized well enough, the source models are generally defined as areal zones, delimited with finite boundary polygons, within which the seismicity and the geological features are deemed homogeneous (e.g., focal depth, seismicity rate). Besides the lack of data (short period of instrumental seismicity), such a method generates different problems for regions with low seismic activity: 1) a large sensitivity of resulting hazard maps to the location of zone boundaries, while these boundaries are set by expert decisions; 2) the zoning cannot represent any variability or structural complexity in seismic parameters; 3) the seismicity rate is distributed throughout the zone and the location of the determinant information used for its calculation is lost. We investigate an alternative approach to model the seismotectonic zoning, with three main objectives: 1) obtaining a reproducible method that 2) preserves the information on the sources and extent of the uncertainties, so as to allow to propagate them (through Ground Motion Prediction Equations on to the hazard maps), and that 3) redefines the seismic source concept to debrief our knowledge on the seismogenic structures and the clustering. To do so, the Bayesian methods are favored. First, a generative model with two zones, differentiated by two different surface activity rates, was developed, creating synthetic catalogs drawn from a Poisson distribution as occurrence model, a truncated Gutenberg-Richter law as magnitudefrequency relationship and a uniform spatial distribution. The inference of this model permits to assess the minimum number of data, nmin, required in an earthquake catalog to recover the activity rates of both zones and the limit between them, with some level of accuracy. In this Bayesian model, the earthquake locations are essential. Consequently, these data have to be obtained with the best accuracy possible. The main difficulty is to reduce the location uncertainty of historical earthquakes. We propose to use the method of Bakun and Wentworth (1997) to reestimate the epicentral region of these events. This method uses directly the intensity data points rather than the isoseismal lines, set up by experts. The significant advantage in directly using individual intensity observations is that the procedures are explicit and hence the results are reproducible. The results of such a method provide an estimation of the epicentral region with levels of confidence appropriated for the number of intensity data points used. As example, we applied this methodology to the 1909 Benavente event, because of its controversial location and the particularly shape of its isoseismal lines. A new location of the 1909 Benavente event is presented in this study and the epicentral region of this event is expressed with confidence levels related to the number of intensity data points. This epicentral region is improved by the development of a new intensity-distance attenuation law, appropriate for the Portugal mainland. This law is the first one in Portugal mainland developed as a function of the magnitude (M) rather than the subjective epicentral intensity. From the logarithmic regression of each event, we define the equation form of the attenuation law. We obtained the following attenuation law: I= -1.9438 ln(D)+4.1Mw-9.5763 for 4.4 ≤ Mw ≤ 6.2 Using these attenuation laws, we reached to a magnitude estimation of the 1909 Benavente event that is in good agreement with the instrumental one. The epicentral region estimation was also improved with a tightening of the confidence level contours and a minimum of rms[MI] coming closer to the epicenter estimation of Karnik (1969). Finally, this two zone model will be a reference in the comparison with other models, which will incorporate other available data. Nevertheless, future improvements are needed to obtain a seismotectonic zoning. We emphasize that such an approach is reproducible once priors and data sets are chosen. Indeed, the objective is to incorporate expert opinions as priors, and avoid using expert decisions. Instead, the products will be directly the result of the inference, when only one model is considered, or the result of a combination of models in the Bayesian sense.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis M.; Negri, Jacquelyn A.; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2017-02-01

Early warning of post-fire debris-flow occurrence during intense rainfall has traditionally relied upon a library of regionally specific empirical rainfall intensity-duration thresholds. Development of this library and the calculation of rainfall intensity-duration thresholds often require several years of monitoring local rainfall and hydrologic response to rainstorms, a time-consuming approach where results are often only applicable to the specific region where data were collected. Here, we present a new, fully predictive approach that utilizes rainfall, hydrologic response, and readily available geospatial data to predict rainfall intensity-duration thresholds for debris-flow generation in recently burned locations in the western United States. Unlike the traditional approach to defining regional thresholds from historical data, the proposed methodology permits the direct calculation of rainfall intensity-duration thresholds for areas where no such data exist. The thresholds calculated by this method are demonstrated to provide predictions that are of similar accuracy, and in some cases outperform, previously published regional intensity-duration thresholds. The method also provides improved predictions of debris-flow likelihood, which can be incorporated into existing approaches for post-fire debris-flow hazard assessment. Our results also provide guidance for the operational expansion of post-fire debris-flow early warning systems in areas where empirically defined regional rainfall intensity-duration thresholds do not currently exist.

AI in medicine on its way from knowledge-intensive to data-intensive systems.

PubMed

Horn, W

2001-08-01

The last 20 years of research and development in the field of artificial intelligence in medicine (AIM) show a path from knowledge-intensive systems, which try to capture the essential knowledge of experts in a knowledge-based system, to data-intensive systems available today. Nowadays enormous amounts of information is accessible electronically. Large datasets are collected continuously monitoring physiological parameters of patients. Knowledge-based systems are needed to make use of all these data available and to help us to cope with the information explosion. In addition, temporal data analysis and intelligent information visualization can help us to get a summarized view of the change over time of clinical parameters. Integrating AIM modules into the daily-routine software environment of our care providers gives us a great chance for maintaining and improving quality of care.

Expanding ICU facilities in an epidemic: recommendations based on experience from the SARS epidemic in Hong Kong and Singapore.

PubMed

Gomersall, Charles D; Tai, Dessmon Y H; Loo, Shi; Derrick, James L; Goh, Mia Siang; Buckley, Thomas A; Chua, Catherine; Ho, Ka Man; Raghavan, Geeta P; Ho, Oi Man; Lee, Lay Beng; Joynt, Gavin M

2006-07-01

Epidemics have the potential to severely strain intensive care resources and may require an increase in intensive care capability. Few intensivists have direct experience of rapidly expanding intensive care services in response to an epidemic. This contribution presents the recommendations of an expert group from Hong Kong and Singapore who had direct experience of expanding intensive care services in response to the epidemic of severe acute respiratory syndrome. These recommendations cover training, infection control, staffing, communication and ethical issues. The issue of what equipment to purchase is not addressed. Early preparations should include fit testing of negative pressure respirators, training of reserve staff, sourcing of material for physical modifications to the ICU, development of infection control policies and training programmes, and discussion of triage and quarantine issues.

Scratching the surface of tomorrow's diagnostics: the Editor-in-Chief's opinion at the 15th year of Expert Review of Molecular Diagnostics.

PubMed

Lorincz, Attila; Raison, Claire

2015-01-01

Interview with Attila Lorincz by Claire Raison (Commissioning Editor) To mark the beginning of the 15th year of Expert Review of Molecular Diagnostics, the journal's Editor-in-Chief shares his expert knowledge on translational diagnostics, his opinion on recent controversies and his predictions for molecular diagnostics in 2015 and beyond. Attila Lorincz received his doctorate from Trinity College, Dublin, Republic of Ireland, and went on to become a research fellow at the University of California, Santa Barbara, CA, USA. During Professor Lorincz's research on human papillomavirus (HPV), he found several important and novel carcinogenic HPV types and pioneered the use of HPV DNA testing for clinical diagnostics. In 1988, Professor Lorincz's team produced the first HPV test to be FDA-approved for patients and in 2003, for general population cervical precancer screening. Now Professor of Molecular Epidemiology at the Centre for Cancer Prevention, Queen Mary University of London, UK, he and his team are furthering translational research into DNA methylation assays for cancer risk prediction.

Cognition of Experts and Top Managers about the Changes in Innovation Space

ERIC Educational Resources Information Center

Bergman, Jukka-Pekka; Jantunen, Ari; Saksa, Juha-Matti; Hurmelinna-Laukkanen, Pia

2007-01-01

The innovation space has become more complex and knowledge-intensive. As a result, it is increasingly important to see innovations as knowledge that is embodied in learning and technical and organisational knowledge bases. However, in processes such as innovation development, individuals make sense of it and utilise existing knowledge differently…

A Mixed-Response Intelligent Tutoring System Based on Learning from Demonstration

ERIC Educational Resources Information Center

Alvarez Xochihua, Omar

2012-01-01

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

Statistical model selection for better prediction and discovering science mechanisms that affect reliability

DOE PAGES

Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.

2015-08-19

Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less

Enhanced training using the life support for trauma and transport (LSTAT)

NASA Astrophysics Data System (ADS)

Hanson, Matthew E.; Toth, Louis S.; White, William H.

1999-07-01

The Life Support for Trauma and Transport (LSTAT) is an intensive care unit (ICU) in a 'stretcher' only 5 inches thick. LSTAT is a portable intensive care system which integrates state-of-the-art, commercial-off-the-shelf, hospital grade ICU devices into a single patient resuscitation, stabilization, evacuation, and surgical platform. LSTAT's current and evolving attributes include compact volume, low weight, integrated devices and subsystems, ergonomic patient-caregiver interface, patient and system information system, near-universal power interface, patient- caregiver hazardous environment isolation, and extensive evacuation vehicle interface compatibility. Although the LSTAT system architecture was established primarily to support diagnosis, monitoring and telemedicine consulting, the information architecture and communications suite can also support hosting training experiences and scenarios. The training scenario capabilities and features include: (1) moving training out to the field, (2) facilitating distributed training, (3) off-setting training with remote experts (or potentially embedded expert systems), and (4) facilitating training-by-simulation. Equipping the caregiver via such enhanced equipment and training should ultimately translate into better care for the patient.

The Volcanic Hazards Simulation: Students behaving expert-like when faced with challenging, authentic tasks during a simulated Volcanic Crisis

NASA Astrophysics Data System (ADS)

Dohaney, J. A.; kennedy, B.; Brogt, E.; Gravley, D.; Wilson, T.; O'Steen, B.

2011-12-01

This qualitative study investigates behaviors and experiences of upper-year geosciences undergraduate students during an intensive role-play simulation, in which the students interpret geological data streams and manage a volcanic crisis event. We present the development of the simulation, its academic tasks, (group) role assignment strategies and planned facilitator interventions over three iterations. We aim to develop and balance an authentic, intensive and highly engaging capstone activity for volcanology and geo-hazard courses. Interview data were collected from academic and professional experts in the fields of Volcanology and Hazard Management (n=11) in order to characterize expertise in the field, characteristics of key roles in the simulation, and to validate the authenticity of tasks and scenarios. In each iteration, observations and student artifacts were collected (total student participants: 68) along with interviews (n=36) and semi-structured, open-ended questionnaires (n=26). Our analysis of these data indicates that increasing the structure (i.e. organization, role-specific tasks and responsibilities) lessens non-productive group dynamics, which allows for an increase in difficulty of academic tasks within the simulation without increasing the cognitive load on students. Under these conditions, students exhibit professional expert-like behaviours, in particular in the quality of decision-making, communication skills and task-efficiency. In addition to illustrating the value of using this simulation to teach geosciences concepts, this study has implications for many complex situated-learning activities.

Predictive Data Tools Find Uses in Schools

ERIC Educational Resources Information Center

Sparks, Sarah D.

2011-01-01

The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

Climate Prediction Center - Expert Assessments Index

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Global Climate Data & Maps > ; Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are

Assessing the impact of climate change on vector-borne viruses in the EU through the elicitation of expert opinion.

PubMed

Gale, P; Brouwer, A; Ramnial, V; Kelly, L; Kosmider, R; Fooks, A R; Snary, E L

2010-02-01

Expert opinion was elicited to undertake a qualitative risk assessment to estimate the current and future risks to the European Union (EU) from five vector-borne viruses listed by the World Organization for Animal Health. It was predicted that climate change will increase the risk of incursions of African horse sickness virus (AHSV), Crimean-Congo haemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV) into the EU from other parts of the world, with African swine fever virus (ASFV) and West Nile virus (WNV) being less affected. Currently the predicted risks of incursion were lowest for RVFV and highest for ASFV. Risks of incursion were considered for six routes of entry (namely vectors, livestock, meat products, wildlife, pets and people). Climate change was predicted to increase the risk of incursion from entry of vectors for all five viruses to some degree, the strongest effects being predicted for AHSV, CCHFV and WNV. This work will facilitate identification of appropriate risk management options in relation to adaptations to climate change.

Research in space commercialization, technology transfer, and communications, volume 2

NASA Technical Reports Server (NTRS)

Dunn, D. A.; Agnew, C. E.

1983-01-01

Spectrum management, models for evaluating communication systems, the communications regulatory environment, expert prediction and consensus, remote sensing, and manned space operations research are discussed.

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

PubMed

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

Track-pattern-based seasonal prediction model for intense tropical cyclone activities over the North Atlantic and the western North Pacific basins

NASA Astrophysics Data System (ADS)

Choi, W.; Ho, C. H.

2015-12-01

Intense tropical cyclones (TCs) accompanying heavy rainfall and destructive wind gusts sometimes cause incredible socio-economic damages in the regions near their landfall. This study aims to analyze intense TC activities in the North Atlantic (NA) and the western North Pacific (WNP) basins and develop their track propensity seasonal prediction model. Considering that the number of TCs in the NA basin is much smaller than that in the WNP basin, different intensity criteria are used; category 1 and above for NA and category 3 and above for WNP based on Saffir-Simpson hurricane wind scale. By using a fuzzy clustering method, intense TC tracks in the NA and the WNP basins are classified into two and three representative patterns, respectively. Each pattern shows empirical relationships with climate variabilities such as sea surface temperature distribution associated with El Niño/La Niña or Atlantic Meridional Mode, Pacific decadal oscillation, upper and low level zonal wind, and strength of subtropical high. The hybrid statistical-dynamical method has been used to develop the seasonal prediction model for each pattern based on statistical relationships between the intense TC activity and seasonal averaged key predictors. The model performance is statistically assessed by cross validation for the training period (1982-2013) and has been applied for the 2014 and 2015 prediction. This study suggests applicability of this model to real prediction work and provide bridgehead of attempt for intense TC prediction.

Application of remote sensing data to monitoring of oil pollution as part of the environmental expert system

NASA Astrophysics Data System (ADS)

Shagarova, Lyudmila; Muratova, Mira; Abuova, Sholpan

2016-07-01

The impact of oil-producing facilities on the environment is caused by toxicity of hydrocarbons and by-products, a variety of chemicals used in industrial processes, as well as specificity of production, treatment, transportation and storage of oil and oil products. To predict the state of the geological environment, scientists carry out investigations, which help to choose the optimal strategy for creation of the expert system taking into account simulations and to provide efficient use of available environmentally relevant information related to the current state of the geological environment. The expert system is a complex of interconnected blocks, one of which is the information on the presence of oil pollution, which can be identified using satellite imagery. The satellite imagery has practical application in monitoring of oil pollution, as it allows specialists to identify oil spills remotely and to determine their characteristics based on the differentiation of the surface reflectance spectra. Snapshots are used to estimate the area of oil-contamination and location of spills. To detect contaminants it is necessary to perform the following steps in processing of the remote sensing data: - Identify and isolate all the dark deformations in the satellite images, as a result of processing of segmentation and threshold processing; - Calculate statistical parameters of dark deformations, i.e., signs similar to areas prone to contamination. These signs are related to the geometry of formation, their physical changes (backscattering value) and the image context; - Classify the selected spectral anomalies as oil pollution and oil sludge. On the basis of classification of satellite imagery, the objects of oil pollution are detected and deciphering signs are analyzed in order to refer classified objects to implicit or explicit contaminations. To detect oil pollution, pixels are classified into categories with learning on the given areas with creation of the corresponding signature for each of them, i.e. the area with a given class, which is used to determine centers of classes in further supervised classification. The classification process compares the luminance of pixels with the training sample, as a result, each pixel is referred to the most appropriate class of objects. The development of an expert system using digital space information will extend the circle of problems solved in the environmental protection, creation of complex schemes of intensive development of hydrocarbon production regions in view of environmental risks.

Expert forecasts and the emergence of water scarcity on public agendas

USGS Publications Warehouse

Graffy, E.A.

2006-01-01

Expert forecasts of worldwide water scarcity depict conditions that call for proactive, preventive, coordinated water governance, but they have not been matched by public agendas of commensurate scope and urgency in the United States. This disconnect can not be adequately explained without some attention to attributes of forecasts themselves. I propose that the institutional fragmentation of water expertise and prevailing patterns of communication about water scarcity militate against the formulation of a common public definition of the problem and encourage reliance on unambiguous crises to stimulate social and policy agenda setting. I do not argue that expert forecasts should drive public agendas deterministically, but if their purpose is to help prevent water crises (not just predict them), then a greater effort is needed to overcome the barriers to meaningful public scrutiny of expert claims and evaluation of water strategies presently in place. Copyright ?? 2006 Taylor & Francis Group, LLC.

[Medical expert consensus in AH on the clinical use of triple fixed-dose antihypertensive therapy in Spain].

PubMed

Mazón, P; Galve, E; Gómez, J; Gorostidi, M; Górriz, J L; Mediavilla, J D

The opinion of experts (different specialties) on the triple fixed-dose antihypertensive therapy in clinical practice may differ. Online questionnaire with controversial aspects of the triple therapy answered by panel of experts in hypertension (HT) using two-round modified Delphi method. The questionnaire was completed by 158 experts: Internal Medicine (49), Nephrology (26), Cardiology (83). Consensus was reached (agreement) on 27/45 items (60%); 7 items showed differences statistically significant. Consensus was reached regarding: Predictive factors in the need for combination therapy and its efficacy vs. increasing the dose of a pretreatment, and advantage of triple therapy (prescription/adherence/cost/pressure control) vs. free combination. This consensus provides an overview of the clinical use of triple therapy in moderate-severe and resistant/difficult to control HT. Copyright © 2016 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Wine Expertise Predicts Taste Phenotype

PubMed Central

Hayes, John E; Pickering, Gary J

2011-01-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance – with appropriate caveats about populations tested, outcomes measured and psychophysical methods used – an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli. PMID:22888174

Developing and validating a model to predict the success of an IHCS implementation: the Readiness for Implementation Model.

PubMed

Wen, Kuang-Yi; Gustafson, David H; Hawkins, Robert P; Brennan, Patricia F; Dinauer, Susan; Johnson, Pauley R; Siegler, Tracy

2010-01-01

To develop and validate the Readiness for Implementation Model (RIM). This model predicts a healthcare organization's potential for success in implementing an interactive health communication system (IHCS). The model consists of seven weighted factors, with each factor containing five to seven elements. Two decision-analytic approaches, self-explicated and conjoint analysis, were used to measure the weights of the RIM with a sample of 410 experts. The RIM model with weights was then validated in a prospective study of 25 IHCS implementation cases. Orthogonal main effects design was used to develop 700 conjoint-analysis profiles, which varied on seven factors. Each of the 410 experts rated the importance and desirability of the factors and their levels, as well as a set of 10 different profiles. For the prospective 25-case validation, three time-repeated measures of the RIM scores were collected for comparison with the implementation outcomes. Two of the seven factors, 'organizational motivation' and 'meeting user needs,' were found to be most important in predicting implementation readiness. No statistically significant difference was found in the predictive validity of the two approaches (self-explicated and conjoint analysis). The RIM was a better predictor for the 1-year implementation outcome than the half-year outcome. The expert sample, the order of the survey tasks, the additive model, and basing the RIM cut-off score on experience are possible limitations of the study. The RIM needs to be empirically evaluated in institutions adopting IHCS and sustaining the system in the long term.

Effects of expertise on football betting.

PubMed

Khazaal, Yasser; Chatton, Anne; Billieux, Joël; Bizzini, Lucio; Monney, Grégoire; Fresard, Emmanuelle; Thorens, Gabriel; Bondolfi, Guido; El-Guebaly, Nady; Zullino, Daniele; Khan, Riaz

2012-05-11

Football (soccer) is one of the most popular sports in the world, including Europe. It is associated with important betting activities. A common belief, widely spread among those who participate in gambling activities, is that knowledge and expertise on football lead to better prediction skills for match outcomes. If unfounded, however, this belief should be considered as a form of "illusion of control." The aim of this study was to examine whether football experts are better than nonexperts at predicting football match scores. Two hundred and fifty-eight persons took part in the study: 21.3% as football experts, 54.3% as laypersons (non-initiated to football), and 24.4% as football amateurs. They predicted the scores of the first 10 matches of the 2008 UEFA European Football Championship. Logistic regressions were carried out to assess the link between the accuracy of the forecasted scores and the expertise of the participants (expert, amateur, layperson), controlling for age and gender. The variables assessed did not predict the accuracy of scoring prognosis (R2 ranged from 1% to 6%). Expertise, age, and gender did not appear to have an impact on the accuracy of the football match prognoses. Therefore, the belief that football expertise improves betting skills is no more than a cognitive distortion called the "illusion of control." Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Public health policies may need to consider the phenomenon in order to prevent problem gambling related to football betting.

Wine Expertise Predicts Taste Phenotype.

PubMed

Hayes, John E; Pickering, Gary J

2012-03-01

Taste phenotypes have long been studied in relation to alcohol intake, dependence, and family history, with contradictory findings. However, on balance - with appropriate caveats about populations tested, outcomes measured and psychophysical methods used - an association between variation in taste responsiveness and some alcohol behaviors is supported. Recent work suggests super-tasting (operationalized via propylthiouracil (PROP) bitterness) not only associates with heightened response but also with more acute discrimination between stimuli. Here, we explore relationships between food and beverage adventurousness and taste phenotype. A convenience sample of wine drinkers (n=330) were recruited in Ontario and phenotyped for PROP bitterness via filter paper disk. They also filled out a short questionnaire regarding willingness to try new foods, alcoholic beverages and wines as well as level of wine involvement, which was used to classify them as a wine expert (n=110) or wine consumer (n=220). In univariate logisitic models, food adventurousness predicted trying new wines and beverages but not expertise. Likewise, wine expertise predicted willingness to try new wines and beverages but not foods. In separate multivariate logistic models, willingness to try new wines and beverages was predicted by expertise and food adventurousness but not PROP. However, mean PROP bitterness was higher among wine experts than wine consumers, and the conditional distribution functions differed between experts and consumers. In contrast, PROP means and distributions did not differ with food adventurousness. These data suggest individuals may self-select for specific professions based on sensory ability (i.e., an active gene-environment correlation) but phenotype does not explain willingness to try new stimuli.

A system for the model based emergency detection and communication for the telerehabilitation training of cardiopulmonary patients.

PubMed

Helmer, Axel; Kretschmer, Friedrich; Deparade, Riana; Song, Bianying; Meis, Markus; Hein, Andreas; Marschollek, Michael; Tegtbur, Uwe

2012-01-01

Cardiopulmonary diseases affect millions of people and cause high costs in health care systems worldwide. Patients should perform regular endurance exercises to stabilize their health state and prevent further impairment. However, patients are often uncertain about the level of intensity they should exercise in their current condition. The cost of continuous monitoring for these training sessions in clinics is high and additionally requires the patient to travel to a clinic for each single session. Performing the rehabilitation training at home can raise compliance and reduce costs. To ensure safe telerehabilitation training and to enable patients to control their performance and health state, detection of abnormal events during training is a critical prerequisite. Therefore, we created a model that predicts the heart rate of cardiopulmonary patients and that can be used to detect and avoid abnormal health states. To enable external feedback and an immediate reaction in case of a critical situation, the patient should have the possibility to configure the system to communicate warnings and emergency events to clinical and non-clinical actors. To fulfill this task, we coupled a personal health record (PHR) with a new component that extends the classic home emergency systems. The PHR is also used for a training schedule definition that makes use of the predictive HR model. We used statistical methods to evaluate the prediction model and found that our prediction error of 3.2 heart beats per minute is precise enough to enable a detection of critical states. The concept for the communication of alerts was evaluated through focus group interviews with domain experts who judged that it fulfills the needs of potential users.

Collaborations for Arctic Sea Ice Information and Tools

NASA Astrophysics Data System (ADS)

Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H.

2017-12-01

The dramatic and rapid changes in Arctic sea ice require collaboration across boundaries, including between disciplines, sectors, institutions, and between scientists and decision-makers. This poster will highlight several projects that provide knowledge to advance the development and use of sea ice knowledge. Sea Ice for Walrus Outlook (SIWO: https://www.arcus.org/search-program/siwo) - SIWO is a resource for Alaskan Native subsistence hunters and other interested stakeholders. SIWO provides weekly reports, during April-June, of sea ice conditions relevant to walrus in the northern Bering and southern Chukchi seas. Collaboration among scientists, Alaskan Native sea-ice experts, and the Eskimo Walrus Commission is fundamental to this project's success. Sea Ice Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions. The goals of SIPN include: coordinate and evaluate Arctic sea ice predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The Sea Ice Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic sea ice extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of Sea Ice Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of sea ice experts across institutions, countries, and sectors. The goal of the project is to catalyze networking between individual investigators, institutions, funding agencies, and other stakeholders interested in Arctic sea ice. Study of Environmental Arctic Change (SEARCH: https://www.arcus.org/search-program) - SEARCH is a collaborative program that advances research, synthesizes research findings, and broadly communicates the results to support informed decision-making. One of SEARCH's primary science topics is focused on Arctic sea ice; the SEARCH Sea Ice Action Team is leading efforts to advance understanding and awareness of the impacts of Arctic sea-ice loss.

A numerical field experiment approach for determining probabilities of microburst intensity

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin K.; Zweifel, Terry

1992-01-01

Several investigators had determined that some atmospheric parameters were related to the formation and severity of microbursts. For example, Caracena pointed out the relationship between a dry adiabatic lapse rate and microbursts in 'The crash of Delta Flight 191 at Dallas-Fort Worth international airport'. These early investigations led to the idea that numeric modeling of microbursts with varying atmospheric parameters might define 'signatures' that could lead to determining the probability of microburst intensity. The idea was that, by using already available sensors (such as static air temperature, pressure altitude, and radar reflectivity) onboard an aircraft, a reliable prediction of microburst existence and intensity could be formed. Such data could be used to create an 'expert meteorologist' using either artificial intelligence or other techniques that could be used in either reactive or look-ahead systems to vary sensitivity thresholds and coordinate the inputs from different detecting systems. To this end, Honeywell contracted to have the microburst simulations run. The questions to be addressed were the following: using the sensor set available to the aircraft (e.g. temperature, radar reflectivity, etc.), can we calculate the probability that (1) a microburst could be formed? and (2) that the resultant winds would be of sufficient magnitude to threaten the aircraft? Over a two year period, a data set of 1800 microburst simulations was accumulated. Verification of the microburst simulation was obtained using the results of other independent researchers and actual comparison to microburst events in Orlando and Denver. Some of the results from the simulation have already been incorporated into Honeywell's Windshear Detection and Guidance System with excellent results. Various aspects of this investigation are presented in viewgraph form.

Plus Disease in Retinopathy of Prematurity: A Continuous Spectrum of Vascular Abnormality as a Basis of Diagnostic Variability.

PubMed

Campbell, J Peter; Kalpathy-Cramer, Jayashree; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To identify patterns of interexpert discrepancy in plus disease diagnosis in retinopathy of prematurity (ROP). We developed 2 datasets of clinical images as part of the Imaging and Informatics in ROP study and determined a consensus reference standard diagnosis (RSD) for each image based on 3 independent image graders and the clinical examination results. We recruited 8 expert ROP clinicians to classify these images and compared the distribution of classifications between experts and the RSD. Eight participating experts with more than 10 years of clinical ROP experience and more than 5 peer-reviewed ROP publications who analyzed images obtained during routine ROP screening in neonatal intensive care units. Expert classification of images of plus disease in ROP. Interexpert agreement (weighted κ statistic) and agreement and bias on ordinal classification between experts (analysis of variance [ANOVA]) and the RSD (percent agreement). There was variable interexpert agreement on diagnostic classifications between the 8 experts and the RSD (weighted κ, 0-0.75; mean, 0.30). The RSD agreement ranged from 80% to 94% for the dataset of 100 images and from 29% to 79% for the dataset of 34 images. However, when images were ranked in order of disease severity (by average expert classification), the pattern of expert classification revealed a consistent systematic bias for each expert consistent with unique cut points for the diagnosis of plus disease and preplus disease. The 2-way ANOVA model suggested a highly significant effect of both image and user on the average score (dataset A: P < 0.05 and adjusted R 2  = 0.82; and dataset B: P < 0.05 and adjusted R 2  = 0.6615). There is wide variability in the classification of plus disease by ROP experts, which occurs because experts have different cut points for the amounts of vascular abnormality required for presence of plus and preplus disease. This has important implications for research, teaching, and patient care for ROP and suggests that a continuous ROP plus disease severity score may reflect more accurately the behavior of expert ROP clinicians and may better standardize classification in the future. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

DETERMINATION OF RELATIVE IMPORTANCE OF NONPROLIFERATION FACTORS

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

Richard Metcalf

2009-07-01

Methodologies to determine the proliferation resistance (PR) of nuclear facilities often rely on either expert elicitation, a resource-intensive approach without easily reproducible results, or numeric evaluations, which can fail to take into account the institutional knowledge and expert experience of the nonproliferation community. In an attempt to bridge the gap and bring the institutional knowledge into numeric evaluations of PR, a survey was conducted of 33 individuals to find the relative importance of a set of 62 nonproliferation factors, subsectioned into groups under the headings of Diversion, Transportation, Transformation, and Weaponization. One third of the respondents were self-described nonproliferation professionals,more » and the remaining two thirds were from secondary professions related to nonproliferation, such as industrial engineers or policy analysts. The factors were taken from previous work which used multi-attribute utility analysis with uniform weighting of attributes and did not include institutional knowledge. In both expert and non-expert groups, all four headings and the majority of factors had different relative importance at a confidence of 95% (p=0.05). This analysis and survey demonstrates that institutional knowledge can be brought into numeric evaluations of PR, if there is a sufficient investment of resources made prior to the evaluation.« less

Expert system for on-board satellite scheduling and control

NASA Technical Reports Server (NTRS)

Barry, John M.; Sary, Charisse

1988-01-01

An Expert System is described which Rockwell Satellite and Space Electronics Division (S&SED) is developing to dynamically schedule the allocation of on-board satellite resources and activities. This expert system is the Satellite Controller. The resources to be scheduled include power, propellant and recording tape. The activities controlled include scheduling satellite functions such as sensor checkout and operation. The scheduling of these resources and activities is presently a labor intensive and time consuming ground operations task. Developing a schedule requires extensive knowledge of the system and subsystems operations, operational constraints, and satellite design and configuration. This scheduling process requires highly trained experts anywhere from several hours to several weeks to accomplish. The process is done through brute force, that is examining cryptic mnemonic data off line to interpret the health and status of the satellite. Then schedules are formulated either as the result of practical operator experience or heuristics - that is rules of thumb. Orbital operations must become more productive in the future to reduce life cycle costs and decrease dependence on ground control. This reduction is required to increase autonomy and survivability of future systems. The design of future satellites require that the scheduling function be transferred from ground to on board systems.

Physical activity and training in sarcoidosis: review and experience-based recommendations.

PubMed

Strookappe, Bert; Saketkoo, Lesley Ann; Elfferich, Marjon; Holland, Anne; De Vries, Jolanda; Knevel, Ton; Drent, Marjolein

2016-10-01

Sarcoidosis is a multisystemic inflammatory disorder with a great variety of symptoms, including fatigue, dyspnea, pain, reduced exercise tolerance and muscle strength. Physical training has the potential to improve exercise capacity and muscle strength, and reduce fatigue. The aim of this review and survey was to present information about the role of physical training in sarcoidosis and offer practical guidelines. A systematic literature review guided an international consensus effort among sarcoidosis experts to establish practice-basic recommendations for the implementation of exercise as treatment for patients with various manifestations of sarcoidosis. International sarcoidosis experts suggested considering physical training in symptomatic patients with sarcoidosis. Expert commentary: There is promising evidence of a positive effect of physical training. Recommendations were based on available data and expert consensus. However, the heterogeneity of these patients will require modification and program adjustment of the standard rehabilitation format for e.g. COPD or interstitial lung diseases. An optimal training program (types of exercise, intensities, frequency, duration) still needs to be defined to optimize training adjustments, especially reduction of fatigue. Further randomized controlled trials are needed to consolidate these findings and optimize the comprehensive care of sarcoidosis patients.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1988-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 to + or - 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was developed to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Strengths of specimens containing crack-like slits were calculated from predicted failing strains using uniaxial stress-strain curves. Predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only + or - 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Diagnostic value of a pancreatic mass on computed tomography in patients undergoing pancreatoduodenectomy for presumed pancreatic cancer.

PubMed

Gerritsen, Arja; Bollen, Thomas L; Nio, C Yung; Molenaar, I Quintus; Dijkgraaf, Marcel G W; van Santvoort, Hjalmar C; Offerhaus, G Johan; Brosens, Lodewijk A; Biermann, Katharina; Sieders, Egbert; de Jong, Koert P; van Dam, Ronald M; van der Harst, Erwin; van Goor, Harry; van Ramshorst, Bert; Bonsing, Bert A; de Hingh, Ignace H; Gerhards, Michael F; van Eijck, Casper H; Gouma, Dirk J; Borel Rinkes, Inne H M; Busch, Olivier R C; Besselink, Marc G H

2015-07-01

Previous studies have shown that 5-14% of patients undergoing pancreatoduodenectomy for suspected malignancy ultimately are diagnosed with benign disease. A "pancreatic mass" on computed tomography (CT) is considered to be the strongest predictor of malignancy, but studies describing its diagnostic value are lacking. The aim of this study was to determine the diagnostic value of a pancreatic mass on CT in patients with presumed pancreatic cancer, as well as the interobserver agreement among radiologists and the additional value of reassessment by expert-radiologists. Reassessment of preoperative CT scans was performed within a previously described multicenter retrospective cohort study in 344 patients undergoing pancreatoduodenectomy for suspected malignancy (2003-2010). Preoperative CT scans were reassessed by 2 experienced abdominal radiologists separately and subsequently in a consensus meeting, after defining a pancreatic mass as "a measurable space occupying soft tissue density, except for an enlarged papilla or focal steatosis". CT scans of 86 patients with benign and 258 patients with (pre)malignant disease were reassessed. In 66% of patients a pancreatic mass was reported in the original CT report, versus 48% and 50% on reassessment by the 2 expert radiologists separately and 44% in consensus (P < .001 vs original report). Interobserver agreement between the original CT report and expert consensus was fair (kappa = 0.32, 95% confidence interval 0.23-0.42). Among both expert-radiologists agreement was moderate (kappa = 0.47, 95% confidence interval 0.38-0.56), with disagreement on the presence of a pancreatic mass in 29% of cases. The specificity for malignancy of pancreatic masses identified in expert consensus was twice as high compared with the original CT report (87% vs 42%, respectively). Positive predictive value increased to 98% after expert consensus, but negative predictive value was low (12%). Clinicians need to be aware of potential considerable disagreement among radiologists about the presence of a pancreatic mass. The specificity for malignancy doubled by expert radiologist reassessment when a uniform definition of "pancreatic mass" was used. Copyright © 2015 Elsevier Inc. All rights reserved.

Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series

PubMed Central

DeVries, Ben; Pratihast, Arun Kumar; Verbesselt, Jan; Kooistra, Lammert; Herold, Martin

2016-01-01

Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources. PMID:27018852

Crowd-sourced assessment of surgical skills in cricothyrotomy procedure.

PubMed

Aghdasi, Nava; Bly, Randall; White, Lee W; Hannaford, Blake; Moe, Kris; Lendvay, Thomas S

2015-06-15

Objective assessment of surgical skills is resource intensive and requires valuable time of expert surgeons. The goal of this study was to assess the ability of a large group of laypersons using a crowd-sourcing tool to grade a surgical procedure (cricothyrotomy) performed on a simulator. The grading included an assessment of the entire procedure by completing an objective assessment of technical skills survey. Two groups of graders were recruited as follows: (1) Amazon Mechanical Turk users and (2) three expert surgeons from University of Washington Department of Otolaryngology. Graders were presented with a video of participants performing the procedure on the simulator and were asked to grade the video using the objective assessment of technical skills questions. Mechanical Turk users were paid $0.50 for each completed survey. It took 10 h to obtain all responses from 30 Mechanical Turk users for 26 training participants (26 videos/tasks), whereas it took 60 d for three expert surgeons to complete the same 26 tasks. The assessment of surgical performance by a group (n = 30) of laypersons matched the assessment by a group (n = 3) of expert surgeons with a good level of agreement determined by Cronbach alpha coefficient = 0.83. We found crowd sourcing was an efficient, accurate, and inexpensive method for skills assessment with a good level of agreement to experts' grading. Copyright © 2015 Elsevier Inc. All rights reserved.

Predicting grief intensity after recent perinatal loss.

PubMed

Hutti, Marianne H; Myers, John; Hall, Lynne A; Polivka, Barbara J; White, Susan; Hill, Janice; Kloenne, Elizabeth; Hayden, Jaclyn; Grisanti, Meredith McGrew

2017-10-01

The Perinatal Grief Intensity Scale (PGIS) was developed for clinical use to identify and predict intense grief and need for follow-up after perinatal loss. This study evaluates the validity of the PGIS via its ability to predict future intense grief based on a PGIS score obtained early after a loss. A prospective observational study was conducted with 103 international, English-speaking women recruited at hospital discharge or via the internet who experienced a miscarriage, stillbirth, or neonatal death within the previous 8weeks. Survey data were collected at baseline using the PGIS and the Perinatal Grief Scale (PGS). Follow-up data on the PGS were obtained 3months later. Data analysis included descriptive statistics, Cronbach's alpha, receiver operating characteristic curve analysis, and confirmatory factor analysis. Cronbach's alphas were ≥0.70 for both instruments. PGIS factor analysis yielded three factors as predicted, explaining 57.7% of the variance. The optimal cutoff identified for the PGIS was 3.535. No difference was found when the ability of the PGIS to identify intense grief was compared to the PGS (p=0.754). The PGIS was not inferior to the PGS (AUC=0.78, 95% CI 0.68-0.88, p<0.001) in predicting intense grief at the follow-up. A PGIS score≥3.53 at baseline was associated with increased grief intensity at Time 2 (PGS: OR=1.97, 95% CI 1.59-2.34, p<0.001). The PGIS is comparable to the PGS, has a lower response burden, and can reliably and validly predict women who may experience future intense grief associated with perinatal loss. Copyright © 2017 Elsevier Inc. All rights reserved.

A biomechanical comparison between expert and novice manual materials handlers using a multi-joint EMG-assisted optimization musculoskeletal model of the lumbar spine.

PubMed

Gagnon, Denis; Plamondon, André; Larivière, Christian

2016-09-06

Expertise is a key factor modulating the risk of low back disorders (LBD). Through years of practice in the workplace, the typical expert acquires high level specific skills and maintains a clean record of work-related injuries. Ergonomic observations of manual materials handling (MMH) tasks show that expert techniques differ from those of novices, leading to the idea that expert techniques are safer. Biomechanical studies of MMH tasks performed by experts/novices report mixed results for kinematic/kinetic variables, evoking potential internal effect of expertise. In the context of series of box transfers simulated by actual workers, detailed internal loads predicted by a multiple-joint EMG-assisted optimization lumbar spine model are compared between experts and novices. The results confirmed that the distribution of internal moments are modulated by worker expertise. Experts flexed less their lumbar spine and exerted more active muscle forces while novices relied more on passive resistance of the muscles and ligamentous spine. More specifically for novices, the passive contributions came from global extensor muscles, selected local extensor muscles, and passive structures of the lumbar spine (ligaments and discs). The distinctive distribution of internal forces was not concomitant with a similar effect on joint forces, these forces being dependent on external loading which was equivalent between experts and novices. From a safety standpoint, the present results suggest that experts were more efficient than novices in partitioning internal moment contributions to balance net (external) loading. Thus, safer handling practices might be seen as a result of experts׳ experience. Copyright © 2016 Elsevier Ltd. All rights reserved.

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1990-01-01

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished.

exprso: an R-package for the rapid implementation of machine learning algorithms.

PubMed

Quinn, Thomas; Tylee, Daniel; Glatt, Stephen

2016-01-01

Machine learning plays a major role in many scientific investigations. However, non-expert programmers may struggle to implement the elaborate pipelines necessary to build highly accurate and generalizable models. We introduce exprso , a new R package that is an intuitive machine learning suite designed specifically for non-expert programmers. Built initially for the classification of high-dimensional data, exprso uses an object-oriented framework to encapsulate a number of common analytical methods into a series of interchangeable modules. This includes modules for feature selection, classification, high-throughput parameter grid-searching, elaborate cross-validation schemes (e.g., Monte Carlo and nested cross-validation), ensemble classification, and prediction. In addition, exprso also supports multi-class classification (through the 1-vs-all generalization of binary classifiers) and the prediction of continuous outcomes.

Preliminary development of POEAW in enhancing K-11 students’ understanding level on impulse and momentum

NASA Astrophysics Data System (ADS)

Luthfiani, T. A.; Sinaga, P.; Samsudin, A.

2018-05-01

We have been analyzed that there were limited research about Predict-Observe- Explain which use writing process with conceptual change text strategy. This study aims to develop a learning model namely Predict-Observe-Explain-Apply-Writing (POEAW) which is able to enhance students’ understanding level. The research method utilized the 4D model (Defining, Designing, Developing and Disseminating) that is formally limited to Developing Stage. There are four experts who judge the learning component (syntax, lesson plan, teaching material and student worksheet) and matter component (learning quality and content component). The result of this study are obtained expert validity test score average of 87% for learning content and 89% for matter component that means the POEAW is valid and can be tested in classroom learning. This research producing POEAW learning model that has five main steps, Predict, Observe, Explain, Apply and Write. To sum up, we have early developed POEAW in enhancing K-11 students’ understanding levels on impulse and momentum.

Explosion probability of unexploded ordnance: expert beliefs.

PubMed

MacDonald, Jacqueline Anne; Small, Mitchell J; Morgan, M G

2008-08-01

This article reports on a study to quantify expert beliefs about the explosion probability of unexploded ordnance (UXO). Some 1,976 sites at closed military bases in the United States are contaminated with UXO and are slated for cleanup, at an estimated cost of $15-140 billion. Because no available technology can guarantee 100% removal of UXO, information about explosion probability is needed to assess the residual risks of civilian reuse of closed military bases and to make decisions about how much to invest in cleanup. This study elicited probability distributions for the chance of UXO explosion from 25 experts in explosive ordnance disposal, all of whom have had field experience in UXO identification and deactivation. The study considered six different scenarios: three different types of UXO handled in two different ways (one involving children and the other involving construction workers). We also asked the experts to rank by sensitivity to explosion 20 different kinds of UXO found at a case study site at Fort Ord, California. We found that the experts do not agree about the probability of UXO explosion, with significant differences among experts in their mean estimates of explosion probabilities and in the amount of uncertainty that they express in their estimates. In three of the six scenarios, the divergence was so great that the average of all the expert probability distributions was statistically indistinguishable from a uniform (0, 1) distribution-suggesting that the sum of expert opinion provides no information at all about the explosion risk. The experts' opinions on the relative sensitivity to explosion of the 20 UXO items also diverged. The average correlation between rankings of any pair of experts was 0.41, which, statistically, is barely significant (p= 0.049) at the 95% confidence level. Thus, one expert's rankings provide little predictive information about another's rankings. The lack of consensus among experts suggests that empirical studies are needed to better understand the explosion risks of UXO.

[Study on expert system of infrared spectral characteristic of combustible smoke agent].

PubMed

Song, Dong-ming; Guan, Hua; Hou, Wei; Pan, Gong-pei

2009-05-01

The present paper studied the application of expert system in prediction of infrared spectral characteristic of combustible anti-infrared smoke agent. The construction of the expert system was founded, based on the theory of minimum free energy and infrared spectral addition. After the direction of smoke agent was input, the expert system could figure out the final combustion products. Then infrared spectrogram of smoke could also be simulated by adding the spectra of all of the combustion products. Meanwhile, the screening index of smoke was provided in the wave bands of 3-5 im and 8-14 microm. FTIR spectroscope was used to investigate the performance of one kind of HC smoke. The combustion products calculated by the expert system were coincident with the actual data, and the simulant infrared spectrum was also similar to the real one of the smoke. The screening index given by the system was consistent with the known facts. It was showed that a new approach was offered for the fast discrimination of varieties of directions of smoke agent.

BAYESIAN META-ANALYSIS ON MEDICAL DEVICES: APPLICATION TO IMPLANTABLE CARDIOVERTER DEFIBRILLATORS

PubMed Central

Youn, Ji-Hee; Lord, Joanne; Hemming, Karla; Girling, Alan; Buxton, Martin

2012-01-01

Objectives: The aim of this study is to describe and illustrate a method to obtain early estimates of the effectiveness of a new version of a medical device. Methods: In the absence of empirical data, expert opinion may be elicited on the expected difference between the conventional and modified devices. Bayesian Mixed Treatment Comparison (MTC) meta-analysis can then be used to combine this expert opinion with existing trial data on earlier versions of the device. We illustrate this approach for a new four-pole implantable cardioverter defibrillator (ICD) compared with conventional ICDs, Class III anti-arrhythmic drugs, and conventional drug therapy for the prevention of sudden cardiac death in high risk patients. Existing RCTs were identified from a published systematic review, and we elicited opinion on the difference between four-pole and conventional ICDs from experts recruited at a cardiology conference. Results: Twelve randomized controlled trials were identified. Seven experts provided valid probability distributions for the new ICDs compared with current devices. The MTC model resulted in estimated relative risks of mortality of 0.74 (0.60–0.89) (predictive relative risk [RR] = 0.77 [0.41–1.26]) and 0.83 (0.70–0.97) (predictive RR = 0.84 [0.55–1.22]) with the new ICD therapy compared to Class III anti-arrhythmic drug therapy and conventional drug therapy, respectively. These results showed negligible differences from the preliminary results for the existing ICDs. Conclusions: The proposed method incorporating expert opinion to adjust for a modification made to an existing device may play a useful role in assisting decision makers to make early informed judgments on the effectiveness of frequently modified healthcare technologies. PMID:22559753

Evaluation and Applications of the Prediction of Intensity Model Error (PRIME) Model

NASA Astrophysics Data System (ADS)

Bhatia, K. T.; Nolan, D. S.; Demaria, M.; Schumacher, A.

2015-12-01

Forecasters and end users of tropical cyclone (TC) intensity forecasts would greatly benefit from a reliable expectation of model error to counteract the lack of consistency in TC intensity forecast performance. As a first step towards producing error predictions to accompany each TC intensity forecast, Bhatia and Nolan (2013) studied the relationship between synoptic parameters, TC attributes, and forecast errors. In this study, we build on previous results of Bhatia and Nolan (2013) by testing the ability of the Prediction of Intensity Model Error (PRIME) model to forecast the absolute error and bias of four leading intensity models available for guidance in the Atlantic basin. PRIME forecasts are independently evaluated at each 12-hour interval from 12 to 120 hours during the 2007-2014 Atlantic hurricane seasons. The absolute error and bias predictions of PRIME are compared to their respective climatologies to determine their skill. In addition to these results, we will present the performance of the operational version of PRIME run during the 2015 hurricane season. PRIME verification results show that it can reliably anticipate situations where particular models excel, and therefore could lead to a more informed protocol for hurricane evacuations and storm preparations. These positive conclusions suggest that PRIME forecasts also have the potential to lower the error in the original intensity forecasts of each model. As a result, two techniques are proposed to develop a post-processing procedure for a multimodel ensemble based on PRIME. The first approach is to inverse-weight models using PRIME absolute error predictions (higher predicted absolute error corresponds to lower weights). The second multimodel ensemble applies PRIME bias predictions to each model's intensity forecast and the mean of the corrected models is evaluated. The forecasts of both of these experimental ensembles are compared to those of the equal-weight ICON ensemble, which currently provides the most reliable forecasts in the Atlantic basin.

A Theory-Based Methodology for Analyzing Domain Suitability for Expert Systems Technology Applications

DTIC Science & Technology

1989-06-01

amount of data now available as a result of these experiments, we are still unable to explain the "why" or " how " of successful systems or to predict for...order to better understand the potential contribution of this research, it is important to first discuss how expert systems are developed and the...task performance through internal and external feedback. 9. Knowing how to act upon the feedback received. 10. Implementing the action based on the

The role of parental perceptions of tic frequency and intensity in predicting tic-related functional impairment in youth with chronic tic disorders.

PubMed

Espil, Flint M; Capriotti, Matthew R; Conelea, Christine A; Woods, Douglas W

2014-12-01

Tic severity is composed of several dimensions. Tic frequency and intensity are two such dimensions, but little empirical data exist regarding their relative contributions to functional impairment in those with chronic tic disorders (CTD). The present study examined the relative contributions of these dimensions in predicting tic-related impairment across several psychosocial domains. Using data collected from parents of youth with CTD, multivariate regression analyses revealed that both tic frequency and intensity predicted tic-related impairment in several areas; including family and peer relationships, school interference, and social endeavors, even when controlling for the presence of comorbid anxiety symptoms and Attention Deficit Hyperactivity Disorder diagnostic status. Results showed that tic intensity predicted more variance across more domains than tic frequency.

A Quantitative Model of Expert Transcription Typing

DTIC Science & Technology

1993-03-08

side of pure psychology, several researchers have argued that transcription typing is a particularly good activity for the study of human skilled...phenomenon with a quantitative METT prediction. The first, quick and dirty analysis gives a good prediction of the copy span, in fact, it is even...typing, it should be demonstrated that the mechanism of the model does not get in the way of good predictions. If situations occur where the entire

Intuition and Professional Competence: Intuitive Versus Rational Forecasting of the Stock Market

ERIC Educational Resources Information Center

Harteis, Christian; Gruber, Hans

2008-01-01

This article argues that intuition is a crucial component of professional competence, and provides empirical evidence to support this claim. It was found that in most cases intuitive predictions of stock market development are better than rationally justified ones and that experts predict more precisely than novices on a descriptive data level.…

[Pitfalls in 'orthodox knowledge'].

PubMed

Taneda, Hiroyuki

2003-03-01

Within contemporary society both 'pseudoscience' and 'pseudomedicine' can be found. Such knowledge is seen as incorrect, wrong or irrational. I call them 'unorthodox (uncertain) knowledge'. Conversely, 'orthodox knowledge'--for example, science, medicine, etc.--is seen as correct, right or rational. Some people believe 'unorthodox (uncertain) knowledge'. Experts castigate such people from the standpoint that they lack the basic understanding of 'orthodox knowledge'. That is, experts see the ordinary lay person as subjective, ignorant or irrational (whereas they see themselves as objective, analytical, prudent or rational). But are people ignorant or irrational? The aim of this paper is to examine this question in terms of analyzing the interplay among the characteristics of 'orthodox knowledge', 'unorthodox (uncertain) knowledge' and the nature of people's concerns. Thus, this paper explains that people develop certain situated understandings of 'orthodox knowledge' and/or 'unorthodox (uncertain) knowledge' through their intensive experiences. Also, this paper suggests that people need to rethink or reflect on the good institutions which mediate between people and experts.

Prescribed Fire And Smoke Management In The South: Conference Proceedings

Treesearch

Dale D. Wade; [Compiler

1984-01-01

The deliberate application of fire to produce desired wildland benefits has evolved through the centuries into the art of prescription burning. Southern resource managers became expert at applying this art and practiced it for decades with few operational constraints. However, as the available land base shrank and management became more intensive, the value of these...

A Set of Patterns for the Structured Design of MOOCs

ERIC Educational Resources Information Center

Warburton, Steven; Mor, Yishay

2015-01-01

A design pattern approach, in the form of participatory pattern workshops, has been used to explore the design approaches that experts in the field of online learning have used to develop and deliver Massive Open Online Courses (MOOCs). Over the course of 3 intensive workshops a total of 20 design patterns were developed from shared narratives of…

After Early Intervention, Then What? Teaching Struggling Readers in Grades 3 and Beyond.

ERIC Educational Resources Information Center

McCormack, Rachel L., Ed.; Paratore, Jeanne R., Ed.

Noting that early intervention is insufficient for many children because they struggle in learning to read for an array of reasons, this book highlights the need for expert, intensive, and focused instruction in reading beyond the primary years in addition to identifying and describing effective practices for teaching those students in grades 3 to…

Using Hierarchical Cluster Models to Systematically Identify Groups of Jobs With Similar Occupational Questionnaire Response Patterns to Assist Rule-Based Expert Exposure Assessment in Population-Based Studies

PubMed Central

Friesen, Melissa C.; Shortreed, Susan M.; Wheeler, David C.; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S.; Baris, Dalsu; Karagas, Margaret R.; Schwenn, Molly; Johnson, Alison; Armenti, Karla R.; Silverman, Debra T.; Yu, Kai

2015-01-01

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m−3 respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters’ homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job’s estimate and the mean estimate for all jobs within the cluster. Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. PMID:25477475

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

PubMed

Friesen, Melissa C; Shortreed, Susan M; Wheeler, David C; Burstyn, Igor; Vermeulen, Roel; Pronk, Anjoeka; Colt, Joanne S; Baris, Dalsu; Karagas, Margaret R; Schwenn, Molly; Johnson, Alison; Armenti, Karla R; Silverman, Debra T; Yu, Kai

2015-05-01

Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.

[Progressive noise induced hearing loss caused by hearing AIDS, a dilemma for the worker and the expert alike].

PubMed

Feldmann, H

2001-12-01

Investigating cases of noise induced hearing loss the expert is often confronted with the situation that the hearing loss is progressive although the noise exposure has been reduced to almost non-damaging levels. Other causes such as age, hereditary deafness, head injuries, blasts, internal diseases can be excluded. Hearing aids as sources of damaging noise? By consulting the protocol of the hearing-aid acoustician and by own examinations the expert should obtain the following data: loudness level that yields best discrimination score of speech; level of discomfort for tones and speech, discrimination score that is achieved under free field condition with a speech level of 65 dB, using the hearing aids. Furthermore he should explore the circumstances under which the hearing aids are used: how many hours per day, at what occasions etc.? It is likely that in using the hearing aids they are adjusted to emit an intensity level identical to the one yielding the optimal discrimination score. If this e. g. is 100 dB and the hearing aids are used for 2 hours per day this would be equivalent to an exposure to industrial noise of 94 dB (A) for 8 hours daily without ear protection. Among all individuals working under industrial noise exposure today only about 1 - 2 % having unusually vulnerable inner ears will suffer a noise induced hearing loss. On the other hand workers in industrial noise are accustomed to loud noise levels, usually have a raised threshold of discomfort and therefore are likely to adjust their hearing aids to such high intensities. The expert will have to decide whether in an individual case the industrial noise exposure or the use of the hearing aids is the dominant risk for further damage. The consequences in respect to the regulations of the workers' health insurance are discussed.

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.

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

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

Rizzo, Davinia B.; Blackburn, Mark R.

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Harnessing expert knowledge: Defining a Bayesian network decision model with limited data-Model structure for the vibration qualification problem

DOE PAGES

Rizzo, Davinia B.; Blackburn, Mark R.

2018-03-30

As systems become more complex, systems engineers rely on experts to inform decisions. There are few experts and limited data in many complex new technologies. This challenges systems engineers as they strive to plan activities such as qualification in an environment where technical constraints are coupled with the traditional cost, risk, and schedule constraints. Bayesian network (BN) models provide a framework to aid systems engineers in planning qualification efforts with complex constraints by harnessing expert knowledge and incorporating technical factors. By quantifying causal factors, a BN model can provide data about the risk of implementing a decision supplemented with informationmore » on driving factors. This allows a systems engineer to make informed decisions and examine “what-if” scenarios. This paper discusses a novel process developed to define a BN model structure based primarily on expert knowledge supplemented with extremely limited data (25 data sets or less). The model was developed to aid qualification decisions—specifically to predict the suitability of six degrees of freedom (6DOF) vibration testing for qualification. The process defined the model structure with expert knowledge in an unbiased manner. Finally, validation during the process execution and of the model provided evidence the process may be an effective tool in harnessing expert knowledge for a BN model.« less

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Expert Game experiment predicts emergence of trust in professional communication networks.

PubMed

Bendtsen, Kristian Moss; Uekermann, Florian; Haerter, Jan O

2016-10-25

Strong social capital is increasingly recognized as an organizational advantage. Better knowledge sharing and reduced transaction costs increase work efficiency. To mimic the formation of the associated communication network, we propose the Expert Game, where each individual must find a specific expert and receive her help. Participants act in an impersonal environment and under time constraints that provide short-term incentives for noncooperative behavior. Despite these constraints, we observe cooperation between individuals and the self-organization of a sustained trust network, which facilitates efficient communication channels with increased information flow. We build a behavioral model that explains the experimental dynamics. Analysis of the model reveals an exploitation protection mechanism and measurable social capital, which quantitatively describe the economic utility of trust.

Bayesian methods in reliability

NASA Astrophysics Data System (ADS)

Sander, P.; Badoux, R.

1991-11-01

The present proceedings from a course on Bayesian methods in reliability encompasses Bayesian statistical methods and their computational implementation, models for analyzing censored data from nonrepairable systems, the traits of repairable systems and growth models, the use of expert judgment, and a review of the problem of forecasting software reliability. Specific issues addressed include the use of Bayesian methods to estimate the leak rate of a gas pipeline, approximate analyses under great prior uncertainty, reliability estimation techniques, and a nonhomogeneous Poisson process. Also addressed are the calibration sets and seed variables of expert judgment systems for risk assessment, experimental illustrations of the use of expert judgment for reliability testing, and analyses of the predictive quality of software-reliability growth models such as the Weibull order statistics.

Sports betting: can gamblers beat randomness?

PubMed

Cantinotti, Michael; Ladouceur, Robert; Jacques, Christian

2004-06-01

Although skills are not considered relevant in chance-governed activities, only a few studies have assessed the extent to which sport expert skills in wagering are a manifestation of the illusion of control. This study examined (a) whether expert hockey bettors could make better predictions than chance, (b) whether expert hockey bettors could achieve greater monetary gains than chance, and (c) what kind of strategies hockey gamblers rely on when betting. Accordingly, 30 participants were asked to report their state lottery hockey bets on 6 occasions. We suggest that the information used by bettors, along with near-misses, reinforces their perception of expertise. The results of this experiment suggest that the so-called "skills" of the sports bettors are cognitive distortions. (c) 2004 APA, all rights reserved

Phenobarbital in intensive care unit pediatric population: predictive performances of population pharmacokinetic model.

PubMed

Marsot, Amélie; Michel, Fabrice; Chasseloup, Estelle; Paut, Olivier; Guilhaumou, Romain; Blin, Olivier

2017-10-01

An external evaluation of phenobarbital population pharmacokinetic model described by Marsot et al. was performed in pediatric intensive care unit. Model evaluation is an important issue for dose adjustment. This external evaluation should allow confirming the proposed dosage adaptation and extending these recommendations to the entire intensive care pediatric population. External evaluation of phenobarbital published population pharmacokinetic model of Marsot et al. was realized in a new retrospective dataset of 35 patients hospitalized in a pediatric intensive care unit. The published population pharmacokinetic model was implemented in nonmem 7.3. Predictive performance was assessed by quantifying bias and inaccuracy of model prediction. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were also evaluated. A total of 35 infants were studied with a mean age of 33.5 weeks (range: 12 days-16 years) and a mean weight of 12.6 kg (range: 2.7-70.0 kg). The model predicted the observed phenobarbital concentrations with a reasonable bias and inaccuracy. The median prediction error was 3.03% (95% CI: -8.52 to 58.12%), and the median absolute prediction error was 26.20% (95% CI: 13.07-75.59%). No trends in NPDE and VPC were observed. The model previously proposed by Marsot et al. in neonates hospitalized in intensive care unit was externally validated for IV infusion administration. The model-based dosing regimen was extended in all pediatric intensive care unit to optimize treatment. Due to inter- and intravariability in pharmacokinetic model, this dosing regimen should be combined with therapeutic drug monitoring. © 2017 Société Française de Pharmacologie et de Thérapeutique.

Predicting long-term outcomes for children affected by HIV and AIDS: perspectives from the scientific study of children's development.

PubMed

Stein, Alan; Desmond, Christopher; Garbarino, James; Van IJzendoorn, Marinus H; Barbarin, Oscar; Black, Maureen M; Stein, Aryeh D; Hillis, Susan D; Kalichman, Seth C; Mercy, James A; Bakermans-Kranenburg, Marian J; Rapa, Elizabeth; Saul, Janet R; Dobrova-Krol, Natasha A; Richter, Linda M

2014-07-01

The immediate and short-term consequences of adult HIV for affected children are well documented. Little research has examined the long-term implications of childhood adversity stemming from caregiver HIV infection. Through overviews provided by experts in the field, together with an iterative process of consultation and refinement, we have extracted insights from the broader field of child development of relevance to predicting the long-term consequences to children affected by HIV and AIDS. We focus on what is known about the impact of adversities similar to those experienced by HIV-affected children, and for which there is longitudinal evidence. Cautioning that findings are not directly transferable across children or contexts, we examine findings from the study of parental death, divorce, poor parental mental health, institutionalization, undernutrition, and exposure to violence. Regardless of the type of adversity, the majority of children manifest resilience and do not experience any long-term negative consequences. However, a significant minority do and these children experience not one, but multiple problems, which frequently endure over time in the absence of support and opportunities for recovery. As a result, they are highly likely to suffer numerous and enduring impacts. These insights suggest a new strategic approach to interventions for children affected by HIV and AIDS, one that effectively combines a universal lattice of protection with intensive intervention targeted to selected children and families.

Adaptive maritime video surveillance

NASA Astrophysics Data System (ADS)

Gupta, Kalyan Moy; Aha, David W.; Hartley, Ralph; Moore, Philip G.

2009-05-01

Maritime assets such as ports, harbors, and vessels are vulnerable to a variety of near-shore threats such as small-boat attacks. Currently, such vulnerabilities are addressed predominantly by watchstanders and manual video surveillance, which is manpower intensive. Automatic maritime video surveillance techniques are being introduced to reduce manpower costs, but they have limited functionality and performance. For example, they only detect simple events such as perimeter breaches and cannot predict emerging threats. They also generate too many false alerts and cannot explain their reasoning. To overcome these limitations, we are developing the Maritime Activity Analysis Workbench (MAAW), which will be a mixed-initiative real-time maritime video surveillance tool that uses an integrated supervised machine learning approach to label independent and coordinated maritime activities. It uses the same information to predict anomalous behavior and explain its reasoning; this is an important capability for watchstander training and for collecting performance feedback. In this paper, we describe MAAW's functional architecture, which includes the following pipeline of components: (1) a video acquisition and preprocessing component that detects and tracks vessels in video images, (2) a vessel categorization and activity labeling component that uses standard and relational supervised machine learning methods to label maritime activities, and (3) an ontology-guided vessel and maritime activity annotator to enable subject matter experts (e.g., watchstanders) to provide feedback and supervision to the system. We report our findings from a preliminary system evaluation on river traffic video.

Crowd-sourced data collection to support automatic classification of building footprint data

NASA Astrophysics Data System (ADS)

Hecht, Robert; Kalla, Matthias; Krüger, Tobias

2018-05-01

Human settlements are mainly formed by buildings with their different characteristics and usage. Despite the importance of buildings for the economy and society, complete regional or even national figures of the entire building stock and its spatial distribution are still hardly available. Available digital topographic data sets created by National Mapping Agencies or mapped voluntarily through a crowd via Volunteered Geographic Information (VGI) platforms (e.g. OpenStreetMap) contain building footprint information but often lack additional information on building type, usage, age or number of floors. For this reason, predictive modeling is becoming increasingly important in this context. The capabilities of machine learning allow for the prediction of building types and other building characteristics and thus, the efficient classification and description of the entire building stock of cities and regions. However, such data-driven approaches always require a sufficient amount of ground truth (reference) information for training and validation. The collection of reference data is usually cost-intensive and time-consuming. Experiences from other disciplines have shown that crowdsourcing offers the possibility to support the process of obtaining ground truth data. Therefore, this paper presents the results of an experimental study aiming at assessing the accuracy of non-expert annotations on street view images collected from an internet crowd. The findings provide the basis for a future integration of a crowdsourcing component into the process of land use mapping, particularly the automatic building classification.

Post-training Beliefs, Intentions, and Use of Prolonged Exposure Therapy by Clinicians in the Veterans Health Administration.

PubMed

Ruzek, J I; Eftekhari, A; Crowley, J; Kuhn, E; Karlin, B E; Rosen, C S

2017-01-01

To examine how changes in beliefs during the training process predict adoption of prolonged exposure therapy (PE) by veterans health administration clinicians who received intensive training in this evidence-based treatment. Participants completed a 4-day PE workshop and received expert consultation as they used PE with two or more training cases. Participants were surveyed prior to the workshop, after the workshop, after case consultation (n = 1.034), and 6 months after training (n = 810). Hierarchical regression was used to assess how pre-training factors, and changes in beliefs during different stages of training incrementally predicted post-training intent to use PE and how many patients clinicians were treating with PE 6 months after training. Post-training intent to use PE was high (mean = 6.2, SD = 0.81 on a 1-7 scale), yet most participants treated only 1 or 2 patients at a time with PE. Pre-training factors predicted intent to use and actual use of PE. Changes in beliefs during the workshop had statistically significant yet modest effects on intent and use of PE. Changes in beliefs during case consultation had substantial effects on intent and actual use of PE. Pre-training factors and changes in beliefs during training (especially during case consultation) influence clinicians' adoption of PE. Use of PE was influenced not only by its perceived clinical advantages/disadvantages, but also by contextual factors (working in a PTSD specialty clinic, perceived control over one's schedule, and ability to promote PE to patients and colleagues).

Biology-inspired Microphysiological System Approaches to Solve the Prediction Dilemma of Substance Testing

PubMed Central

Marx, Uwe; Andersson, Tommy B.; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R.; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B.; Hoeng, Julia; de Jong, Wim H.; Kojima, Hajime; Kuehnl, Jochen; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J. A. M.; Steger-Hartmann, Thomas; Tagle, Danilo A.; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian

2017-01-01

Summary The recent advent of microphysiological systems – microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro – is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-five experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale. PMID:27180100

The immunotherapy of Guillain-Barré syndrome.

PubMed

Restrepo-Jiménez, Paula; Rodríguez, Yhojan; González, Paulina; Chang, Christopher; Gershwin, M Eric; Anaya, Juan-Manuel

2018-05-08

Guillain-Barré syndrome is the most common cause of acute flaccid paralysis worldwide. Microorganisms such as Campylobacter jejuni, Cytomegalovirus, Epstein-Barr virus, Mycoplasma pneumoniae, Haemophilus influenzae and Zika virus have been linked to the disease. The most common clinical variants are acute inflammatory demyelinating polyneuropathy and acute motor axonal neuropathy. Plasma exchange and intravenous immunoglobulins are the standard therapy for the disease. Areas covered: research to elucidate the pathophysiology of Guillain-Barré syndrome has led to the development of drugs directed towards new potential therapeutic targets. This review offers a comprehensive view of the current treatment based upon the physiopathology. Expert opinion: patients with Guillain-Barré syndrome need a multidisciplinary approach, limitation to walk unaided and disability score are indicators for treatment as well as the presence of autonomic dysfunction and pain. Admission to intensive care units should be considered for those patients presenting with respiratory failure, bulbar involvement and progression of the disease. Research aimed to deciphering the pathophysiology of the disease, discovering new biomarkers and establishing algorithms of prediction of both the disease and its outcomes is warranted.

MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation.

PubMed

Degroeve, Sven; Maddelein, Davy; Martens, Lennart

2015-07-01

We present an MS(2) peak intensity prediction server that computes MS(2) charge 2+ and 3+ spectra from peptide sequences for the most common fragment ions. The server integrates the Unimod public domain post-translational modification database for modified peptides. The prediction model is an improvement of the previously published MS(2)PIP model for Orbitrap-LTQ CID spectra. Predicted MS(2) spectra can be downloaded as a spectrum file and can be visualized in the browser for comparisons with observations. In addition, we added prediction models for HCD fragmentation (Q-Exactive Orbitrap) and show that these models compute accurate intensity predictions on par with CID performance. We also show that training prediction models for CID and HCD separately improves the accuracy for each fragmentation method. The MS(2)PIP prediction server is accessible from http://iomics.ugent.be/ms2pip. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Stable Atlas-based Mapped Prior (STAMP) machine-learning segmentation for multicenter large-scale MRI data.

PubMed

Kim, Eun Young; Magnotta, Vincent A; Liu, Dawei; Johnson, Hans J

2014-09-01

Machine learning (ML)-based segmentation methods are a common technique in the medical image processing field. In spite of numerous research groups that have investigated ML-based segmentation frameworks, there remains unanswered aspects of performance variability for the choice of two key components: ML algorithm and intensity normalization. This investigation reveals that the choice of those elements plays a major part in determining segmentation accuracy and generalizability. The approach we have used in this study aims to evaluate relative benefits of the two elements within a subcortical MRI segmentation framework. Experiments were conducted to contrast eight machine-learning algorithm configurations and 11 normalization strategies for our brain MR segmentation framework. For the intensity normalization, a Stable Atlas-based Mapped Prior (STAMP) was utilized to take better account of contrast along boundaries of structures. Comparing eight machine learning algorithms on down-sampled segmentation MR data, it was obvious that a significant improvement was obtained using ensemble-based ML algorithms (i.e., random forest) or ANN algorithms. Further investigation between these two algorithms also revealed that the random forest results provided exceptionally good agreement with manual delineations by experts. Additional experiments showed that the effect of STAMP-based intensity normalization also improved the robustness of segmentation for multicenter data sets. The constructed framework obtained good multicenter reliability and was successfully applied on a large multicenter MR data set (n>3000). Less than 10% of automated segmentations were recommended for minimal expert intervention. These results demonstrate the feasibility of using the ML-based segmentation tools for processing large amount of multicenter MR images. We demonstrated dramatically different result profiles in segmentation accuracy according to the choice of ML algorithm and intensity normalization chosen. Copyright © 2014 Elsevier Inc. All rights reserved.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity

PubMed Central

Brousset, Jean Marie; Abbal, Philippe; Guillemin, Hervé; Perret, Bruno; Goulet, Etienne; Guerin, Laurence; Barbeau, Gérard; Picque, Daniel

2015-01-01

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system. PMID:26230334

The Role of Parental Perceptions of Tic Frequency and Intensity in Predicting Tic-Related Functional Impairment in Youth with Chronic Tic Disorders

PubMed Central

Espil, Flint M.; Capriotti, Matthew R.; Conelea, Christine A.; Woods, Douglas W.

2014-01-01

Tic severity is composed of several dimensions. Tic frequency and intensity are two such dimensions, but little empirical data exist regarding their relative contributions to functional impairment in those with Chronic Tic Disorders (CTD). The present study examined the relative contributions of these dimensions in predicting tic-related impairment across several psychosocial domains. Using data collected from parents of youth with CTD, multivariate regression analyses revealed that both tic frequency and intensity predicted tic-related impairment in several areas; including family and peer relationships, school interference, and social endeavors, even when controlling for the presence of comorbid anxiety symptoms and Attention Deficit Hyperactivity Disorder diagnostic status. Results showed that tic intensity predicted more variance across more domains than tic frequency. PMID:24395287

[Outlier cases in surgical disciplines. Micro-economic and macro-economic problems].

PubMed

Tecklenburg, A; Liebeneiner, J; Schaefer, O

2009-09-01

Postoperative complications will always occur and the negative impact puts strain on patients, relatives and the attending physicians. The conversion to a remuneration system based on flat rates (diagnosis-related groups) presents additional economic problems for hospitals in some resource-intensive treatments. This particularly pertains to extremely cost-intensive cases in which costs succeed revenue by the factor of 2 and are often surgical procedures. Here the economic risk increases with the number of interventions performed. Despite improvements in the remuneration system this problem persists. An improved payment for these treatments is desirable. To achieve this it is necessary to systematically analyze the extremely cost-intensive cases by experts of different medical disciplines to create a data basis for a proposal of a cost-covering payment.

Process consistency in models: The importance of system signatures, expert knowledge, and process complexity

NASA Astrophysics Data System (ADS)

Hrachowitz, M.; Fovet, O.; Ruiz, L.; Euser, T.; Gharari, S.; Nijzink, R.; Freer, J.; Savenije, H. H. G.; Gascuel-Odoux, C.

2014-09-01

Hydrological models frequently suffer from limited predictive power despite adequate calibration performances. This can indicate insufficient representations of the underlying processes. Thus, ways are sought to increase model consistency while satisfying the contrasting priorities of increased model complexity and limited equifinality. In this study, the value of a systematic use of hydrological signatures and expert knowledge for increasing model consistency was tested. It was found that a simple conceptual model, constrained by four calibration objective functions, was able to adequately reproduce the hydrograph in the calibration period. The model, however, could not reproduce a suite of hydrological signatures, indicating a lack of model consistency. Subsequently, testing 11 models, model complexity was increased in a stepwise way and counter-balanced by "prior constraints," inferred from expert knowledge to ensure a model which behaves well with respect to the modeler's perception of the system. We showed that, in spite of unchanged calibration performance, the most complex model setup exhibited increased performance in the independent test period and skill to better reproduce all tested signatures, indicating a better system representation. The results suggest that a model may be inadequate despite good performance with respect to multiple calibration objectives and that increasing model complexity, if counter-balanced by prior constraints, can significantly increase predictive performance of a model and its skill to reproduce hydrological signatures. The results strongly illustrate the need to balance automated model calibration with a more expert-knowledge-driven strategy of constraining models.

Computer-Aided Decision Making.

DTIC Science & Technology

1988-04-01

Center at Gunter APS, Alabama, 1% predicts that 150.000 more microcomputers, with integrated software, will be VP aided !,: the A:r Fcrce inventory...a computer’s power when he said, ’it is also useful to anticipate or predict changes in the data Pondering ’what if’ situations enabled me to answer... predict future b) experts forecast In Isolation, then consensus is found C. Group decision making (3t30-34) Slide i-i 1. Advantages a. broader background 1

Pain assessment tools: is the content appropriate for use in palliative care?

PubMed

Hølen, Jacob Chr; Hjermstad, Marianne Jensen; Loge, Jon Håvard; Fayers, Peter M; Caraceni, Augusto; De Conno, Franco; Forbes, Karen; Fürst, Carl Johan; Radbruch, Lukas; Kaasa, Stein

2006-12-01

Inadequate pain assessment prevents optimal treatment in palliative care. The content of pain assessment tools might limit their usefulness for proper pain assessment, but data on the content validity of the tools are scarce. The objective of this study was to examine the content of the existing pain assessment tools, and to evaluate the appropriateness of different dimensions and items for pain assessment in palliative care. A systematic search was performed to find pain assessment tools for patients with advanced cancer who were receiving palliative care. An ad hoc search with broader search criteria supplemented the systematic search. The items of the identified tools were allocated to appropriate dimensions. This was reviewed by an international panel of experts, who also evaluated the relevance of the different dimensions for pain assessment in palliative care. The systematic literature search generated 16 assessment tools while the ad hoc search generated 64. Ten pain dimensions containing 1,011 pain items were identified by the experts. The experts ranked intensity, temporal pattern, treatment and exacerbating/relieving factors, location, and interference with health-related quality of life as the most important dimensions. None of the assessment tools covered these dimensions satisfactorily. Most items were related to interference (231) and intensity (138). Temporal pattern (which includes breakthrough pain), ranked as the second most important dimension, was covered by 29 items only. Many tools include dimensions and items of limited relevance for patients with advanced cancer. This might reduce compliance and threaten the validity of the assessment. New tools should reflect the clinical relevance of different dimensions and be user-friendly.

Quality pharmacy services and key performance indicators in Polish NICUs: a Delphi approach.

PubMed

Krzyżaniak, Natalia; Pawłowska, Iga; Bajorek, Beata

2018-03-31

Background Currently, there is no literature describing what a quality level of practice entails in Polish neonatal intensive care units (NICUs), nor are there any means of currently measuring the quality of pharmaceutical care provided to NICU patients. Objective To identify a set of essential pharmacist roles and pharmacy-relevant key performance indicators (KPI's) suitable for Polish neonatal intensive units (NICUs). Setting Polish hospital pharmacies and NICUs. Method Using a modified Delphi technique, potential KPI's structured along Donabedian's domains as well as pharmacy services were presented to an expert panel of stakeholders. Two online, consecutive Delphi rounds, were completed by panellists between August and September 2017. Main outcome measure To identify the minimum level of pharmacy services that should be consistently provided to NICU patients. Results A total of 16 panellists contributed to the expert panel. Overall, consensus of 75% was reached for 23 indicators and for 28 roles. When considering pharmacy services for the NICU, the experts were found to highly value traditional pharmacy roles, such as dispensing and extemporaneous compounding, however, they were still eager for roles in the other domains, such as educational and clinical services, to be listed as essential for NICU practice. Panellists were found to positively value the list of indicators presented, and excluded only 9 out of the total list. Conclusion There is a need for future research to establish a minimum standard of practice for Polish pharmacists to encourage the progression and standardisation of hospital pharmacy services to meet the level of practice seen in NICUs worldwide.

Functional magnetic resonance imaging examination of two modular architectures for switching multiple internal models.

PubMed

Imamizu, Hiroshi; Kuroda, Tomoe; Yoshioka, Toshinori; Kawato, Mitsuo

2004-02-04

An internal model is a neural mechanism that can mimic the input-output properties of a controlled object such as a tool. Recent research interests have moved on to how multiple internal models are learned and switched under a given context of behavior. Two representative computational models for task switching propose distinct neural mechanisms, thus predicting different brain activity patterns in the switching of internal models. In one model, called the mixture-of-experts architecture, switching is commanded by a single executive called a "gating network," which is different from the internal models. In the other model, called the MOSAIC (MOdular Selection And Identification for Control), the internal models themselves play crucial roles in switching. Consequently, the mixture-of-experts model predicts that neural activities related to switching and internal models can be temporally and spatially segregated, whereas the MOSAIC model predicts that they are closely intermingled. Here, we directly examined the two predictions by analyzing functional magnetic resonance imaging activities during the switching of one common tool (an ordinary computer mouse) and two novel tools: a rotated mouse, the cursor of which appears in a rotated position, and a velocity mouse, the cursor velocity of which is proportional to the mouse position. The switching and internal model activities temporally and spatially overlapped each other in the cerebellum and in the parietal cortex, whereas the overlap was very small in the frontal cortex. These results suggest that switching mechanisms in the frontal cortex can be explained by the mixture-of-experts architecture, whereas those in the cerebellum and the parietal cortex are explained by the MOSAIC model.

New predictive equations for Arias intensity from crustal earthquakes in New Zealand

NASA Astrophysics Data System (ADS)

Stafford, Peter J.; Berrill, John B.; Pettinga, Jarg R.

2009-01-01

Arias Intensity (Arias, MIT Press, Cambridge MA, pp 438-483, 1970) is an important measure of the strength of a ground motion, as it is able to simultaneously reflect multiple characteristics of the motion in question. Recently, the effectiveness of Arias Intensity as a predictor of the likelihood of damage to short-period structures has been demonstrated, reinforcing the utility of Arias Intensity for use in both structural and geotechnical applications. In light of this utility, Arias Intensity has begun to be considered as a ground-motion measure suitable for use in probabilistic seismic hazard analysis (PSHA) and earthquake loss estimation. It is therefore timely to develop predictive equations for this ground-motion measure. In this study, a suite of four predictive equations, each using a different functional form, is derived for the prediction of Arias Intensity from crustal earthquakes in New Zealand. The provision of a suite of models is included to allow for epistemic uncertainty to be considered within a PSHA framework. Coefficients are presented for four different horizontal-component definitions for each of the four models. The ground-motion dataset for which the equations are derived include records from New Zealand crustal earthquakes as well as near-field records from worldwide crustal earthquakes. The predictive equations may be used to estimate Arias Intensity for moment magnitudes between 5.1 and 7.5 and for distances (both rjb and rrup) up to 300 km.

Landscape ecological risk assessment study in arid land

NASA Astrophysics Data System (ADS)

Gong, Lu; Amut, Aniwaer; Shi, Qingdong; Wang, Gary Z.

2007-09-01

The ecosystem risk assessment is an essential decision making system for predicting the reconstruction and recovery of a damaged ecosystem after intensive mankind activities. The sustainability of environment and resources of the lake ecosystem in arid districts have been paid close attention to by international communities as well as numerous experts and scholars. The ecological risk assessment offered a scientific foundation for making the decision and execution of ecological risk management. Bosten Lake, the largest inland freshwater lake in China, is the main water source of the industrial and agricultural production as well as the local residence in Yanqi basin, Kuara city and Yuri County in the southern Xinjiang. Bosten Lake also provides a direct water source for emergency transportation in the Lower Reaches of Tarim River. However, with the intensive utilizations of water and soil resources, the environmental condition in the Bosten Lake has become more and more serious. In this study, the theory and method of landscape ecological risk assessment has been practiced using 3S technologies combined with the frontier theory of landscape ecology. Defining the mainly risk resource including flood, drought, water pollution and rich nutrition of water has been evaluated based on the ecosystem risk assessment system. The main process includes five stages: regional natural resources analysis, risk receptor selection, risk sources evaluation, exposure and hazard analysis, and integrated risk assessment. Based on the risk assessment results, the environmental risk management countermeasure has been determined.

Estimating outcomes in newborn infants using fuzzy logic

PubMed Central

Chaves, Luciano Eustáquio; Nascimento, Luiz Fernando C.

2014-01-01

OBJECTIVE: To build a linguistic model using the properties of fuzzy logic to estimate the risk of death of neonates admitted to a Neonatal Intensive Care Unit. METHODS: Computational model using fuzzy logic. The input variables of the model were birth weight, gestational age, 5th-minute Apgar score and inspired fraction of oxygen in newborn infants admitted to a Neonatal Intensive Care Unit of Taubaté, Southeast Brazil. The output variable was the risk of death, estimated as a percentage. Three membership functions related to birth weight, gestational age and 5th-minute Apgar score were built, as well as two functions related to the inspired fraction of oxygen; the risk presented five membership functions. The model was developed using the Mandani inference by means of Matlab(r) software. The model values were compared with those provided by experts and their performance was estimated by ROC curve. RESULTS: 100 newborns were included, and eight of them died. The model estimated an average possibility of death of 49.7±29.3%, and the possibility of hospital discharge was 24±17.5%. These values are different when compared by Student's t-test (p<0.001). The correlation test revealed r=0.80 and the performance of the model was 81.9%. CONCLUSIONS: This predictive, non-invasive and low cost model showed a good accuracy and can be applied in neonatal care, given the easiness of its use. PMID:25119746

Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.

Perceived competence in computer use as a moderator of musculoskeletal strain in VDU work: an ergonomics intervention case.

PubMed

Tuomivaara, S; Ketola, R; Huuhtanen, P; Toivonen, R

2008-02-01

Musculoskeletal strain and other symptoms are common in visual display unit (VDU) work. Psychosocial factors are closely related to the outcome and experience of musculoskeletal strain. The user-computer relationship from the viewpoint of the quality of perceived competence in computer use was assessed as a psychosocial stress indicator. It was assumed that the perceived competence in computer use moderates the experience of musculoskeletal strain and the success of the ergonomics intervention. The participants (n = 124, female 58%, male 42%) worked with VDU for more than 4 h per week. They took part in an ergonomics intervention and were allocated into three groups: intensive; education; and reference group. Musculoskeletal strain, the level of ergonomics of the workstation assessed by the experts in ergonomics and amount of VDU work were estimated at the baseline and at the 10-month follow-up. Age, gender and the perceived competence in computer use were assessed at the baseline. The perceived competence in computer use predicted strain in the upper and the lower part of the body at the follow-up. The interaction effect shows that the intensive ergonomics intervention procedure was the most effective among participants with high perceived competence. The interpretation of the results was that an anxiety-provoking and stressful user-computer relationship prevented the participants from being motivated and from learning in the ergonomics intervention. In the intervention it is important to increase the computer competence along with the improvements of physical workstation and work organization.

Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula

PubMed Central

Geuter, Stephan; Boll, Sabrina; Eippert, Falk; Büchel, Christian

2017-01-01

The computational principles by which the brain creates a painful experience from nociception are still unknown. Classic theories suggest that cortical regions either reflect stimulus intensity or additive effects of intensity and expectations, respectively. By contrast, predictive coding theories provide a unified framework explaining how perception is shaped by the integration of beliefs about the world with mismatches resulting from the comparison of these beliefs against sensory input. Using functional magnetic resonance imaging during a probabilistic heat pain paradigm, we investigated which computations underlie pain perception. Skin conductance, pupil dilation, and anterior insula responses to cued pain stimuli strictly followed the response patterns hypothesized by the predictive coding model, whereas posterior insula encoded stimulus intensity. This novel functional dissociation of pain processing within the insula together with previously observed alterations in chronic pain offer a novel interpretation of aberrant pain processing as disturbed weighting of predictions and prediction errors. DOI: http://dx.doi.org/10.7554/eLife.24770.001 PMID:28524817

Deep learning based tissue analysis predicts outcome in colorectal cancer.

PubMed

Bychkov, Dmitrii; Linder, Nina; Turkki, Riku; Nordling, Stig; Kovanen, Panu E; Verrill, Clare; Walliander, Margarita; Lundin, Mikael; Haglund, Caj; Lundin, Johan

2018-02-21

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low- and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.

Experts Foresee a Major Shift From Inpatient to Ambulatory Care.

PubMed

Beans, Bruce E

2016-04-01

An American Society of Health-System Pharmacists Research and Education Foundation report predicts trends in health care delivery and financing, drug development and therapeutics, pharmaceutical marketplace, pharmacy workforce, and more.

Saturn Radiation (SATRAD) Model

NASA Technical Reports Server (NTRS)

Garrett, H. B.; Ratliff, J. M.; Evans, R. W.

2005-01-01

The Saturnian radiation belts have not received as much attention as the Jovian radiation belts because they are not nearly as intense-the famous Saturnian particle rings tend to deplete the belts near where their peak would occur. As a result, there has not been a systematic development of engineering models of the Saturnian radiation environment for mission design. A primary exception is that of Divine (1990). That study used published data from several charged particle experiments aboard the Pioneer 1 1, Voyager 1, and Voyager 2 spacecraft during their flybys at Saturn to generate numerical models for the electron and proton radiation belts between 2.3 and 13 Saturn radii. The Divine Saturn radiation model described the electron distributions at energies between 0.04 and 10 MeV and the proton distributions at energies between 0.14 and 80 MeV. The model was intended to predict particle intensity, flux, and fluence for the Cassini orbiter. Divine carried out hand calculations using the model but never formally developed a computer program that could be used for general mission analyses. This report seeks to fill that void by formally developing a FORTRAN version of the model that can be used as a computer design tool for missions to Saturn that require estimates of the radiation environment around the planet. The results of that effort and the program listings are presented here along with comparisons with the original estimates carried out by Divine. In addition, Pioneer and Voyager data were scanned in from the original references and compared with the FORTRAN model s predictions. The results were statistically analyzed in a manner consistent with Divine s approach to provide estimates of the ability of the model to reproduce the original data. Results of a formal review of the model by a panel of experts are also presented. Their recommendations for further tests, analyses, and extensions to the model are discussed.

MRMaid, the web-based tool for designing multiple reaction monitoring (MRM) transitions.

PubMed

Mead, Jennifer A; Bianco, Luca; Ottone, Vanessa; Barton, Chris; Kay, Richard G; Lilley, Kathryn S; Bond, Nicholas J; Bessant, Conrad

2009-04-01

Multiple reaction monitoring (MRM) of peptides uses tandem mass spectrometry to quantify selected proteins of interest, such as those previously identified in differential studies. Using this technique, the specificity of precursor to product transitions is harnessed for quantitative analysis of multiple proteins in a single sample. The design of transitions is critical for the success of MRM experiments, but predicting signal intensity of peptides and fragmentation patterns ab initio is challenging given existing methods. The tool presented here, MRMaid (pronounced "mermaid") offers a novel alternative for rapid design of MRM transitions for the proteomics researcher. The program uses a combination of knowledge of the properties of optimal MRM transitions taken from expert practitioners and literature with MS/MS evidence derived from interrogation of a database of peptide identifications and their associated mass spectra. The tool also predicts retention time using a published model, allowing ordering of transition candidates. By exploiting available knowledge and resources to generate the most reliable transitions, this approach negates the need for theoretical prediction of fragmentation and the need to undertake prior "discovery" MS studies. MRMaid is a modular tool built around the Genome Annotating Proteomic Pipeline framework, providing a web-based solution with both descriptive and graphical visualizations of transitions. Predicted transition candidates are ranked based on a novel transition scoring system, and users may filter the results by selecting optional stringency criteria, such as omitting frequently modified residues, constraining the length of peptides, or omitting missed cleavages. Comparison with published transitions showed that MRMaid successfully predicted the peptide and product ion pairs in the majority of cases with appropriate retention time estimates. As the data content of the Genome Annotating Proteomic Pipeline repository increases, the coverage and reliability of MRMaid are set to increase further. MRMaid is freely available over the internet as an executable web-based service at www.mrmaid.info.

MRMaid, the Web-based Tool for Designing Multiple Reaction Monitoring (MRM) Transitions*

PubMed Central

Mead, Jennifer A.; Bianco, Luca; Ottone, Vanessa; Barton, Chris; Kay, Richard G.; Lilley, Kathryn S.; Bond, Nicholas J.; Bessant, Conrad

2009-01-01

Multiple reaction monitoring (MRM) of peptides uses tandem mass spectrometry to quantify selected proteins of interest, such as those previously identified in differential studies. Using this technique, the specificity of precursor to product transitions is harnessed for quantitative analysis of multiple proteins in a single sample. The design of transitions is critical for the success of MRM experiments, but predicting signal intensity of peptides and fragmentation patterns ab initio is challenging given existing methods. The tool presented here, MRMaid (pronounced “mermaid”) offers a novel alternative for rapid design of MRM transitions for the proteomics researcher. The program uses a combination of knowledge of the properties of optimal MRM transitions taken from expert practitioners and literature with MS/MS evidence derived from interrogation of a database of peptide identifications and their associated mass spectra. The tool also predicts retention time using a published model, allowing ordering of transition candidates. By exploiting available knowledge and resources to generate the most reliable transitions, this approach negates the need for theoretical prediction of fragmentation and the need to undertake prior “discovery” MS studies. MRMaid is a modular tool built around the Genome Annotating Proteomic Pipeline framework, providing a web-based solution with both descriptive and graphical visualizations of transitions. Predicted transition candidates are ranked based on a novel transition scoring system, and users may filter the results by selecting optional stringency criteria, such as omitting frequently modified residues, constraining the length of peptides, or omitting missed cleavages. Comparison with published transitions showed that MRMaid successfully predicted the peptide and product ion pairs in the majority of cases with appropriate retention time estimates. As the data content of the Genome Annotating Proteomic Pipeline repository increases, the coverage and reliability of MRMaid are set to increase further. MRMaid is freely available over the internet as an executable web-based service at www.mrmaid.info. PMID:19011259

Heart health risk assessment system: a nonintrusive proposal using ontologies and expert rules.

PubMed

Garcia-Valverde, Teresa; Muñoz, Andrés; Arcas, Francisco; Bueno-Crespo, Andrés; Caballero, Alberto

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch.

Dance and music share gray matter structural correlates.

PubMed

Karpati, Falisha J; Giacosa, Chiara; Foster, Nicholas E V; Penhune, Virginia B; Hyde, Krista L

2017-02-15

Intensive practise of sensorimotor skills, such as music and dance, is associated with brain structural plasticity. While the neural correlates of music have been well-investigated, less is known about the neural correlates of dance. Additionally, the gray matter structural correlates of dance versus music training have not yet been directly compared. The objectives of the present study were to compare gray matter structure as measured by surface- and voxel-based morphometry between expert dancers, expert musicians and untrained controls, as well as to correlate gray matter structure with performance on dance- and music-related tasks. Dancers and musicians were found to have increased cortical thickness compared to controls in superior temporal regions. Gray matter structure in the superior temporal gyrus was also correlated with performance on dance imitation, rhythm synchronization and melody discrimination tasks. These results suggest that superior temporal regions are important in both dance- and music-related skills and may be affected similarly by both types of long-term intensive training. This work advances knowledge of the neural correlates of dance and music, as well as training-associated brain plasticity in general. Copyright © 2016 Elsevier B.V. All rights reserved.

[Main principles of rapid diagnosis and intensive care in emergency states: their realization in expert systems].

PubMed

Zislin, B D; Bazhenov, A M; Belkin, A A; Bazylev, S V; Badaev, F I; Trifonov, Iu O

1997-01-01

A retrospective analysis of 543 case histories over 1980-1990 in the town of Yekaterinburg and analysis of published data permitted the authors to single out the signs characterizing the most frequent syndromes requiring urgent intensive care. By either diagnostic value, these signs are distributed into main, accessory, and ruling out. An expert system has been created, making use of the productive-Freimont's approach to representing information on the basis of blurred multiplicities and ambiguous logics. The diagnosis was made by stages: first the main signs were analyzed, determining the severity of patient's status, then (after first aid was rendered) accessory and ruling out signs, which help make the diagnosis more precise. The system was tried in 231 patients, 102 of these with acute respiratory failure, 63 with acute hemodynamic insufficiency, and 66 with acute cerebral insufficiency. Primary diagnosis of the underlying syndrome was correct in 87-89% of cases, of the concomitant syndrome in 92-97%. Repeated evaluations (in 1-3 and 24 h) taking account of the time course of the symptoms and of the results of unsophisticated instrumental examinations increased the share of correct diagnoses to 92-96%.

Heart Health Risk Assessment System: A Nonintrusive Proposal Using Ontologies and Expert Rules

PubMed Central

2014-01-01

According to the World Health Organization, the world's leading cause of death is heart disease, with nearly two million deaths per year. Although some factors are not possible to change, there are some keys that help to prevent heart diseases. One of the most important keys is to keep an active daily life, with moderate exercise. However, deciding what a moderate exercise is or when a slightly abnormal heart rate value is a risk depends on the person and the activity. In this paper we propose a context-aware system that is able to determine the activity the person is performing in an unobtrusive way. Then, we have defined ontology to represent the available knowledge about the person (biometric data, fitness status, medical information, etc.) and her current activity (level of intensity, heart rate recommended for that activity, etc.). With such knowledge, a set of expert rules based on this ontology are involved in a reasoning process to infer levels of alerts or suggestions for the users when the intensity of the activity is detected as dangerous for her health. We show how this approach can be accomplished by using only everyday devices such as a smartphone and a smartwatch. PMID:25045715

Mapping species abundance by a spatial zero-inflated Poisson model: a case study in the Wadden Sea, the Netherlands.

PubMed

Lyashevska, Olga; Brus, Dick J; van der Meer, Jaap

2016-01-01

The objective of the study was to provide a general procedure for mapping species abundance when data are zero-inflated and spatially correlated counts. The bivalve species Macoma balthica was observed on a 500×500 m grid in the Dutch part of the Wadden Sea. In total, 66% of the 3451 counts were zeros. A zero-inflated Poisson mixture model was used to relate counts to environmental covariates. Two models were considered, one with relatively fewer covariates (model "small") than the other (model "large"). The models contained two processes: a Bernoulli (species prevalence) and a Poisson (species intensity, when the Bernoulli process predicts presence). The model was used to make predictions for sites where only environmental data are available. Predicted prevalences and intensities show that the model "small" predicts lower mean prevalence and higher mean intensity, than the model "large". Yet, the product of prevalence and intensity, which might be called the unconditional intensity, is very similar. Cross-validation showed that the model "small" performed slightly better, but the difference was small. The proposed methodology might be generally applicable, but is computer intensive.

CPO Prediction: Accuracy Assessment and Impact on UT1 Intensive Results

NASA Technical Reports Server (NTRS)

Malkin, Zinovy

2010-01-01

The UT1 Intensive results heavily depend on the celestial pole offset (CPO) model used during data processing. Since accurate CPO values are available with a delay of two to four weeks, CPO predictions are necessarily applied to the UT1 Intensive data analysis, and errors in the predictions can influence the operational UT1 accuracy. In this paper we assess the real accuracy of CPO prediction using the actual IERS and PUL predictions made in 2007-2009. Also, results of operational processing were analyzed to investigate the actual impact of EOP prediction errors on the rapid UT1 results. It was found that the impact of CPO prediction errors is at a level of several microseconds, whereas the impact of the inaccuracy in the polar motion prediction may be about one order of magnitude larger for ultra-rapid UT1 results. The situation can be amended if the IERS Rapid solution will be updated more frequently.

Neural processing of emotional-intensity predicts emotion regulation choice.

PubMed

Shafir, Roni; Thiruchselvam, Ravi; Suri, Gaurav; Gross, James J; Sheppes, Gal

2016-12-01

Emotional-intensity is a core characteristic of affective events that strongly determines how individuals choose to regulate their emotions. Our conceptual framework suggests that in high emotional-intensity situations, individuals prefer to disengage attention using distraction, which can more effectively block highly potent emotional information, as compared with engagement reappraisal, which is preferred in low emotional-intensity. However, existing supporting evidence remains indirect because prior intensity categorization of emotional stimuli was based on subjective measures that are potentially biased and only represent the endpoint of emotional-intensity processing. Accordingly, this study provides the first direct evidence for the role of online emotional-intensity processing in predicting behavioral regulatory-choices. Utilizing the high temporal resolution of event-related potentials, we evaluated online neural processing of stimuli's emotional-intensity (late positive potential, LPP) prior to regulatory-choices between distraction and reappraisal. Results showed that enhanced neural processing of intensity (enhanced LPP amplitudes) uniquely predicted (above subjective measures of intensity) increased tendency to subsequently choose distraction over reappraisal. Additionally, regulatory-choices led to adaptive consequences, demonstrated in finding that actual implementation of distraction relative to reappraisal-choice resulted in stronger attenuation of LPPs and self-reported arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Development of an expert system for analysis of Shuttle atmospheric revitalization and pressure control subsystem anomalies

NASA Technical Reports Server (NTRS)

Lafuse, Sharon A.

1991-01-01

The paper describes the Shuttle Leak Management Expert System (SLMES), a preprototype expert system developed to enable the ECLSS subsystem manager to analyze subsystem anomalies and to formulate flight procedures based on flight data. The SLMES combines the rule-based expert system technology with the traditional FORTRAN-based software into an integrated system. SLMES analyzes the data using rules, and, when it detects a problem that requires simulation, it sets up the input for the FORTRAN-based simulation program ARPCS2AT2, which predicts the cabin total pressure and composition as a function of time. The program simulates the pressure control system, the crew oxygen masks, the airlock repress/depress valves, and the leakage. When the simulation has completed, other SLMES rules are triggered to examine the results of simulation contrary to flight data and to suggest methods for correcting the problem. Results are then presented in form of graphs and tables.

Fuzzy Expert System for Heart Attack Diagnosis

NASA Astrophysics Data System (ADS)

Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

2017-08-01

Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

Expert explanations of honeybee losses in areas of extensive agriculture in France: Gaucho® compared with other supposed causal factors

NASA Astrophysics Data System (ADS)

Maxim, L.; van der Sluijs, J. P.

2010-01-01

Debates on causality are at the core of controversies as regards environmental changes. The present paper presents a new method for analyzing controversies on causality in a context of social debate and the results of its empirical testing. The case study used is the controversy as regards the role played by the insecticide Gaucho®, compared with other supposed causal factors, in the substantial honeybee (Apis mellifera L.) losses reported to have occurred in France between 1994 and 2004. The method makes use of expert elicitation of the perceived strength of evidence regarding each of Bradford Hill's causality criteria, as regards the link between each of eight possible causal factors identified in attempts to explain each of five signs observed in honeybee colonies. These judgments are elicited from stakeholders and experts involved in the debate, i.e., representatives of Bayer Cropscience, of the Ministry of Agriculture, of the French Food Safety Authority, of beekeepers and of public scientists. We show that the intense controversy observed in confused and passionate public discourses is much less salient when the various arguments are structured using causation criteria. The contradictions between the different expert views have a triple origin: (1) the lack of shared definition and quantification of the signs observed in colonies; (2) the lack of specialist knowledge on honeybees; and (3) the strategic discursive practices associated with the lack of trust between experts representing stakeholders having diverging stakes in the case.

Knowledge of Fecal Calprotectin and Infliximab Trough Levels Alters Clinical Decision-making for IBD Outpatients on Maintenance Infliximab Therapy.

PubMed

Huang, Vivian W; Prosser, Connie; Kroeker, Karen I; Wang, Haili; Shalapay, Carol; Dhami, Neil; Fedorak, Darryl K; Halloran, Brendan; Dieleman, Levinus A; Goodman, Karen J; Fedorak, Richard N

2015-06-01

Infliximab is an effective therapy for inflammatory bowel disease (IBD). However, more than 50% of patients lose response. Empiric dose intensification is not effective for all patients because not all patients have objective disease activity or subtherapeutic drug level. The aim was to determine how an objective marker of disease activity or therapeutic drug monitoring affects clinical decisions regarding maintenance infliximab therapy in outpatients with IBD. Consecutive patients with IBD on maintenance infliximab therapy were invited to participate by providing preinfusion stool and blood samples. Fecal calprotectin (FCP) and infliximab trough levels (ITLs) were measured by enzyme linked immunosorbent assay. Three decisions were compared: (1) actual clinical decision, (2) algorithmic FCP or ITL decisions, and (3) expert panel decision based on (a) clinical data, (b) clinical data plus FCP, and (c) clinical data plus FCP plus ITL. In secondary analysis, Receiver-operating curves were used to assess the ability of FCP and ITL in predicting clinical disease activity or remission. A total of 36 sets of blood and stool were available for analysis; median FCP 191.5 μg/g, median ITLs 7.3 μg/mL. The actual clinical decision differed from the hypothetical decision in 47.2% (FCP algorithm); 69.4% (ITL algorithm); 25.0% (expert panel clinical decision); 44.4% (expert panel clinical plus FCP); 58.3% (expert panel clinical plus FCP plus ITL) cases. FCP predicted clinical relapse (area under the curve [AUC] = 0.417; 95% confidence interval [CI], 0.197-0.641) and subtherapeutic ITL (AUC = 0.774; 95% CI, 0.536-1.000). ITL predicted clinical remission (AUC = 0.498; 95% CI, 0.254-0.742) and objective remission (AUC = 0.773; 95% CI, 0.622-0.924). Using FCP and ITLs in addition to clinical data results in an increased number of decisions to optimize management in outpatients with IBD on stable maintenance infliximab therapy.

Functional MRI reveals expert-novice differences during sport-related anticipation.

PubMed

Wright, Michael J; Bishop, Daniel T; Jackson, Robin C; Abernethy, Bruce

2010-01-27

We examined the effect of expertise on cortical activation during sports anticipation using functional MRI. In experiment 1, recreational players predicted badminton stroke direction and the pattern of active clusters was consistent with a proposed perception-of-action network. This pattern was not replicated in a stimulus-matched, action-unrelated control task. In experiment 2, players of three different skill levels anticipated stroke direction from clips occluded either 160 ms before or 80 ms after racquet-shuttle contact. Early-occluded sequences produced more activation than late-occluded sequences overall, in most cortical regions of interest, but experts showed an additional enhancement in medial, dorsolateral and ventrolateral frontal cortex. Anticipation in open-skill sports engages cortical areas integral to observing and understanding others' actions; such activity is enhanced in experts.

Complex Causal Process Diagrams for Analyzing the Health Impacts of Policy Interventions

PubMed Central

Joffe, Michael; Mindell, Jennifer

2006-01-01

Causal diagrams are rigorous tools for controlling confounding. They also can be used to describe complex causal systems, which is done routinely in communicable disease epidemiology. The use of change diagrams has advantages over static diagrams, because change diagrams are more tractable, relate better to interventions, and have clearer interpretations. Causal diagrams are a useful basis for modeling. They make assumptions explicit, provide a framework for analysis, generate testable predictions, explore the effects of interventions, and identify data gaps. Causal diagrams can be used to integrate different types of information and to facilitate communication both among public health experts and between public health experts and experts in other fields. Causal diagrams allow the use of instrumental variables, which can help control confounding and reverse causation. PMID:16449586

How to Build an AppleSeed: A Parallel Macintosh Cluster for Numerically Intensive Computing

NASA Astrophysics Data System (ADS)

Decyk, V. K.; Dauger, D. E.

We have constructed a parallel cluster consisting of a mixture of Apple Macintosh G3 and G4 computers running the Mac OS, and have achieved very good performance on numerically intensive, parallel plasma particle-incell simulations. A subset of the MPI message-passing library was implemented in Fortran77 and C. This library enabled us to port code, without modification, from other parallel processors to the Macintosh cluster. Unlike Unix-based clusters, no special expertise in operating systems is required to build and run the cluster. This enables us to move parallel computing from the realm of experts to the main stream of computing.

A Multicenter Study of Key Stakeholders’ Perspectives on Communicating with Surrogates about Prognosis in Intensive Care Units

PubMed Central

Cimino, Jenica W.; Ernecoff, Natalie C.; Ungar, Anna; Shotsberger, Kaitlin J.; Pollice, Laura A.; Buddadhumaruk, Praewpannarai; Carson, Shannon S.; Curtis, J. Randall; Hough, Catherine L.; Lo, Bernard; Matthay, Michael A.; Peterson, Michael W.; Steingrub, Jay S.; White, Douglas B.

2015-01-01

Rationale: Surrogates of critically ill patients often have inaccurate expectations about prognosis. Yet there is little research on how intensive care unit (ICU) clinicians should discuss prognosis, and existing expert opinion–based recommendations give only general guidance that has not been validated with surrogate decision makers. Objective: To determine the perspectives of key stakeholders regarding how prognostic information should be conveyed in critical illness. Methods: This was a multicenter study at three academic medical centers in California, Pennsylvania, and Washington. One hundred eighteen key stakeholders completed in-depth semistructured interviews. Participants included 47 surrogates of adult patients with acute respiratory distress syndrome; 45 clinicians working in study ICUs, including physicians, nurses, social workers, and spiritual care providers; and 26 experts in health communication, decision science, ethics, family-centered care, geriatrics, healthcare disparities, palliative care, psychology, psychiatry, and critical care. Measurements and Main Results: There was broad support among surrogates for existing expert recommendations, including truthful prognostic disclosure, emotional support, tailoring the disclosure strategy to each family’s needs, and checking for understanding. In addition, stakeholders offered suggestions that add specificity to existing recommendations, including: (1) In addition to conveying prognostic estimates, clinicians should help families “see the prognosis for themselves” by showing families radiographic images and explaining the clinical significance of physical manifestations of severe disease at the bedside. (2) Many physicians did not support using numeric estimates to convey prognosis to families, whereas many surrogates, clinicians from other disciplines, and experts believed numbers could be helpful. (3) Clinicians should conceptualize prognostic communication as an iterative process that begins with a preliminary mention of the possibility of death early in the ICU stay and becomes more detailed as the clinical situation develops. (4) Although prognostic information should be initially disclosed by physicians, other members of the multidisciplinary team—nurses, social workers, and spiritual care providers—should be given explicit role responsibilities to reinforce physicians’ prognostications and help families process a poor prognosis emotionally. Conclusions: Family members, clinicians, and experts identified specific communication behaviors that clinicians should use to discuss prognosis in the critical care setting. These findings extend existing opinion-based recommendations and should guide interventions to improve communication about prognosis in ICUs. PMID:25521191

Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior: A Danish Study of Adolescents at a High Risk of Suicide.

PubMed

Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William; Jakobsen, Ida Skytte; Larsen, Kim Juul

2017-07-03

Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85 adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior at follow-up over and above suicidal behavior at baseline. Actual suicide attempts at baseline strongly predicted suicide attempts at follow-up. Baseline suicidal ideation severity and intensity did not significantly predict future actual attempts over and above baseline attempts. The suicidal ideation intensity items deterrents and duration were significant predictors of subsequent actual attempts after adjustment for baseline suicide attempts and suicidal behavior of any type, respectively. Suicidal ideation severity and intensity, and the intensity items frequency, duration and deterrents, all significantly predicted any type of suicidal behavior at follow-up, also after adjusting for baseline suicidal behavior. The present study points to an incremental predictive validity of the C-SSRS suicidal ideation scales for short-term suicidal behavior of any type among high-risk adolescents.

Scientists versus regulators: precaution, novelty & regulatory oversight as predictors of perceived risks of engineered nanomaterials.

PubMed

Beaudrie, Christian E H; Satterfield, Terre; Kandlikar, Milind; Harthorn, Barbara H

2014-01-01

Engineered nanoscale materials (ENMs) present a difficult challenge for risk assessors and regulators. Continuing uncertainty about the potential risks of ENMs means that expert opinion will play an important role in the design of policies to minimize harmful implications while supporting innovation. This research aims to shed light on the views of 'nano experts' to understand which nanomaterials or applications are regarded as more risky than others, to characterize the differences in risk perceptions between expert groups, and to evaluate the factors that drive these perceptions. Our analysis draws from a web-survey (N = 404) of three groups of US and Canadian experts: nano-scientists and engineers, nano-environmental health and safety scientists, and regulatory scientists and decision-makers. Significant differences in risk perceptions were found across expert groups; differences found to be driven by underlying attitudes and perceptions characteristic of each group. Nano-scientists and engineers at the upstream end of the nanomaterial life cycle perceived the lowest levels of risk, while those who are responsible for assessing and regulating risks at the downstream end perceived the greatest risk. Perceived novelty of nanomaterial risks, differing preferences for regulation (i.e. the use of precaution versus voluntary or market-based approaches), and perceptions of the risk of technologies in general predicted variation in experts' judgments of nanotechnology risks. Our findings underscore the importance of involving a diverse selection of experts, particularly those with expertise at different stages along the nanomaterial lifecycle, during policy development.

Simulation Of Combat With An Expert System

NASA Technical Reports Server (NTRS)

Provenzano, J. P.

1989-01-01

Proposed expert system predicts outcomes of combat situations. Called "COBRA", combat outcome based on rules for attrition, system selects rules for mathematical modeling of losses and discrete events in combat according to previous experiences. Used with another software module known as the "Game". Game/COBRA software system, consisting of Game and COBRA modules, provides for both quantitative aspects and qualitative aspects in simulations of battles. COBRA intended for simulation of large-scale military exercises, concepts embodied in it have much broader applicability. In industrial research, knowledge-based system enables qualitative as well as quantitative simulations.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, Betty M.

1988-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth science. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of US energy and mineral resources.

FUTURE APPLICATIONS OF EXPERT SYSTEMS FOR THE EVALUATION OF ENERGY RESOURCES.

USGS Publications Warehouse

Miller, B.M.

1987-01-01

The loss of professional experience and expertise in the domain of the earth sciences may prove to be one of the most serious outcomes of the boom-and-bust cyclic nature of the volatile energy and mining industries. Promising new applications of powerful computer systems, known as 'expert systems' or 'knowledge-based systems', are predicted for use in the earth sciences. These systems have the potential capability to capture and preserve the invaluable knowledge bases essential to the evaluation of the Nation's energy and mineral resources.

Exercise Prescription in Patients with Different Combinations of Cardiovascular Disease Risk Factors: A Consensus Statement from the EXPERT Working Group.

PubMed

Hansen, Dominique; Niebauer, Josef; Cornelissen, Veronique; Barna, Olga; Neunhäuserer, Daniel; Stettler, Christoph; Tonoli, Cajsa; Greco, Eugenio; Fagard, Robert; Coninx, Karin; Vanhees, Luc; Piepoli, Massimo F; Pedretti, Roberto; Ruiz, Gustavo Rovelo; Corrà, Ugo; Schmid, Jean-Paul; Davos, Constantinos H; Edelmann, Frank; Abreu, Ana; Rauch, Bernhard; Ambrosetti, Marco; Braga, Simona Sarzi; Beckers, Paul; Bussotti, Maurizio; Faggiano, Pompilio; Garcia-Porrero, Esteban; Kouidi, Evangelia; Lamotte, Michel; Reibis, Rona; Spruit, Martijn A; Takken, Tim; Vigorito, Carlo; Völler, Heinz; Doherty, Patrick; Dendale, Paul

2018-05-04

Whereas exercise training is key in the management of patients with cardiovascular disease (CVD) risk (obesity, diabetes, dyslipidaemia, hypertension), clinicians experience difficulties in how to optimally prescribe exercise in patients with different CVD risk factors. Therefore, a consensus statement for state-of-the-art exercise prescription in patients with combinations of CVD risk factors as integrated into a digital training and decision support system (the EXercise Prescription in Everyday practice & Rehabilitative Training (EXPERT) tool) needed to be established. EXPERT working group members systematically reviewed the literature for meta-analyses, systematic reviews and/or clinical studies addressing exercise prescriptions in specific CVD risk factors and formulated exercise recommendations (exercise training intensity, frequency, volume and type, session and programme duration) and exercise safety precautions, for obesity, arterial hypertension, type 1 and 2 diabetes, and dyslipidaemia. The impact of physical fitness, CVD risk altering medications and adverse events during exercise testing was further taken into account to fine-tune this exercise prescription. An algorithm, supported by the interactive EXPERT tool, was developed by Hasselt University based on these data. Specific exercise recommendations were formulated with the aim to decrease adipose tissue mass, improve glycaemic control and blood lipid profile, and lower blood pressure. The impact of medications to improve CVD risk, adverse events during exercise testing and physical fitness was also taken into account. Simulations were made of how the EXPERT tool provides exercise prescriptions according to the variables provided. In this paper, state-of-the-art exercise prescription to patients with combinations of CVD risk factors is formulated, and it is shown how the EXPERT tool may assist clinicians. This contributes to an appropriately tailored exercise regimen for every CVD risk patient.

Improved operator agreement and efficiency using the minimum area contour change method for delineation of hyperintense multiple sclerosis lesions on FLAIR MRI

PubMed Central

2013-01-01

Background Activity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans. The Minimum Area Contour Change (MACC) algorithm has been created with two main goals: a) to improve inter-operator agreement on outlining regions of interest (ROIs) and b) to automatically propagate longitudinal ROIs from the baseline scan to a follow-up scan. Methods The MACC algorithm first identifies an outer bound for the solution path, forms a high number of iso-contour curves based on equally spaced contour values, and then selects the best contour value to outline the lesion. The MACC software was tested on a set of 17 FLAIR MRI images evaluated by a pair of human experts and a longitudinal dataset of 12 pairs of T2-weighted Fluid Attenuated Inversion Recovery (FLAIR) images that had lesion analysis ROIs drawn by a single expert operator. Results In the tests where two human experts evaluated the same MRI images, the MACC program demonstrated that it could markedly reduce inter-operator outline error. In the longitudinal part of the study, the MACC program created ROIs on follow-up scans that were in close agreement to the original expert’s ROIs. Finally, in a post-hoc analysis of 424 follow-up scans 91% of propagated MACC were accepted by an expert and only 9% of the final accepted ROIS had to be created or edited by the expert. Conclusion When used with an expert operator's verification of automatically created ROIs, MACC can be used to improve inter- operator agreement and decrease analysis time, which should improve data collected and analyzed in multicenter clinical trials. PMID:24004511

Expert system for computer-assisted annotation of MS/MS spectra.

PubMed

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-11-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions.

Expert System for Computer-assisted Annotation of MS/MS Spectra*

PubMed Central

Neuhauser, Nadin; Michalski, Annette; Cox, Jürgen; Mann, Matthias

2012-01-01

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions. PMID:22888147

Expert opinion as 'validation' of risk assessment applied to calf welfare.

PubMed

Bracke, Marc B M; Edwards, Sandra A; Engel, Bas; Buist, Willem G; Algers, Bo

2008-07-14

Recently, a Risk Assessment methodology was applied to animal welfare issues in a report of the European Food Safety Authority (EFSA) on intensively housed calves. Because this is a new and potentially influential approach to derive conclusions on animal welfare issues, a so-called semantic-modelling type 'validation' study was conducted by asking expert scientists, who had been involved or quoted in the report, to give welfare scores for housing systems and for welfare hazards. Kendall's coefficient of concordance among experts (n = 24) was highly significant (P < 0.001), but low (0.29 and 0.18 for housing systems and hazards respectively). Overall correlations with EFSA scores were significant only for experts with a veterinary or mixed (veterinary and applied ethological) background. Significant differences in welfare scores were found between housing systems, between hazards, and between experts with different backgrounds. For example, veterinarians gave higher overall welfare scores for housing systems than ethologists did, probably reflecting a difference in their perception of animal welfare. Systems with the lowest scores were veal calves kept individually in so-called "baby boxes" (veal crates) or in small groups, and feedlots. A suckler herd on pasture was rated as the best for calf welfare. The main hazards were related to underfeeding, inadequate colostrum intake, poor stockperson education, insufficient space, inadequate roughage, iron deficiency, inadequate ventilation, poor floor conditions and no bedding. Points for improvement of the Risk Assessment applied to animal welfare include linking information, reporting uncertainty and transparency about underlying values. The study provides novel information on expert opinion in relation to calf welfare and shows that Risk Assessment applied to animal welfare can benefit from a semantic modelling approach.

Expert consensus contouring guidelines for IMRT in esophageal and gastroesophageal junction cancer

PubMed Central

Wu, Abraham J.; Bosch, Walter R.; Chang, Daniel T.; Hong, Theodore S.; Jabbour, Salma K.; Kleinberg, Lawrence R.; Mamon, Harvey J.; Thomas, Charles R.; Goodman, Karyn A.

2015-01-01

Purpose/Objective(s) Current guidelines for esophageal cancer contouring are derived from traditional two-dimensional fields based on bony landmarks, and do not provide sufficient anatomical detail to ensure consistent contouring for more conformal radiotherapy techniques such as intensity-modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials Eight expert academically-based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform CT simulation datasets and an accompanying diagnostic PET-CT were distributed to each expert, and he/she was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results Kappa statistics indicated substantial agreement between panelists for each of the three test cases. A consensus CTV atlas was generated for the three test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets utilizing these guidelines may require modification in the future. PMID:26104943

Prediction of genotoxic potential of cosmetic ingredients by an in silico battery system consisting of a combination of an expert rule-based system and a statistics-based system.

PubMed

Aiba née Kaneko, Maki; Hirota, Morihiko; Kouzuki, Hirokazu; Mori, Masaaki

2015-02-01

Genotoxicity is the most commonly used endpoint to predict the carcinogenicity of chemicals. The International Conference on Harmonization (ICH) M7 Guideline on Assessment and Control of DNA Reactive (Mutagenic) Impurities in Pharmaceuticals to Limit Potential Carcinogenic Risk offers guidance on (quantitative) structure-activity relationship ((Q)SAR) methodologies that predict the outcome of bacterial mutagenicity assay for actual and potential impurities. We examined the effectiveness of the (Q)SAR approach with the combination of DEREK NEXUS as an expert rule-based system and ADMEWorks as a statistics-based system for the prediction of not only mutagenic potential in the Ames test, but also genotoxic potential in mutagenicity and clastogenicity tests, using a data set of 342 chemicals extracted from the literature. The prediction of mutagenic potential or genotoxic potential by DEREK NEXUS or ADMEWorks showed high values of sensitivity and concordance, while prediction by the combination of DEREK NEXUS and ADMEWorks (battery system) showed the highest values of sensitivity and concordance among the three methods, but the lowest value of specificity. The number of false negatives was reduced with the battery system. We also separately predicted the mutagenic potential and genotoxic potential of 41 cosmetic ingredients listed in the International Nomenclature of Cosmetic Ingredients (INCI) among the 342 chemicals. Although specificity was low with the battery system, sensitivity and concordance were high. These results suggest that the battery system consisting of DEREK NEXUS and ADMEWorks is useful for prediction of genotoxic potential of chemicals, including cosmetic ingredients.

Crohn's Disease and Ulcerative Colitis: A Guide for Parents

MedlinePlus

... for cures; participate in a clinical trial of experimental treatments. Interactive Disease Tracker Use GI Buddy to ... to target them and block inflammation. With many experimental treatments for IBD in clinical trials, experts predict ...

Prompt comprehension in UNIX command production.

PubMed

Doane, S M; McNamara, D S; Kintsch, W; Polson, P G; Clawson, D M

1992-07-01

We hypothesize that a cognitive analysis based on the construction-integration theory of comprehension (Kintsch, 1988) can predict what is difficult about generating complex composite commands in the UNIX operating system. We provide empirical support for assumptions of the Doane, Kintsch, and Polson (1989, 1990) construction-integration model for generating complex commands in UNIX. We asked users whose UNIX experience varied to produce complex UNIX commands, and then provided help prompts whenever the commands that they produced were erroneous. The help prompts were designed to assist subjects with respect to both the knowledge and the memory processes that our UNIX modeling efforts have suggested are lacking in less expert users. It appears that experts respond to different prompts than do novices. Expert performance is helped by the presentation of abstract information, whereas novice and intermediate performance is modified by presentation of concrete information. Second, while presentation of specific prompts helps less expert subjects, they do not provide sufficient information to obtain correct performance. Our analyses suggest that information about the ordering of commands is required to help the less expert with both knowledge and memory load problems in a manner consistent with skill acquisition theories.

An expert system for water quality modelling.

PubMed

Booty, W G; Lam, D C; Bobba, A G; Wong, I; Kay, D; Kerby, J P; Bowen, G S

1992-12-01

The RAISON-micro (Regional Analysis by Intelligent System ON a micro-computer) expert system is being used to predict the effects of mine effluents on receiving waters in Ontario. The potential of this system to assist regulatory agencies and mining industries to define more acceptable effluent limits was shown in an initial study. This system has been further developed so that the expert system helps the model user choose the most appropriate model for a particular application from a hierarchy of models. The system currently contains seven models which range from steady state to time dependent models, for both conservative and nonconservative substances in rivers and lakes. The menu driven expert system prompts the model user for information such as the nature of the receiving water system, the type of effluent being considered, and the range of background data available for use as input to the models. The system can also be used to determine the nature of the environmental conditions at the site which are not available in the textual information database, such as the components of river flow. Applications of the water quality expert system are presented for representative mine sites in the Timmins area of Ontario.

Wishful Thinking? Inside the Black Box of Exposure Assessment.

PubMed

Money, Annemarie; Robinson, Christine; Agius, Raymond; de Vocht, Frank

2016-05-01

Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts' assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the 'black box' of exposure assessment. A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; 'intensity'; 'probability'; 'agent'; 'process'; and 'duration' of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment. © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Expert diagnosis of plus disease in retinopathy of prematurity from computer-based image analysis

PubMed Central

Campbell, J. Peter; Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir N.; Reynolds, James D.; Horowitz, Jason; Hutcheson, Kelly; Shapiro, Michael; Repka, Michael X.; Ferrone, Phillip; Drenser, Kimberly; Martinez-Castellanos, Maria Ana; Ostmo, Susan; Jonas, Karyn; Chan, R.V. Paul; Chiang, Michael F.

2016-01-01

Importance Published definitions of “plus disease” in retinopathy of prematurity (ROP) reference arterial tortuosity and venous dilation within the posterior pole based on a standard published photograph. One possible explanation for limited inter-expert reliability for plus disease diagnosis is that experts deviate from the published definitions. Objective To identify vascular features used by experts for diagnosis of plus disease through quantitative image analysis. Design We developed a computer-based image analysis system (Imaging and Informatics in ROP, i-ROP), and trained the system to classify images compared to a reference standard diagnosis (RSD). System performance was analyzed as a function of the field of view (circular crops 1–6 disc diameters [DD] radius) and vessel subtype (arteries only, veins only, or all vessels). The RSD was compared to the majority diagnosis of experts. Setting Routine ROP screening in neonatal intensive care units at 8 academic institutions. Participants A set of 77 digital fundus images was used to develop the i-ROP system. A subset of 73 images was independently classified by 11 ROP experts for validation. Main Outcome Measures The primary outcome measure was the percentage accuracy of i-ROP system classification of plus disease with the RSD as a function of field-of-view and vessel type. Secondary outcome measures included the accuracy of the 11 experts compared to the RSD. Results Accuracy of plus disease diagnosis by the i-ROP computer based system was highest (95%, confidence interval [CI] 94 – 95%) when it incorporated vascular tortuosity from both arteries and veins, and with the widest field of view (6 disc diameter radius). Accuracy was ≤90% when using only arterial tortuosity (P<0.001), and ≤85% using a 2–3 disc diameter view similar to the standard published photograph (p<0.001). Diagnostic accuracy of the i-ROP system (95%) was comparable to that of 11 expert clinicians (79–99%). Conclusions and Relevance ROP experts appear to consider findings from beyond the posterior retina when diagnosing plus disease, and consider tortuosity of both arteries and veins, in contrast to published definitions. It is feasible for a computer-based image analysis system to perform comparably to ROP experts, using manually segmented images. PMID:27077667

Evaluation of proposed casemix criteria as a basis for costing patients in the adult general intensive care unit.

PubMed

Stevens, V G; Hibbert, C L; Edbrooke, D L

1998-10-01

This study analyses the relationship between the actual patient-related costs of care calculated for 145 patients admitted sequentially to an adult general intensive care unit and a number of factors obtained from a previously described consensus of opinion study. The factors identified in the study were suggested as potential descriptors for the casemix in an intensive care unit that could be used to predict the costs of care. Significant correlations between the costs of care and severity of illness, workload and length of stay were found but these failed to predict the costs of care with sufficient accuracy to be used in isolation to define isoresource groups in the intensive care unit. No associations between intensive care unit mortality, reason for admission and intensive and unit treatments and costs of care were found. Based on these results, it seems that casemix descriptors and isoresource groups for the intensive care unit that would allow costs to be predicted cannot be defined in terms of single factors.

[Fire behavior of ground surface fuels in Pinus koraiensis and Quercus mongolica mixed forest under no wind and zero slope condition: a prediction with extended Rothermel model].

PubMed

Zhang, Ji-Li; Liu, Bo-Fei; Chu, Teng-Fei; Di, Xue-Ying; Jin, Sen

2012-06-01

A laboratory burning experiment was conducted to measure the fire spread speed, residual time, reaction intensity, fireline intensity, and flame length of the ground surface fuels collected from a Korean pine (Pinus koraiensis) and Mongolian oak (Quercus mongolica) mixed stand in Maoer Mountains of Northeast China under the conditions of no wind, zero slope, and different moisture content, load, and mixture ratio of the fuels. The results measured were compared with those predicted by the extended Rothermel model to test the performance of the model, especially for the effects of two different weighting methods on the fire behavior modeling of the mixed fuels. With the prediction of the model, the mean absolute errors of the fire spread speed and reaction intensity of the fuels were 0.04 m X min(-1) and 77 kW X m(-2), their mean relative errors were 16% and 22%, while the mean absolute errors of residual time, fireline intensity and flame length were 15.5 s, 17.3 kW X m(-1), and 9.7 cm, and their mean relative errors were 55.5%, 48.7%, and 24%, respectively, indicating that the predicted values of residual time, fireline intensity, and flame length were lower than the observed ones. These errors could be regarded as the lower limits for the application of the extended Rothermel model in predicting the fire behavior of similar fuel types, and provide valuable information for using the model to predict the fire behavior under the similar field conditions. As a whole, the two different weighting methods did not show significant difference in predicting the fire behavior of the mixed fuels by extended Rothermel model. When the proportion of Korean pine fuels was lower, the predicted values of spread speed and reaction intensity obtained by surface area weighting method and those of fireline intensity and flame length obtained by load weighting method were higher; when the proportion of Korean pine needles was higher, the contrary results were obtained.

Experimental evaluation of models for predicting Cherenkov light intensities from short-cooled nuclear fuel assemblies

NASA Astrophysics Data System (ADS)

Branger, E.; Grape, S.; Jansson, P.; Jacobsson Svärd, S.

2018-02-01

The Digital Cherenkov Viewing Device (DCVD) is a tool used by nuclear safeguards inspectors to verify irradiated nuclear fuel assemblies in wet storage based on the recording of Cherenkov light produced by the assemblies. One type of verification involves comparing the measured light intensity from an assembly with a predicted intensity, based on assembly declarations. Crucial for such analyses is the performance of the prediction model used, and recently new modelling methods have been introduced to allow for enhanced prediction capabilities by taking the irradiation history into account, and by including the cross-talk radiation from neighbouring assemblies in the predictions. In this work, the performance of three models for Cherenkov-light intensity prediction is evaluated by applying them to a set of short-cooled PWR 17x17 assemblies for which experimental DCVD measurements and operator-declared irradiation data was available; (1) a two-parameter model, based on total burnup and cooling time, previously used by the safeguards inspectors, (2) a newly introduced gamma-spectrum-based model, which incorporates cycle-wise burnup histories, and (3) the latter gamma-spectrum-based model with the addition to account for contributions from neighbouring assemblies. The results show that the two gamma-spectrum-based models provide significantly higher precision for the measured inventory compared to the two-parameter model, lowering the standard deviation between relative measured and predicted intensities from 15.2 % to 8.1 % respectively 7.8 %. The results show some systematic differences between assemblies of different designs (produced by different manufacturers) in spite of their similar PWR 17x17 geometries, and possible ways are discussed to address such differences, which may allow for even higher prediction capabilities. Still, it is concluded that the gamma-spectrum-based models enable confident verification of the fuel assembly inventory at the currently used detection limit for partial defects, being a 30 % discrepancy between measured and predicted intensities, while some false detection occurs with the two-parameter model. The results also indicate that the gamma-spectrum-based prediction methods are accurate enough that the 30 % discrepancy limit could potentially be lowered.

Knowledge exchange for climate adaptation planning in western North America

NASA Astrophysics Data System (ADS)

Garfin, Gregg; Orr, Barron

2015-04-01

In western North America, the combination of sustained drought, rapid ecosystem changes, and land use changes associated with urban population growth has motivated concern among ecosystem managers about the implications of future climate changes for the landscapes which they manage. Through literature review, surveys, and workshop discussions, we assess the process of moving from concern, to planning, to action, with an emphasis on questions, such as: What are the roles of boundary organizations in facilitating knowledge exchange? Which practices lead to effective interactions between scientists, decision-makers, and knowledge brokers? While there is no "one size fits all" science communication method, the co-production of science and policy by research scientists, science translators, and decision-makers, as co-equals, is a resource intensive, but effective practice for moving adaptation planning forward. Constructive approaches make use of alliances with early adopters and opinion leaders, and make strong communication links between predictions, impacts and solutions. Resource managers need information on the basics of regional climate variability and global climate change, region-specific projections of climate changes and impacts, frank discussion of uncertainties, and opportunities for candid exploration of these topics with peers and subject experts. Research scientists play critical roles in adaptation planning discussions, because they assist resource managers in clarifying the cascade of interactions leading to potential impacts and, importantly, because decision-makers want to hear the information straight from the scientists conducting the research, which bolsters credibility. We find that uncertainty, formerly a topic to avoided, forms the foundation for constructive progress in adaptation planning. Candid exploration of the array of uncertainties, including those due to modeling, institutional, policy and economic factors, with practitioners, science translators, and subject experts, stimulates constructive thinking on adaptation strategies. Discussion support to explore multiple future scenarios and research nuances advances the discussion beyond "uncertainty paralysis."

Motivation and emotion predict medical students' attention to computer-based feedback.

PubMed

Naismith, Laura M; Lajoie, Susanne P

2017-12-14

Students cannot learn from feedback unless they pay attention to it. This study investigated relationships between the personal factors of achievement goal orientations, achievement emotions, and attention to feedback in BioWorld, a computer environment for learning clinical reasoning. Novice medical students (N = 28) completed questionnaires to measure their achievement goal orientations and then thought aloud while solving three endocrinology patient cases and reviewing corresponding expert solutions. Questionnaires administered after each case measured participants' experiences of five feedback emotions: pride, relief, joy, shame, and anger. Attention to individual text segments of the expert solutions was modelled using logistic regression and the method of generalized estimating equations. Participants did not attend to all of the feedback that was available to them. Performance-avoidance goals and shame positively predicted attention to feedback, and performance-approach goals and relief negatively predicted attention to feedback. Aspects of how the feedback was displayed also influenced participants' attention. Findings are discussed in terms of their implications for educational theory as well as the design and use of computer learning environments in medical education.

Intelligent instrumentation applied in environment management

NASA Astrophysics Data System (ADS)

Magheti, Mihnea I.; Walsh, Patrick; Delassus, Patrick

2005-06-01

The use of information and communications technology in environment management and research has witnessed a renaissance in recent years. From optical sensor technology, expert systems, GIS and communications technologies to computer aided harvesting and yield prediction, these systems are increasable used for applications developing in the management sector of natural resources and biodiversity. This paper presents an environmental decision support system, used to monitor biodiversity and present a risk rating for the invasion of pests into the particular systems being examined. This system will utilise expert mobile technology coupled with artificial intelligence and predictive modelling, and will emphasize the potential for expansion into many areas of intelligent remote sensing and computer aided decision-making for environment management or certification. Monitoring and prediction in natural systems, harnessing the potential of computing and communication technologies is an emerging technology within the area of environmental management. This research will lead to the initiation of a hardware and software multi tier decision support system for environment management allowing an evaluation of areas for biodiversity or areas at risk from invasive species, based upon environmental factors/systems.

Critical thinking traits of top-tier experts and implications for computer science education

NASA Astrophysics Data System (ADS)

Bushey, Dean E.

A documented shortage of technical leadership and top-tier performers in computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling. The decline is "a quiet crisis building in the United States," a crisis that, if allowed to continue unchecked, could endanger America's well-being and preeminence among the world's nations. Past research on expert performance has shown that the cognitive traits of critical thinking, creativity, and problem solving possessed by top-tier performers can be identified, observed and measured. The studies show that the identified attributes are applicable across many domains and disciplines. Companies have begun to realize that cognitive skills are important for high-level performance and are reevaluating the traditional academic standards they have used to predict success for their top-tier performers in computer science. Previous research in the computer science field has focused either on programming skills of its experts or has attempted to predict the academic success of students at the undergraduate level. This study, on the other hand, examines the critical-thinking skills found among experts in the computer science field in order to explore the questions, "What cognitive skills do outstanding performers possess that make them successful?" and "How do currently used measures of academic performance correlate to critical-thinking skills among students?" The results of this study suggest a need to examine how critical-thinking abilities are learned in the undergraduate computer science curriculum and the need to foster these abilities in order to produce the high-level, critical-thinking professionals necessary to fill the growing need for these experts. Due to the fact that current measures of academic performance do not adequately depict students' cognitive abilities, assessment of these skills must be incorporated into existing curricula.

Predicting dynamic range and intensity discrimination for electrical pulse-train stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

PubMed

Xu, Yifang; Collins, Leslie M

2005-06-01

This work investigates dynamic range and intensity discrimination for electrical pulse-train stimuli that are modulated by noise using a stochastic auditory nerve model. Based on a hypothesized monotonic relationship between loudness and the number of spikes elicited by a stimulus, theoretical prediction of the uncomfortable level has previously been determined by comparing spike counts to a fixed threshold, Nucl. However, no specific rule for determining Nucl has been suggested. Our work determines the uncomfortable level based on the excitation pattern of the neural response in a normal ear. The number of fibers corresponding to the portion of the basilar membrane driven by a stimulus at an uncomfortable level in a normal ear is related to Nucl at an uncomfortable level of the electrical stimulus. Intensity discrimination limens are predicted using signal detection theory via the probability mass function of the neural response and via experimental simulations. The results show that the uncomfortable level for pulse-train stimuli increases slightly as noise level increases. Combining this with our previous threshold predictions, we hypothesize that the dynamic range for noise-modulated pulse-train stimuli should increase with additive noise. However, since our predictions indicate that intensity discrimination under noise degrades, overall intensity coding performance may not improve significantly.

Observed Emotions as Predictors of Quality of Kindergartners’ Social Relationships

PubMed Central

Hernández, Maciel M.; Eisenberg, Nancy; Valiente, Carlos; Spinrad, Tracy L.; VanSchyndel, Sarah K.; Diaz, Anjolii; Silva, Kassondra M.; Berger, Rebecca H.; Southworth, Jody

2018-01-01

This study evaluated whether positive and anger emotional frequency (the proportion of instances an emotion was observed) and intensity (the strength of an emotion when it was observed) uniquely predicted social relationships among kindergarteners (N = 301). Emotions were observed as naturally occurring at school in the fall term and multiple reporters (peers and teachers) provided information on quality of relationships with children in the spring term. In structural equation models, positive emotion frequency, but not positive emotion intensity, was positively related to peer acceptance and negatively related to peer rejection. In contrast, the frequency of anger provided unique positive prediction of teacher–student conflict and negative prediction of peer acceptance. Furthermore, anger intensity negatively predicted teacher–student closeness and positively predicted teacher–student conflict. Implications for promoting social relationships in school are discussed. PMID:29861553

Developing Expert Systems

DOT National Transportation Integrated Search

1974-10-01

The basic manual, published as the first volume of this report, is intended for use as a tool in predicting noise levels which will be generated by freely-flowing vehicle traffic along a highway of known characteristics. The first volume explains the...

Ontology-based tools to expedite predictive model construction.

PubMed

Haug, Peter; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Ferraro, Jeffrey

2014-01-01

Large amounts of medical data are collected electronically during the course of caring for patients using modern medical information systems. This data presents an opportunity to develop clinically useful tools through data mining and observational research studies. However, the work necessary to make sense of this data and to integrate it into a research initiative can require substantial effort from medical experts as well as from experts in medical terminology, data extraction, and data analysis. This slows the process of medical research. To reduce the effort required for the construction of computable, diagnostic predictive models, we have developed a system that hybridizes a medical ontology with a large clinical data warehouse. Here we describe components of this system designed to automate the development of preliminary diagnostic models and to provide visual clues that can assist the researcher in planning for further analysis of the data behind these models.

Feared consequences of panic attacks in panic disorder: a qualitative and quantitative analysis.

PubMed

Raffa, Susan D; White, Kamila S; Barlow, David H

2004-01-01

Cognitions are hypothesized to play a central role in panic disorder (PD). Previous studies have used questionnaires to assess cognitive content, focusing on prototypical cognitions associated with PD; however, few studies have qualitatively examined cognitions associated with the feared consequences of panic attacks. The purpose of this study was to conduct a qualitative and quantitative analysis of feared consequences of panic attacks. The initial, qualitative analysis resulted in the development of 32 categories of feared consequences. The categories were derived from participant responses to a standardized, semi-structured question (n = 207). Five expert-derived categories were then utilized to quantitatively examine the relationship between cognitions and indicators of PD severity. Cognitions did not predict PD severity; however, correlational analyses indicated some predictive validity to the expert-derived categories. The qualitative analysis identified additional areas of patient-reported concern not included in previous research that may be important in the assessment and treatment of PD.

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

International AIDS Society global scientific strategy: towards an HIV cure 2016.

PubMed

Deeks, Steven G; Lewin, Sharon R; Ross, Anna Laura; Ananworanich, Jintanat; Benkirane, Monsef; Cannon, Paula; Chomont, Nicolas; Douek, Daniel; Lifson, Jeffrey D; Lo, Ying-Ru; Kuritzkes, Daniel; Margolis, David; Mellors, John; Persaud, Deborah; Tucker, Joseph D; Barre-Sinoussi, Françoise; Alter, Galit; Auerbach, Judith; Autran, Brigitte; Barouch, Dan H; Behrens, Georg; Cavazzana, Marina; Chen, Zhiwei; Cohen, Éric A; Corbelli, Giulio Maria; Eholié, Serge; Eyal, Nir; Fidler, Sarah; Garcia, Laurindo; Grossman, Cynthia; Henderson, Gail; Henrich, Timothy J; Jefferys, Richard; Kiem, Hans-Peter; McCune, Joseph; Moodley, Keymanthri; Newman, Peter A; Nijhuis, Monique; Nsubuga, Moses Supercharger; Ott, Melanie; Palmer, Sarah; Richman, Douglas; Saez-Cirion, Asier; Sharp, Matthew; Siliciano, Janet; Silvestri, Guido; Singh, Jerome; Spire, Bruno; Taylor, Jeffrey; Tolstrup, Martin; Valente, Susana; van Lunzen, Jan; Walensky, Rochelle; Wilson, Ira; Zack, Jerome

2016-08-01

Antiretroviral therapy is not curative. Given the challenges in providing lifelong therapy to a global population of more than 35 million people living with HIV, there is intense interest in developing a cure for HIV infection. The International AIDS Society convened a group of international experts to develop a scientific strategy for research towards an HIV cure. This Perspective summarizes the group's strategy.

The Actions of One Inspire the Power of Many: Laura Briley, Day Schools, Tulsa, Oklahoma

ERIC Educational Resources Information Center

Gonzalez-Mena, Janet

2010-01-01

Laura Briley is a person who makes things happen! Not only is she instrumental in creating a new World Forum Working Group for the Rights of Children in Children's Homes, but in April she organized the first ever Pikler Intensive Training in the United States by bringing two internationally famous infant development experts to Tulsa, Oklahoma. In…

SpikeGUI: software for rapid interictal discharge annotation via template matching and online machine learning.

PubMed

Jing Jin; Dauwels, Justin; Cash, Sydney; Westover, M Brandon

2014-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface "SpikeGUI" was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. "SpikeGUI" substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types.

SpikeGUI: Software for Rapid Interictal Discharge Annotation via Template Matching and Online Machine Learning

PubMed Central

Jin, Jing; Dauwels, Justin; Cash, Sydney; Westover, M. Brandon

2015-01-01

Detection of interictal discharges is a key element of interpreting EEGs during the diagnosis and management of epilepsy. Because interpretation of clinical EEG data is time-intensive and reliant on experts who are in short supply, there is a great need for automated spike detectors. However, attempts to develop general-purpose spike detectors have so far been severely limited by a lack of expert-annotated data. Huge databases of interictal discharges are therefore in great demand for the development of general-purpose detectors. Detailed manual annotation of interictal discharges is time consuming, which severely limits the willingness of experts to participate. To address such problems, a graphical user interface “SpikeGUI” was developed in our work for the purposes of EEG viewing and rapid interictal discharge annotation. “SpikeGUI” substantially speeds up the task of annotating interictal discharges using a custom-built algorithm based on a combination of template matching and online machine learning techniques. While the algorithm is currently tailored to annotation of interictal epileptiform discharges, it can easily be generalized to other waveforms and signal types. PMID:25570976

Balance, Sensorimotor, and Cognitive Performance in Long-Year Expert Senior Ballroom Dancers

PubMed Central

Kattenstroth, Jan-Christoph; Kalisch, Tobias; Kolankowska, Izabela; Dinse, Hubert R.

2011-01-01

Physical fitness is considered a major factor contributing to the maintenance of independent living and everyday competence. In line with this notion, it has been shown that several years of amateur dancing experience can exert beneficial effects not only on balance and posture but also on tactile, motor, and cognitive functions in older people. This raises the question of whether an even more extensive schedule of dancing, including competitive tournaments, would further enhance these positive effects. We therefore assessed posture, balance, and reaction times, as well as motor, tactile, and cognitive performance in older expert ballroom dancers with several years of competitive experience. We found substantially better performance in the expert group than in the controls in terms of expertise-related domains like posture, balance, and reaction times. However, there was no generalization of positive effects to those domains that were found to be improved in amateur dancers, such as tactile and cognitive performance, suggesting that there might be an optimal range of intervention intensity to maintain health and independence throughout the human lifespan. PMID:21961064

New quality assurance program integrating "modern radiotherapy" within the German Hodgkin Study Group.

PubMed

Kriz, J; Baues, C; Engenhart-Cabillic, R; Haverkamp, U; Herfarth, K; Lukas, P; Schmidberger, H; Marnitz-Schulze, S; Fuchs, M; Engert, A; Eich, H T

2017-02-01

Field design changed substantially from extended-field RT (EF-RT) to involved-field RT (IF-RT) and now to involved-node RT (IN-RT) and involved-site RT (IS-RT) as well as treatment techniques in radiotherapy (RT) of Hodgkin's lymphoma (HL). The purpose of this article is to demonstrate the establishment of a quality assurance program (QAP) including modern RT techniques and field designs within the German Hodgkin Study Group (GHSG). In the era of modern conformal RT, this QAP had to be fundamentally adapted and a new evaluation process has been intensively discussed by the radiotherapeutic expert panel of the GHSG. The expert panel developed guidelines and criteria to analyse "modern" field designs and treatment techniques. This work is based on a dataset of 11 patients treated within the sixth study generation (HD16-17). To develop a QAP of "modern RT", the expert panel defined criteria for analysing current RT procedures. The consensus of a modified QAP in ongoing and future trials is presented. With this schedule, the QAP of the GHSG could serve as a model for other study groups.

Knowledge-Based, Interactive, Custom Anatomical Scene Creation for Medical Education: The Biolucida System

PubMed Central

Warren, Wayne; Brinkley, James F.

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity. PMID:16779148

Knowledge-based, interactive, custom anatomical scene creation for medical education: the Biolucida system.

PubMed

Warren, Wayne; Brinkley, James F

2005-01-01

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity.

Individual and Joint Expert Judgments as Reference Standards in Artifact Detection

PubMed Central

Verduijn, Marion; Peek, Niels; de Keizer, Nicolette F.; van Lieshout, Erik-Jan; de Pont, Anne-Cornelie J.M.; Schultz, Marcus J.; de Jonge, Evert; de Mol, Bas A.J.M.

2008-01-01

Objective To investigate the agreement among clinical experts in their judgments of monitoring data with respect to artifacts, and to examine the effect of reference standards that consist of individual and joint expert judgments on the performance of artifact filters. Design Individual judgments of four physicians, a majority vote judgment, and a consensus judgment were obtained for 30 time series of three monitoring variables: mean arterial blood pressure (ABPm), central venous pressure (CVP), and heart rate (HR). The individual and joint judgments were used to tune three existing automated filtering methods and to evaluate the performance of the resulting filters. Measurements The interrater agreement was calculated in terms of positive specific agreement (PSA). The performance of the artifact filters was quantified in terms of sensitivity and positive predictive value (PPV). Results PSA values between 0.33 and 0.85 were observed among clinical experts in their selection of artifacts, with relatively high values for CVP data. Artifact filters developed using judgments of individual experts were found to moderately generalize to new time series and other experts; sensitivity values ranged from 0.40 to 0.60 for ABPm and HR filters (PPV: 0.57–0.84), and from 0.63 to 0.80 for CVP filters (PPV: 0.71–0.86). A higher performance value for the filters was found for the three variable types when joint judgments were used for tuning the filtering methods. Conclusion Given the disagreement among experts in their individual judgment of monitoring data with respect to artifacts, the use of joint reference standards obtained from multiple experts is recommended for development of automatic artifact filters. PMID:18096912

Earlier Visual N1 Latencies in Expert Video-Game Players: A Temporal Basis of Enhanced Visuospatial Performance?

PubMed Central

Latham, Andrew J.; Patston, Lucy L. M.; Westermann, Christine; Kirk, Ian J.; Tippett, Lynette J.

2013-01-01

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction. PMID:24058667

Earlier visual N1 latencies in expert video-game players: a temporal basis of enhanced visuospatial performance?

PubMed

Latham, Andrew J; Patston, Lucy L M; Westermann, Christine; Kirk, Ian J; Tippett, Lynette J

2013-01-01

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction.

Expert opinion on landslide susceptibility elicted by probabilistic inversion from scenario rankings

NASA Astrophysics Data System (ADS)

Lee, Katy; Dashwood, Claire; Lark, Murray

2016-04-01

For many natural hazards the opinion of experts, with experience in assessing susceptibility under different circumstances, is a valuable source of information on which to base risk assessments. This is particularly important where incomplete process understanding, and limited data, limit the scope to predict susceptibility by mechanistic or statistical modelling. The expert has a tacit model of a system, based on their understanding of processes and their field experience. This model may vary in quality, depending on the experience of the expert. There is considerable interest in how one may elicit expert understanding by a process which is transparent and robust, to provide a basis for decision support. One approach is to provide experts with a set of scenarios, and then to ask them to rank small overlapping subsets of these with respect to susceptibility. Methods of probabilistic inversion have been used to compute susceptibility scores for each scenario, implicit in the expert ranking. It is also possible to model these scores as functions of measurable properties of the scenarios. This approach has been used to assess susceptibility of animal populations to invasive diseases, to assess risk to vulnerable marine environments and to assess the risk in hypothetical novel technologies for food production. We will present the results of a study in which a group of geologists with varying degrees of expertise in assessing landslide hazards were asked to rank sets of hypothetical simplified scenarios with respect to land slide susceptibility. We examine the consistency of their rankings and the importance of different properties of the scenarios in the tacit susceptibility model that their rankings implied. Our results suggest that this is a promising approach to the problem of how experts can communicate their tacit model of uncertain systems to those who want to make use of their expertise.

Heart rate during basketball game play and volleyball drills accurately predicts oxygen uptake and energy expenditure.

PubMed

Scribbans, T D; Berg, K; Narazaki, K; Janssen, I; Gurd, B J

2015-09-01

There is currently little information regarding the ability of metabolic prediction equations to accurately predict oxygen uptake and exercise intensity from heart rate (HR) during intermittent sport. The purpose of the present study was to develop and, cross-validate equations appropriate for accurately predicting oxygen cost (VO2) and energy expenditure from HR during intermittent sport participation. Eleven healthy adult males (19.9±1.1yrs) were recruited to establish the relationship between %VO2peak and %HRmax during low-intensity steady state endurance (END), moderate-intensity interval (MOD) and high intensity-interval exercise (HI), as performed on a cycle ergometer. Three equations (END, MOD, and HI) for predicting %VO2peak based on %HRmax were developed. HR and VO2 were directly measured during basketball games (6 male, 20.8±1.0 yrs; 6 female, 20.0±1.3yrs) and volleyball drills (12 female; 20.8±1.0yrs). Comparisons were made between measured and predicted VO2 and energy expenditure using the 3 equations developed and 2 previously published equations. The END and MOD equations accurately predicted VO2 and energy expenditure, while the HI equation underestimated, and the previously published equations systematically overestimated VO2 and energy expenditure. Intermittent sport VO2 and energy expenditure can be accurately predicted from heart rate data using either the END (%VO2peak=%HRmax x 1.008-17.17) or MOD (%VO2peak=%HRmax x 1.2-32) equations. These 2 simple equations provide an accessible and cost-effective method for accurate estimation of exercise intensity and energy expenditure during intermittent sport.

A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment

PubMed Central

Chadès, Iadine

2017-01-01

Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection. PMID:28686651

A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

PubMed

Nicol, Sam; Chadès, Iadine

2017-01-01

Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.

Medicine is not science: guessing the future, predicting the past.

PubMed

Miller, Clifford

2014-12-01

Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. Irregularity and its consequences for knowledge are considered. Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is outlined. Reducing irregularity and/or increasing regularity can increase the reliability of knowledge. Beyond long experience and specialization, improvements include implementing supporting knowledge systems of libraries of appropriately classified prior cases and clinical histories and education about expertise, intuition and professional judgement. A consequence of irregularity and complexity is that classical reductionist science cannot provide reliable predictions of the behaviour of complex systems found in nature, including of the human body. Expertise, expert judgement and their exercise appear overarching. Diagnosis involves predicting the past will recur in the current patient applying expertise and intuition from knowledge and experience of previous cases and probabilistic medical theory. Treatment decisions are an educated guess about the future (prognosis). Benefits of the improvements suggested here are likely in fields where paucity of feedback for practitioners limits development of reliable expert diagnostic intuition. Further analysis, definition and classification of irregularity is appropriate. Observing and recording irregularities are initial steps in developing irregularity theory to improve the reliability and extent of knowledge, albeit some forms of irregularity present inherent difficulties. © 2014 John Wiley & Sons, Ltd.

Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.

PubMed

Achuthan, Anusha; Rajeswari, Mandava; Ramachandram, Dhanesh; Aziz, Mohd Ezane; Shuaib, Ibrahim Lutfi

2010-07-01

This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region information. The wavelet energy is embedded into a level set model to formulate the segmentation model called wavelet energy-guided level set-based active contour (WELSAC). The WELSAC model is evaluated using several synthetic and CT images focusing on tumour cases, which contain regions demonstrating the characteristics of intra-region intensity variations and having high similarity in intensity distributions with the adjacent regions. The obtained results show that the proposed WELSAC model is able to segment regions of interest in close correspondence with the manual delineation provided by the medical experts and to provide a solution for tumour detection. Copyright 2010 Elsevier Ltd. All rights reserved.

Study to validate the outcome goal, competencies and educational objectives for use in intensive care orientation programs.

PubMed

Boyle, M; Butcher, R; Kenney, C

1998-03-01

Intensive care orientation programs have become an accepted component of intensive care education. To date, however, there have been no Australian-based standards defining the appropriate level of competence to be attained upon completion of orientation. The aim of this study was to validate a set of aims, competencies and educational objectives that could form the basis of intensive care orientation and which would ensure an outcome standard of safe and effective practice. An initial document containing a statement of the desired outcome goal, six competency statements and 182 educational objectives was developed through a review of the orientation programs developed by the investigators. The Delphi technique was used to gain consensus among 13 nurses recognised for their expertise in intensive care education. The expert group rated the acceptability of each of the study items and provided suggestions for objectives to be included. An approval rating of 80 per cent was required to retain each of the study items, with the document refined through three Delphi rounds. The final document contains a validated statement of outcome goal, competencies and educational objectives for intensive care orientation programs.

Observational study of treatment space in individual neonatal cot spaces.

PubMed

Hignett, Sue; Lu, Jun; Fray, Mike

2010-01-01

Technology developments in neonatal intensive care units have increased the spatial requirements for clinical activities. Because the effectiveness of healthcare delivery is determined in part by the design of the physical environment and the spatial organization of work, it is appropriate to apply an evidence-based approach to architectural design. This study aimed to provide empirical evidence of the spatial requirements for an individual cot or incubator space. Observational data from 2 simulation exercises were combined with an expert review to produce a final recommendation. A validated 5-step protocol was used to collect data. Step 1 defined the clinical specialty and space. In step 2, data were collected with 28 staff members and 15 neonates to produce a simulation scenario representing the frequent and safety-critical activities. In step 3, 21 staff members participated in functional space experiments to determine the average spatial requirements. Step 4 incorporated additional data (eg, storage and circulation) to produce a spatial recommendation. Finally, the recommendation was reviewed in step 5 by a national expert clinical panel to consider alternative layouts and technology. The average space requirement for an individual neonatal intensive care unit cot (incubator) space was 13.5 m2 (or 145.3 ft2). The circulation and storage space requirements added in step 4 increased this to 18.46 m2 (or 198.7 ft2). The expert panel reviewed the recommendation and agreed that the average individual cot space (13.5 m2/[or 145.3 ft2]) would accommodate variance in working practices. Care needs to be taken when extrapolating this recommendation to multiple cot areas to maintain the minimum spatial requirement.

Leg pain and psychological variables predict outcome 2-3 years after lumbar fusion surgery.

PubMed

Abbott, Allan D; Tyni-Lenné, Raija; Hedlund, Rune

2011-10-01

Prediction studies testing a thorough range of psychological variables in addition to demographic, work-related and clinical variables are lacking in lumbar fusion surgery research. This prospective cohort study aimed at examining predictions of functional disability, back pain and health-related quality of life (HRQOL) 2-3 years after lumbar fusion by regressing nonlinear relations in a multivariate predictive model of pre-surgical variables. Before and 2-3 years after lumbar fusion surgery, patients completed measures investigating demographics, work-related variables, clinical variables, functional self-efficacy, outcome expectancy, fear of movement/(re)injury, mental health and pain coping. Categorical regression with optimal scaling transformation, elastic net regularization and bootstrapping were used to investigate predictor variables and address predictive model validity. The most parsimonious and stable subset of pre-surgical predictor variables explained 41.6, 36.0 and 25.6% of the variance in functional disability, back pain intensity and HRQOL 2-3 years after lumbar fusion. Pre-surgical control over pain significantly predicted functional disability and HRQOL. Pre-surgical catastrophizing and leg pain intensity significantly predicted functional disability and back pain while the pre-surgical straight leg raise significantly predicted back pain. Post-operative psychomotor therapy also significantly predicted functional disability while pre-surgical outcome expectations significantly predicted HRQOL. For the median dichotomised classification of functional disability, back pain intensity and HRQOL levels 2-3 years post-surgery, the discriminative ability of the prediction models was of good quality. The results demonstrate the importance of pre-surgical psychological factors, leg pain intensity, straight leg raise and post-operative psychomotor therapy in the predictions of functional disability, back pain and HRQOL-related outcomes.

Developments in REDES: The rocket engine design expert system

NASA Technical Reports Server (NTRS)

Davidian, Kenneth O.

1990-01-01

The Rocket Engine Design Expert System (REDES) is being developed at the NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP, a nozzle design program named RAO, a regenerative cooling channel performance evaluation code named RTE, and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES is built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

Developments in REDES: The Rocket Engine Design Expert System

NASA Technical Reports Server (NTRS)

Davidian, Kenneth O.

1990-01-01

The Rocket Engine Design Expert System (REDES) was developed at NASA-Lewis to collect, automate, and perpetuate the existing expertise of performing a comprehensive rocket engine analysis and design. Currently, REDES uses the rigorous JANNAF methodology to analyze the performance of the thrust chamber and perform computational studies of liquid rocket engine problems. The following computer codes were included in REDES: a gas properties program named GASP; a nozzle design program named RAO; a regenerative cooling channel performance evaluation code named RTE; and the JANNAF standard liquid rocket engine performance prediction code TDK (including performance evaluation modules ODE, ODK, TDE, TDK, and BLM). Computational analyses are being conducted by REDES to provide solutions to liquid rocket engine thrust chamber problems. REDES was built in the Knowledge Engineering Environment (KEE) expert system shell and runs on a Sun 4/110 computer.

An expert system-based approach to prediction of year-to-year climatic variations in the North Atlantic region

NASA Astrophysics Data System (ADS)

Rodionov, S. N.; Martin, J. H.

1999-07-01

A novel approach to climate forecasting on an interannual time scale is described. The approach is based on concepts and techniques from artificial intelligence and expert systems. The suitability of this approach to climate diagnostics and forecasting problems and its advantages compared with conventional forecasting techniques are discussed. The article highlights some practical aspects of the development of climatic expert systems (CESs) and describes an implementation of such a system for the North Atlantic (CESNA). Particular attention is paid to the content of CESNA's knowledge base and those conditions that make climatic forecasts one to several years in advance possible. A detailed evaluation of the quality of the experimental real-time forecasts made by CESNA for the winters of 1995-1996, 1996-1997 and 1997-1998 are presented.

[Systematic detection of physical child abuse at emergency rooms].

PubMed

Sittig, J S; Uiterwaal, C S P M; Moons, K G M; Russel, I M B; Nievelstein, R A J; Nieuwenhuis, E E S; van de Putte, E M

2016-01-01

The aim of our diagnostic accuracy study Child Abuse Inventory at Emergency Rooms (CHAIN-ER) was to establish whether a widely used checklist accurately detects or excludes physical abuse among children presenting to ERs with physical injury. A large multicentre study with a 6-month follow-up in 4 ERs in The Netherlands. Participants were 4290 children aged 0-7 years, attending the ER because of physical injury. All children were systematically tested with an easy-to-use child abuse checklist (index test). A national expert panel (reference standard) retrospectively assessed all children with positive screens and a 15% random sample of the children with negative screens for physical abuse, using additional information, namely, an injury history taken by a paediatrician, information provided by the general practitioner, youth doctor and social services by structured questionnaires, and 6-month follow-up information. Our main outcome measure was physical child abuse; secondary outcome measure was injury due to neglect and need for help. 4253/4290 (99%) parents agreed to follow-up. At a prevalence of 0.07% (3/4253) for inflicted injury by expert panel decision, the positive predictive value of the checklist was 0.03 (95% CI 0.006 to 0.085), and the negative predictive value 1.0 (0.994 to 1.0). There was 100% (93 to 100) agreement about inflicted injury in children, with positive screens between the expert panel and child abuse experts. Rare cases of inflicted injury among preschool children presenting at ERs for injury are very likely captured by easy-to-use checklists, but at very high false-positive rates. Subsequent assessment by child abuse experts can be safely restricted to children with positive screens at very low risk of missing cases of inflicted injury. Because of the high false positive rate, we do advise careful prior consideration of cost-effectiveness and clinical and societal implications before de novo implementation.

Does experience in hysteroscopy improve accuracy and inter-observer agreement in the management of abnormal uterine bleeding?

PubMed

Bourdel, Nicolas; Modaffari, Paola; Tognazza, Enrica; Pertile, Riccardo; Chauvet, Pauline; Botchorishivili, Revaz; Savary, Dennis; Pouly, Jean Luc; Rabischong, Benoit; Canis, Michel

2016-12-01

Hysteroscopic reliability may be influenced by the experience of the operator and by a lack of morphological diagnostic criteria for endometrial malignant pathologies. The aim of this study was to evaluate the diagnostic accuracy and the inter-observer agreement (IOA) in the management of abnormal uterine bleeding (AUB) among different experienced gynecologists. Each gynecologist, without any other clinical information, was asked to evaluate the anonymous video recordings of 51 consecutive patients who underwent hysteroscopy and endometrial resection for AUB. Experts (>500 hysteroscopies), seniors (20-499 procedures) and junior (≤19 procedures) gynecologists were asked to judge endometrial macroscopic appearance (benign, suspicious or frankly malignant). They also had to propose the histological diagnosis (atrophic or proliferative endometrium; simple, glandulocystic or atypical endometrial hyperplasia and endometrial carcinoma). Observers were free to indicate whether the quality of recordings were not good enough for adequate assessment. IOA (k coefficient), sensitivity, specificity, predictive value and the likelihood ratio were calculated. Five expert, five senior and six junior gynecologists were involved in the study. Considering endometrial cancer and endometrial atypical hyperplasia, sensitivity and specificity were respectively 55.5 % and 84.5 % for juniors, 66.6 % and 81.2 % for seniors and 86.6 % and 87.3 % for experts. Concerning endometrial macroscopic appearance, IOA was poor for juniors (k = 0.10) and fair for seniors and experts (k = 0.23 and 0.22, respectively). IOA was poor for juniors and experts (k = 0.18 and 0.20, respectively) and fair for seniors (k = 0.30) in predicting the histological diagnosis. Sensitivity improves with the observer's experience, but inter-observer agreement and reproducibility of hysteroscopy for endometrial malignancies are not satisfying no matter the level of expertise. Therefore, an accurate and complete endometrial sampling is still needed.

Improved artificial neural networks in prediction of malignancy of lesions in contrast-enhanced MR-mammography.

PubMed

Vomweg, T W; Buscema, M; Kauczor, H U; Teifke, A; Intraligi, M; Terzi, S; Heussel, C P; Achenbach, T; Rieker, O; Mayer, D; Thelen, M

2003-09-01

The aim of this study was to evaluate the capability of improved artificial neural networks (ANN) and additional novel training methods in distinguishing between benign and malignant breast lesions in contrast-enhanced magnetic resonance-mammography (MRM). A total of 604 histologically proven cases of contrast-enhanced lesions of the female breast at MRI were analyzed. Morphological, dynamic and clinical parameters were collected and stored in a database. The data set was divided into several groups using random or experimental methods [Training & Testing (T&T) algorithm] to train and test different ANNs. An additional novel computer program for input variable selection was applied. Sensitivity and specificity were calculated and compared with a statistical method and an expert radiologist. After optimization of the distribution of cases among the training and testing sets by the T & T algorithm and the reduction of input variables by the Input Selection procedure a highly sophisticated ANN achieved a sensitivity of 93.6% and a specificity of 91.9% in predicting malignancy of lesions within an independent prediction sample set. The best statistical method reached a sensitivity of 90.5% and a specificity of 68.9%. An expert radiologist performed better than the statistical method but worse than the ANN (sensitivity 92.1%, specificity 85.6%). Features extracted out of dynamic contrast-enhanced MRM and additional clinical data can be successfully analyzed by advanced ANNs. The quality of the resulting network strongly depends on the training methods, which are improved by the use of novel training tools. The best results of an improved ANN outperform expert radiologists.

Use of a machine learning algorithm to classify expertise: analysis of hand motion patterns during a simulated surgical task.

PubMed

Watson, Robert A

2014-08-01

To test the hypothesis that machine learning algorithms increase the predictive power to classify surgical expertise using surgeons' hand motion patterns. In 2012 at the University of North Carolina at Chapel Hill, 14 surgical attendings and 10 first- and second-year surgical residents each performed two bench model venous anastomoses. During the simulated tasks, the participants wore an inertial measurement unit on the dorsum of their dominant (right) hand to capture their hand motion patterns. The pattern from each bench model task performed was preprocessed into a symbolic time series and labeled as expert (attending) or novice (resident). The labeled hand motion patterns were processed and used to train a Support Vector Machine (SVM) classification algorithm. The trained algorithm was then tested for discriminative/predictive power against unlabeled (blinded) hand motion patterns from tasks not used in the training. The Lempel-Ziv (LZ) complexity metric was also measured from each hand motion pattern, with an optimal threshold calculated to separately classify the patterns. The LZ metric classified unlabeled (blinded) hand motion patterns into expert and novice groups with an accuracy of 70% (sensitivity 64%, specificity 80%). The SVM algorithm had an accuracy of 83% (sensitivity 86%, specificity 80%). The results confirmed the hypothesis. The SVM algorithm increased the predictive power to classify blinded surgical hand motion patterns into expert versus novice groups. With further development, the system used in this study could become a viable tool for low-cost, objective assessment of procedural proficiency in a competency-based curriculum.

Predicting general criminal recidivism in mentally disordered offenders using a random forest approach.

PubMed

Pflueger, Marlon O; Franke, Irina; Graf, Marc; Hachtel, Henning

2015-03-29

Psychiatric expert opinions are supposed to assess the accused individual's risk of reoffending based on a valid scientific foundation. In contrast to specific recidivism, general recidivism has only been poorly considered in Continental Europe; we therefore aimed to develop a valid instrument for assessing the risk of general criminal recidivism of mentally ill offenders. Data of 259 mentally ill offenders with a median time at risk of 107 months were analyzed and combined with the individuals' criminal records. We derived risk factors for general criminal recidivism and classified re-offences by using a random forest approach. In our sample of mentally ill offenders, 51% were reconvicted. The most important predictive factors for general criminal recidivism were: number of prior convictions, age, type of index offence, diversity of criminal history, and substance abuse. With our statistical approach we were able to correctly identify 58-95% of all reoffenders and 65-97% of all committed offences (AUC = .90). Our study presents a new statistical approach to forensic-psychiatric risk-assessment, allowing experts to evaluate general risk of reoffending in mentally disordered individuals, with a special focus on high-risk groups. This approach might serve not only for expert opinions in court, but also for risk management strategies and therapeutic interventions.

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants.

PubMed

Mueller, Martina; Wagner, Carol L; Annibale, David J; Knapp, Rebecca G; Hulsey, Thomas C; Almeida, Jonas S

2006-03-01

Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0-1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data originally used for the development of the prediction tool. State-of-the-art, machine-learning methods can be employed for the development of sophisticated tools to aid clinicians' decisions. We identified numerous variables considered relevant for extubation decisions for mechanically ventilated premature infants with RDS. We then developed a web-based decision-support tool for clinicians which can be made widely available and potentially improve patient care world wide.

Accuracy and artifact: reexamining the intensity bias in affective forecasting.

PubMed

Levine, Linda J; Lench, Heather C; Kaplan, Robin L; Safer, Martin A

2012-10-01

Research on affective forecasting shows that people have a robust tendency to overestimate the intensity of future emotion. We hypothesized that (a) people can accurately predict the intensity of their feelings about events and (b) a procedural artifact contributes to people's tendency to overestimate the intensity of their feelings in general. People may misinterpret the forecasting question as asking how they will feel about a focal event, but they are later asked to report their feelings in general without reference to that event. In the current investigation, participants predicted and reported both their feelings in general and their feelings about an election outcome (Study 1) and an exam grade (Study 3). We also assessed how participants interpreted forecasting questions (Studies 2 and 4) and conducted a meta-analysis of affective forecasting research (Study 5). The results showed that participants accurately predicted the intensity of their feelings about events. They overestimated only when asked to predict how they would feel in general and later report their feelings without reference to the focal event. Most participants, however, misinterpreted requests to predict their feelings in general as asking how they would feel when they were thinking about the focal event. Clarifying the meaning of the forecasting question significantly reduced overestimation. These findings reveal that people have more sophisticated self-knowledge than is commonly portrayed in the affective forecasting literature. Overestimation of future emotion is partly due to a procedure in which people predict one thing but are later asked to report another.

Emotion Regulation through Movement: Unique Sets of Movement Characteristics are Associated with and Enhance Basic Emotions.

PubMed

Shafir, Tal; Tsachor, Rachelle P; Welch, Kathleen B

2015-01-01

We have recently demonstrated that motor execution, observation, and imagery of movements expressing certain emotions can enhance corresponding affective states and therefore could be used for emotion regulation. But which specific movement(s) should one use in order to enhance each emotion? This study aimed to identify, using Laban Movement Analysis (LMA), the Laban motor elements (motor characteristics) that characterize movements whose execution enhances each of the basic emotions: anger, fear, happiness, and sadness. LMA provides a system of symbols describing its motor elements, which gives a written instruction (motif) for the execution of a movement or movement-sequence over time. Six senior LMA experts analyzed a validated set of video clips showing whole body dynamic expressions of anger, fear, happiness and sadness, and identified the motor elements that were common to (appeared in) all clips expressing the same emotion. For each emotion, we created motifs of different combinations of the motor elements common to all clips of the same emotion. Eighty subjects from around the world read and moved those motifs, to identify the emotion evoked when moving each motif and to rate the intensity of the evoked emotion. All subjects together moved and rated 1241 motifs, which were produced from 29 different motor elements. Using logistic regression, we found a set of motor elements associated with each emotion which, when moved, predicted the feeling of that emotion. Each emotion was predicted by a unique set of motor elements and each motor element predicted only one emotion. Knowledge of which specific motor elements enhance specific emotions can enable emotional self-regulation through adding some desired motor qualities to one's personal everyday movements (rather than mimicking others' specific movements) and through decreasing motor behaviors which include elements that enhance negative emotions.

A conceptual framework for hydropeaking mitigation.

PubMed

Bruder, Andreas; Tonolla, Diego; Schweizer, Steffen P; Vollenweider, Stefan; Langhans, Simone D; Wüest, Alfred

2016-10-15

Hydropower plants are an important source of renewable energy. In the near future, high-head storage hydropower plants will gain further importance as a key element of large-scale electricity production systems. However, these power plants can cause hydropeaking which is characterized by intense unnatural discharge fluctuations in downstream river reaches. Consequences on environmental conditions in these sections are diverse and include changes to the hydrology, hydraulics and sediment regime on very short time scales. These altered conditions affect river ecosystems and biota, for instance due to drift and stranding of fishes and invertebrates. Several structural and operational measures exist to mitigate hydropeaking and the adverse effects on ecosystems, but estimating and predicting their ecological benefit remains challenging. We developed a conceptual framework to support the ecological evaluation of hydropeaking mitigation measures based on current mitigation projects in Switzerland and the scientific literature. We refined this framework with an international panel of hydropeaking experts. The framework is based on a set of indicators, which covers all hydrological phases of hydropeaking and the most important affected abiotic and biotic processes. Effects of mitigation measures on these indicators can be predicted quantitatively using prediction tools such as discharge scenarios and numerical habitat models. Our framework allows a comparison of hydropeaking effects among alternative mitigation measures, to the pre-mitigation situation, and to reference river sections. We further identified key issues that should be addressed to increase the efficiency of current and future projects. They include the spatial and temporal context of mitigation projects, the interactions of river morphology with hydropeaking effects, and the role of appropriate monitoring to evaluate the success of mitigation projects. Copyright © 2016 Elsevier B.V. All rights reserved.

Emotion Regulation through Movement: Unique Sets of Movement Characteristics are Associated with and Enhance Basic Emotions

PubMed Central

Shafir, Tal; Tsachor, Rachelle P.; Welch, Kathleen B.

2016-01-01

We have recently demonstrated that motor execution, observation, and imagery of movements expressing certain emotions can enhance corresponding affective states and therefore could be used for emotion regulation. But which specific movement(s) should one use in order to enhance each emotion? This study aimed to identify, using Laban Movement Analysis (LMA), the Laban motor elements (motor characteristics) that characterize movements whose execution enhances each of the basic emotions: anger, fear, happiness, and sadness. LMA provides a system of symbols describing its motor elements, which gives a written instruction (motif) for the execution of a movement or movement-sequence over time. Six senior LMA experts analyzed a validated set of video clips showing whole body dynamic expressions of anger, fear, happiness and sadness, and identified the motor elements that were common to (appeared in) all clips expressing the same emotion. For each emotion, we created motifs of different combinations of the motor elements common to all clips of the same emotion. Eighty subjects from around the world read and moved those motifs, to identify the emotion evoked when moving each motif and to rate the intensity of the evoked emotion. All subjects together moved and rated 1241 motifs, which were produced from 29 different motor elements. Using logistic regression, we found a set of motor elements associated with each emotion which, when moved, predicted the feeling of that emotion. Each emotion was predicted by a unique set of motor elements and each motor element predicted only one emotion. Knowledge of which specific motor elements enhance specific emotions can enable emotional self-regulation through adding some desired motor qualities to one's personal everyday movements (rather than mimicking others' specific movements) and through decreasing motor behaviors which include elements that enhance negative emotions. PMID:26793147

Predictive value of EEG in postanoxic encephalopathy: A quantitative model-based approach.

PubMed

Efthymiou, Evdokia; Renzel, Roland; Baumann, Christian R; Poryazova, Rositsa; Imbach, Lukas L

2017-10-01

The majority of comatose patients after cardiac arrest do not regain consciousness due to severe postanoxic encephalopathy. Early and accurate outcome prediction is therefore essential in determining further therapeutic interventions. The electroencephalogram is a standardized and commonly available tool used to estimate prognosis in postanoxic patients. The identification of pathological EEG patterns with poor prognosis relies however primarily on visual EEG scoring by experts. We introduced a model-based approach of EEG analysis (state space model) that allows for an objective and quantitative description of spectral EEG variability. We retrospectively analyzed standard EEG recordings in 83 comatose patients after cardiac arrest between 2005 and 2013 in the intensive care unit of the University Hospital Zürich. Neurological outcome was assessed one month after cardiac arrest using the Cerebral Performance Category. For a dynamic and quantitative EEG analysis, we implemented a model-based approach (state space analysis) to quantify EEG background variability independent from visual scoring of EEG epochs. Spectral variability was compared between groups and correlated with clinical outcome parameters and visual EEG patterns. Quantitative assessment of spectral EEG variability (state space velocity) revealed significant differences between patients with poor and good outcome after cardiac arrest: Lower mean velocity in temporal electrodes (T4 and T5) was significantly associated with poor prognostic outcome (p<0.005) and correlated with independently identified visual EEG patterns such as generalized periodic discharges (p<0.02). Receiver operating characteristic (ROC) analysis confirmed the predictive value of lower state space velocity for poor clinical outcome after cardiac arrest (AUC 80.8, 70% sensitivity, 15% false positive rate). Model-based quantitative EEG analysis (state space analysis) provides a novel, complementary marker for prognosis in postanoxic encephalopathy. Copyright © 2017 Elsevier B.V. All rights reserved.

Enabling phenotypic big data with PheNorm.

PubMed

Yu, Sheng; Ma, Yumeng; Gronsbell, Jessica; Cai, Tianrun; Ananthakrishnan, Ashwin N; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Liao, Katherine P; Cai, Tianxi

2018-01-01

Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation, annotation remains a major bottleneck. In this paper, we present PheNorm, a phenotyping algorithm that does not require expert-labeled samples for training. The most predictive features, such as the number of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes or mentions of the target phenotype, are normalized to resemble a normal mixture distribution with high area under the receiver operating curve (AUC) for prediction. The transformed features are then denoised and combined into a score for accurate disease classification. We validated the accuracy of PheNorm with 4 phenotypes: coronary artery disease, rheumatoid arthritis, Crohn's disease, and ulcerative colitis. The AUCs of the PheNorm score reached 0.90, 0.94, 0.95, and 0.94 for the 4 phenotypes, respectively, which were comparable to the accuracy of supervised algorithms trained with sample sizes of 100-300, with no statistically significant difference. The accuracy of the PheNorm algorithms is on par with algorithms trained with annotated samples. PheNorm fully automates the generation of accurate phenotyping algorithms and demonstrates the capacity for EHR-driven annotations to scale to the next level - phenotypic big data. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages

NASA Astrophysics Data System (ADS)

Nguyen, Minh Q.; Allebach, Jan P.

2015-01-01

In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false alarms" are not nearly as catastrophic as "misses", which represent potentially serious problems that are never seen by the systems developers. This scenario motivates us to develop a machine learning framework that will achieve the minimum "false alarm" rate subject to a specified "miss" rate. In order to construct such a set of receiver operating characteristic2 (ROC) curves, we examine various tools for the prediction, ranging from an exhaustive search over the space of the nonlinear discriminants to a Cost-Sentitive SVM3 framework. We then compare the curves gained from those methods. Our work shows promise for applying a standard framework to obtain a full ROC curve when it comes to tackling other machine learning problems in industry.

Hemisphere Differences in Speech-Sound Event-Related Potentials in Intensive Care Neonates: Associations and Predictive Value for Development in Infancy

PubMed Central

Maitre, Nathalie L.; Slaughter, James C.; Aschner, Judy L.; Key, Alexandra P.

2014-01-01

Neurodevelopmental delays in intensive care neonates are common but difficult to predict. In children, hemisphere differences in cortical processing of speech are predictive of cognitive performance. We hypothesized that hemisphere differences in auditory event-related potentials in intensive care neonates are predictive of neurodevelopment in infancy, even in those born preterm. Event-related potentials to speech sounds were prospectively recorded in 57 infants (gestational age 24–40 weeks) prior to discharge. The Developmental Assessment of Young Children was performed at 6 and 12 months. Hemisphere differences in mean amplitudes increased with postnatal age (P < .01) but not with gestational age. Greater hemisphere differences were associated with improved communication and cognitive scores at 6 and 12 months, but decreased in significance at 12 months after adjusting for socioeconomic and clinical factors. Auditory cortical responses can be used in intensive care neonates to help identify infants at higher risk for delays in infancy. PMID:23864588

Prediction of Winter Storm Tracks and Intensities Using the GFDL fvGFS Model

NASA Astrophysics Data System (ADS)

Rees, S.; Boaggio, K.; Marchok, T.; Morin, M.; Lin, S. J.

2017-12-01

The GFDL Finite-Volume Cubed-Sphere Dynamical core (FV3) is coupled to a modified version of the Global Forecast System (GFS) physics and initial conditions, to form the fvGFS model. This model is similar to the one being implemented as the next-generation operational weather model for the NWS, which is also FV3-powered. Much work has been done to verify fvGFS tropical cyclone prediction, but little has been done to verify winter storm prediction. These costly and dangerous storms impact parts of the U.S. every year. To verify winter storms we ran the NCEP operational cyclone tracker, developed at GFDL, on semi-real-time 13 km horizontal resolution fvGFS forecasts. We have found that fvGFS compares well to the operational GFS in storm track and intensity, though often predicts slightly higher intensities. This presentation will show the track and intensity verification from the past two winter seasons and explore possible reasons for bias.

Intensity ratio to improve black hole assessment in multiple sclerosis.

PubMed

Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H

2018-01-01

Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Expert Diagnosis of Plus Disease in Retinopathy of Prematurity From Computer-Based Image Analysis.

PubMed

Campbell, J Peter; Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir N; Reynolds, James D; Horowitz, Jason; Hutcheson, Kelly; Shapiro, Michael; Repka, Michael X; Ferrone, Phillip; Drenser, Kimberly; Martinez-Castellanos, Maria Ana; Ostmo, Susan; Jonas, Karyn; Chan, R V Paul; Chiang, Michael F

2016-06-01

Published definitions of plus disease in retinopathy of prematurity (ROP) reference arterial tortuosity and venous dilation within the posterior pole based on a standard published photograph. One possible explanation for limited interexpert reliability for a diagnosis of plus disease is that experts deviate from the published definitions. To identify vascular features used by experts for diagnosis of plus disease through quantitative image analysis. A computer-based image analysis system (Imaging and Informatics in ROP [i-ROP]) was developed using a set of 77 digital fundus images, and the system was designed to classify images compared with a reference standard diagnosis (RSD). System performance was analyzed as a function of the field of view (circular crops with a radius of 1-6 disc diameters) and vessel subtype (arteries only, veins only, or all vessels). Routine ROP screening was conducted from June 29, 2011, to October 14, 2014, in neonatal intensive care units at 8 academic institutions, with a subset of 73 images independently classified by 11 ROP experts for validation. The RSD was compared with the majority diagnosis of experts. The primary outcome measure was the percentage of accuracy of the i-ROP system classification of plus disease, with the RSD as a function of the field of view and vessel type. Secondary outcome measures included the accuracy of the 11 experts compared with the RSD. Accuracy of plus disease diagnosis by the i-ROP computer-based system was highest (95%; 95% CI, 94%-95%) when it incorporated vascular tortuosity from both arteries and veins and with the widest field of view (6-disc diameter radius). Accuracy was 90% or less when using only arterial tortuosity and 85% or less using a 2- to 3-disc diameter view similar to the standard published photograph. Diagnostic accuracy of the i-ROP system (95%) was comparable to that of 11 expert physicians (mean 87%, range 79%-99%). Experts in ROP appear to consider findings from beyond the posterior retina when diagnosing plus disease and consider tortuosity of both arteries and veins, in contrast with published definitions. It is feasible for a computer-based image analysis system to perform comparably with ROP experts, using manually segmented images.

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PubMed

Kalpathy-Cramer, Jayashree; Campbell, J Peter; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Estimating the spatial distribution of field-applied mushroom compost in the Brandywine-Christina River Basin using multispectral remote sensing

NASA Astrophysics Data System (ADS)

Moxey, Kelsey A.

The world's greatest concentration of mushroom farms is settled within the Brandywine-Christina River Basin in Chester County in southeastern Pennsylvania. This industry produces a nutrient-rich byproduct known as spent mushroom compost, which has been traditionally applied to local farm fields as an organic fertilizer and soil amendment. While mushroom compost has beneficial properties, the possible over-application to farm fields could potentially degrade stream water quality. The goal of this study was to estimate the spatial extent and intensity of field-applied mushroom compost. We applied a remote sensing approach using Landsat multispectral imagery. We utilized the soil line technique, using the red and near-infrared bands, to estimate differences in soil wetness as a result of increased soil organic matter content from mushroom compost. We validated soil wetness estimates by examining the spectral response of references sites. We performed a second independent validation analysis using expert knowledge from agricultural extension agents. Our results showed that the soil line based wetness index worked well. The spectral validation illustrated that compost changes the spectral response of soil because of changes in wetness. The independent expert validation analysis produced a strong significant correlation between our remotely-sensed wetness estimates and the empirical ratings of compost application intensities. Overall, the methodology produced realistic spatial distributions of field-applied compost application intensities across the study area. These spatial distributions will be used for follow-up studies to assess the effect of spent mushroom compost on stream water quality.

Aggregating Data for Computational Toxicology Applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System

PubMed Central

Judson, Richard S.; Martin, Matthew T.; Egeghy, Peter; Gangwal, Sumit; Reif, David M.; Kothiya, Parth; Wolf, Maritja; Cathey, Tommy; Transue, Thomas; Smith, Doris; Vail, James; Frame, Alicia; Mosher, Shad; Cohen Hubal, Elaine A.; Richard, Ann M.

2012-01-01

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases. PMID:22408426

Aggregating data for computational toxicology applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.

PubMed

Judson, Richard S; Martin, Matthew T; Egeghy, Peter; Gangwal, Sumit; Reif, David M; Kothiya, Parth; Wolf, Maritja; Cathey, Tommy; Transue, Thomas; Smith, Doris; Vail, James; Frame, Alicia; Mosher, Shad; Cohen Hubal, Elaine A; Richard, Ann M

2012-01-01

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.

Both trait and state mindfulness predict lower aggressiveness via anger rumination: A multilevel mediation analysis

PubMed Central

Eisenlohr-Moul, Tory A.; Peters, Jessica R.; Pond, Richard S.; DeWall, C. Nathan

2016-01-01

Trait mindfulness, or the capacity for nonjudgmental, present-centered attention, predicts lower aggression in cross-sectional samples, an effect mediated by reduced anger rumination. Experimental work also implicates state mindfulness (i.e., fluctuations around one's typical mindfulness) in aggression. Despite evidence that both trait and state mindfulness predict lower aggression, their relative impact and their mechanisms remain unclear. Higher trait mindfulness and state increases in mindfulness facets may reduce aggression-related outcomes by (1) limiting the intensity of anger, or (2) limiting rumination on anger experiences. The present study tests two hypotheses: First, that both trait and state mindfulness contribute unique variance to lower aggressiveness, and second, that the impact of both trait and state mindfulness on aggressiveness will be uniquely partially mediated by both anger intensity and anger rumination. 86 participants completed trait measures of mindfulness, anger intensity, and anger rumination, then completed diaries for 35 days assessing mindfulness, anger intensity, anger rumination, anger expression, and self-reported and behavioral aggressiveness. Using multilevel zero-inflated regression, we examined unique contributions of trait and state mindfulness facets to daily anger expression and aggressiveness. We also examined the mediating roles of anger intensity and anger rumination at both trait and state levels. Mindfulness facets predicted anger expression and aggressiveness indirectly through anger rumination after controlling for indirect pathways through anger intensity. Individuals with high or fluctuating aggression may benefit from mindfulness training to reduce both intensity of and rumination on anger. PMID:27429667

Impact of vocal load on breathiness: perceptual evaluation.

PubMed

Remacle, Angélique; Schoentgen, Jean; Finck, Camille; Bodson, Agnès; Morsomme, Dominique

2014-10-01

To evaluate the impact on voice of 2 hours of continuous oral reading. Fifty normophonic women underwent two sessions of voice loading in which the required intensity level varied: 60-65 dB(A) for the first session, and 70-75 dB(A) for the second session. Ten expert judges evaluated the breathiness of one sentence recorded before and after each loading session. Pairs of stimuli were presented randomly to the judges, who were asked to designate the breathiest sample. A significant decrease in breathiness was observed following both sessions, suggesting an improvement of voice subsequent to loading. When comparing the two intensity levels, no difference was found for breathiness after vocal loading.

Differences in managerial behaviour between head nurses and medical directors in intensive care units in Europe.

PubMed

Pepermans, R; Mentens, C; Goedee, M; Jegers, M; van Roy, K

2001-01-01

We attempt to determine whether differences appear between the managerial behaviour of European intensive care head nurses on the one side and medical directors on the other. In order to come up with a managerial job and competency analysis of ICU managers, observations and interviews were performed. Additionally, focus groups consisting of ICU experts were organized. The results are discussed according to managerial behaviour taxonomies and existing competency models. There seems to be some differentiation between the two managerial positions studied. Head nurses are more involved in planning/coordinating and motivating/reinforcing activities, whereas medical directors are more involved in socializing/politicking, decision making/problem solving, interaction with others and disciplining.

The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review

PubMed Central

Sheridan, Heather; Reingold, Eyal M.

2017-01-01

In the field of medical image perception, the holistic processing perspective contends that experts can rapidly extract global information about the image, which can be used to guide their subsequent search of the image (Swensson, 1980; Nodine and Kundel, 1987; Kundel et al., 2007). In this review, we discuss the empirical evidence supporting three different predictions that can be derived from the holistic processing perspective: Expertise in medical image perception is domain-specific, experts use parafoveal and/or peripheral vision to process large regions of the image in parallel, and experts benefit from a rapid initial glimpse of an image. In addition, we discuss a pivotal recent study (Litchfield and Donovan, 2016) that seems to contradict the assumption that experts benefit from a rapid initial glimpse of the image. To reconcile this finding with the existing literature, we suggest that global processing may serve multiple functions that extend beyond the initial glimpse of the image. Finally, we discuss future research directions, and we highlight the connections between the holistic processing account and similar theoretical perspectives and findings from other domains of visual expertise. PMID:29033865

The Holistic Processing Account of Visual Expertise in Medical Image Perception: A Review.

PubMed

Sheridan, Heather; Reingold, Eyal M

2017-01-01

In the field of medical image perception, the holistic processing perspective contends that experts can rapidly extract global information about the image, which can be used to guide their subsequent search of the image (Swensson, 1980; Nodine and Kundel, 1987; Kundel et al., 2007). In this review, we discuss the empirical evidence supporting three different predictions that can be derived from the holistic processing perspective: Expertise in medical image perception is domain-specific, experts use parafoveal and/or peripheral vision to process large regions of the image in parallel, and experts benefit from a rapid initial glimpse of an image. In addition, we discuss a pivotal recent study (Litchfield and Donovan, 2016) that seems to contradict the assumption that experts benefit from a rapid initial glimpse of the image. To reconcile this finding with the existing literature, we suggest that global processing may serve multiple functions that extend beyond the initial glimpse of the image. Finally, we discuss future research directions, and we highlight the connections between the holistic processing account and similar theoretical perspectives and findings from other domains of visual expertise.

Analysis of the Structure of Surgical Activity for a Suturing and Knot-Tying Task

PubMed Central

Vedula, S. Swaroop; Malpani, Anand O.; Tao, Lingling; Chen, George; Gao, Yixin; Poddar, Piyush; Ahmidi, Narges; Paxton, Christopher; Vidal, Rene; Khudanpur, Sanjeev; Hager, Gregory D.; Chen, Chi Chiung Grace

2016-01-01

Background Surgical tasks are performed in a sequence of steps, and technical skill evaluation includes assessing task flow efficiency. Our objective was to describe differences in task flow for expert and novice surgeons for a basic surgical task. Methods We used a hierarchical semantic vocabulary to decompose and annotate maneuvers and gestures for 135 instances of a surgeon’s knot performed by 18 surgeons. We compared counts of maneuvers and gestures, and analyzed task flow by skill level. Results Experts used fewer gestures to perform the task (26.29; 95% CI = 25.21 to 27.38 for experts vs. 31.30; 95% CI = 29.05 to 33.55 for novices) and made fewer errors in gestures than novices (1.00; 95% CI = 0.61 to 1.39 vs. 2.84; 95% CI = 2.3 to 3.37). Transitions among maneuvers, and among gestures within each maneuver for expert trials were more predictable than novice trials. Conclusions Activity segments and state flow transitions within a basic surgical task differ by surgical skill level, and can be used to provide targeted feedback to surgical trainees. PMID:26950551

Reliability and validity of expert assessment based on airborne and urinary measures of nickel and chromium exposure in the electroplating industry.

PubMed

Chen, Yu-Cheng; Coble, Joseph B; Deziel, Nicole C; Ji, Bu-Tian; Xue, Shouzheng; Lu, Wei; Stewart, Patricia A; Friesen, Melissa C

2014-11-01

The reliability and validity of six experts' exposure ratings were evaluated for 64 nickel-exposed and 72 chromium-exposed workers from six Shanghai electroplating plants based on airborne and urinary nickel and chromium measurements. Three industrial hygienists and three occupational physicians independently ranked the exposure intensity of each metal on an ordinal scale (1-4) for each worker's job in two rounds: the first round was based on responses to an occupational history questionnaire and the second round also included responses to an electroplating industry-specific questionnaire. The Spearman correlation (r(s)) was used to compare each rating's validity to its corresponding subject-specific arithmetic mean of four airborne or four urinary measurements. Reliability was moderately high (weighted kappa range=0.60-0.64). Validity was poor to moderate (r(s)=-0.37-0.46) for both airborne and urinary concentrations of both metals. For airborne nickel concentrations, validity differed by plant. For dichotomized metrics, sensitivity and specificity were higher based on urinary measurements (47-78%) than airborne measurements (16-50%). Few patterns were observed by metal, assessment round, or expert type. These results suggest that, for electroplating exposures, experts can achieve moderately high agreement and (reasonably) distinguish between low and high exposures when reviewing responses to in-depth questionnaires used in population-based case-control studies.

Visualising probabilistic flood forecast information: expert preferences and perceptions of best practice in uncertainty communication

NASA Astrophysics Data System (ADS)

Pappenberger, F.; Stephens, E. M.; Thielen, J.; Salomon, P.; Demeritt, D.; van Andel, S.; Wetterhall, F.; Alfieri, L.

2011-12-01

The aim of this paper is to understand and to contribute to improved communication of the probabilistic flood forecasts generated by Hydrological Ensemble Prediction Systems (HEPS) with particular focus on the inter expert communication. Different users are likely to require different kinds of information from HEPS and thus different visualizations. The perceptions of this expert group are important both because they are the designers and primary users of existing HEPS. Nevertheless, they have sometimes resisted the release of uncertainty information to the general public because of doubts about whether it can be successfully communicated in ways that would be readily understood to non-experts. In this paper we explore the strengths and weaknesses of existing HEPS visualization methods and thereby formulate some wider recommendations about best practice for HEPS visualization and communication. We suggest that specific training on probabilistic forecasting would foster use of probabilistic forecasts with a wider range of applications. The result of a case study exercise showed that there is no overarching agreement between experts on how to display probabilistic forecasts and what they consider essential information that should accompany plots and diagrams. In this paper we propose a list of minimum properties that, if consistently displayed with probabilistic forecasts, would make the products more easily understandable.

Vulnerability of bridges to scour: insights from an international expert elicitation workshop

NASA Astrophysics Data System (ADS)

Lamb, Rob; Aspinall, Willy; Odbert, Henry; Wagener, Thorsten

2017-08-01

Scour (localised erosion) during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

Role of upper-ocean on the intensity of Bay of Bengal cyclone `Phailin' as revealed by coupled simulation using Mesoscale Coupled Modeling System (WRF-ROMS)

NASA Astrophysics Data System (ADS)

Mani, B.; Mandal, M.

2016-12-01

Numerical prediction of tropical cyclone (TC) track has improved significantly in recent years, but not the intensity. It is well accepted that TC induced sea surface temperature (SST) cooling in conjunction with pre-existing upper-ocean features have major influences on tropical cyclone intensity. Absence of two-way atmosphere-ocean feedback in the stand-alone atmosphere models has major consequences on their prediction of TC intensity. The present study investigates the role of upper-ocean on prediction of TC intensity and track based on coupled and uncoupled simulation of the Bay of Bengal (BoB) cyclone `Phailin'. The coupled simulation is conducted with the Mesoscale Coupled Modeling System (MCMS) which is a fully coupled atmosphere-ocean modeling system that includes the non-hydrostatic atmospheric model (WRF-ARW) and the three-dimensional hydrostatic ocean model (ROMS). The uncoupled simulation is performed using the atmosphere component of MCMS i.e., the customized version of WRF-ARW for BoB cyclones with prescribed (RTG) SST. The track and intensity of the storm is significantly better simulated by the MCMS and closely followed the observation. The peak intensity, landfall position and time are accurately predicted by MCMS, whereas the uncoupled simulation over predicted the storm intensity. Validation of storm induced SST cooling with the merged microwave-infrared satellite SST indicates that the MCMS simulation shows better correlation both in terms of spatial spread of cold wake and its magnitude. The analysis also suggests that the Pre-existing Cyclonic Eddy (PCE) observed adjacent to the storm enhanced the TC induced SST cooling. It is observed that the response of SST (i.e., cooling) to storm intensity is 12hr with 95% statistical significance. The air-sea enthalpy flux shows a clear asymmetry between Front Left (FL) and Rear Right (RR) regime to the storm center where TC induced cooling is more than 0.5K/24hr. The analysis of atmospheric boundary layer reveals the formation of persistent stable boundary layer (SBL) over the cold wake, which caused asymmetry in TC structure by quelling convection in the rainbands downstream to the cold wake. The present study signifies the importance of using MCMS in prediction of the BoB cyclone and encourages further investigation with more cyclone cases.

Geometrical theory to predict eccentric photorefraction intensity profiles in the human eye

NASA Astrophysics Data System (ADS)

Roorda, Austin; Campbell, Melanie C. W.; Bobier, W. R.

1995-08-01

In eccentric photorefraction, light returning from the retina of the eye is photographed by a camera focused on the eye's pupil. We use a geometrical model of eccentric photorefraction to generate intensity profiles across the pupil image. The intensity profiles for three different monochromatic aberration functions induced in a single eye are predicted and show good agreement with the measured eccentric photorefraction intensity profiles. A directional reflection from the retina is incorporated into the calculation. Intensity profiles for symmetric and asymmetric aberrations are generated and measured. The latter profile shows a dependency on the source position and the meridian. The magnitude of the effect of thresholding on measured pattern extents is predicted. Monochromatic aberrations in human eyes will cause deviations in the eccentric photorefraction measurements from traditional crescents caused by defocus and may cause misdiagnoses of ametropia or anisometropia. Our results suggest that measuring refraction along the vertical meridian is preferred for screening studies with the eccentric photorefractor.

Prediction of SEP Peak Proton Intensity Based on CME Speed, Direction and Observations of Associated Solar Phenomena

NASA Astrophysics Data System (ADS)

Richardson, I. G.; Mays, M. L.; Thompson, B. J.; Kwon, R.; Frechette, B. P.

2017-12-01

We assess whether a formula obtained by Richardson et al. (Solar Phys., 289, 3059, 2014; DOI 10.1007/s11207-014-0524-8) relating the intensity of 14-24 MeV protons in a solar energetic particle event at 1 AU to the solar event location and the speed of the associated coronal mass ejection (CME), may be used to "predict" the intensity of a solar energetic particle event. Starting with a subset of several hundred CMEs in the CCMC/SWRC DONKI real-time database (http://kauai.ccmc.gsfc.nasa.gov/DONKI/) selected without consideration of whether they were associated with SEP events, we first use the CME speed and direction to predict the proton intensity at Earth or the STEREO spacecraft using this formula. Since most of these CMEs were not in fact associated with SEP events, many "false alarms" result. We then examine whether considering other phenomena which may accompany the CMEs, such as the X-ray flare intensity and the properties of type II and type III radio emissions, may help to reduce the false alarm rate. We also use CME parameters calculated from an ellipsoidal shell fit to multi-spacecraft CME shock observations for a smaller number of events to predict the SEP intensity. We calculate skill scores for each case and assess whether the Richardson et al. (2014) formula, using additional observations to reduce the false alarm rate, has any potential as a SEP prediction tool, assuming that the required observations could be acquired sufficiently rapidly following the onset of the related solar event/CME.

International AIDS Society: Global Scientific Strategy Towards an HIV Cure 2016

PubMed Central

Deeks, Steven G.; Lewin, Sharon R.; Ross, Anna Laura; Ananworanich, Jintanat; Benkirane, Monsef; Cannon, Paula; Chomont, Nicolas; Douek, Daniel; Lifson, Jeffrey D.; Lo, Ying-Ru; Kuritzkes, Daniel; Margolis, David; Mellors, John; Persaud, Deborah; Tucker, Joseph D.; Barre-Sinoussi, Françoise

2017-01-01

Antiretroviral therapy is not curative. Given the challenges in providing life-long therapy to a global population of over 35 million people living with HIV, there is intense interest in developing a cure for HIV infection. The International AIDS Society convened a group of international experts to develop a scientific strategy for research towards an HIV cure. This Perspective summarizes the group's strategy. PMID:27400264

Activity Report: "Escola de Cultura de Pau", the Laureate of the First Evens Prize for Peace Education

ERIC Educational Resources Information Center

Delvou, Marjolein

2011-01-01

On March 18th 2011 an independent jury of experts convened in Antwerp, Belgium, to select the laureate of the first Evens Prize for Peace Education from a shortlist of eleven organizations from all over Europe. After a long day of intense discussions, the jury agreed unanimously to award the prize to the "Escola de Cultura de Pau"…

How Long Does It Take to Learn a Second Language?: Applying the "10,000-Hour Rule" as a Model for Fluency

ERIC Educational Resources Information Center

Eaton, Sarah Elaine

2011-01-01

This study applies the model of expertise developed by Ericsson et al (2007) to second and foreign language learning. Ericsson et al posits that in order to achieve expertise (as they define it) requires 10,000 or longer of "intense training". Applying this model to language learning, equating an expert level of competence with fluency, various…

Bomb Strike Experiment for Mine Countermeasure

DTIC Science & Technology

2006-01-01

Domestic Product ( GDP ), up from 11 percent in 1970, and experts agree that this figure will only continue to increase in coming years (Frittelli...Prediction Model – Technical Description of Recent Changes and Developments. Defense Scientific Establishment, Auckland , New Zealand, Report 149. Seventh

Intelligent data reduction for autonomous power systems

NASA Technical Reports Server (NTRS)

Floyd, Stephen A.

1988-01-01

Since 1984 Marshall Space Flight Center was actively engaged in research and development concerning autonomous power systems. Much of the work in this domain has dealt with the development and application of knowledge-based or expert systems to perform tasks previously accomplished only through intensive human involvement. One such task is the health status monitoring of electrical power systems. Such monitoring is a manpower intensive task which is vital to mission success. The Hubble Space Telescope testbed and its associated Nickel Cadmium Battery Expert System (NICBES) were designated as the system on which the initial proof of concept for intelligent power system monitoing will be established. The key function performed by an engineer engaged in system monitoring is to analyze the raw telemetry data and identify from the whole only those elements which can be considered significant. This function requires engineering expertise on the functionality of the system, the mode of operation and the efficient and effective reading of the telemetry data. Application of this expertise to extract the significant components of the data is referred to as data reduction. Such a function possesses characteristics which make it a prime candidate for the application of knowledge-based systems' technologies. Such applications are investigated and recommendations are offered for the development of intelligent data reduction systems.