Proximal humeral fracture classification systems revisited.

PubMed

Majed, Addie; Macleod, Iain; Bull, Anthony M J; Zyto, Karol; Resch, Herbert; Hertel, Ralph; Reilly, Peter; Emery, Roger J H

2011-10-01

This study evaluated several classification systems and expert surgeons' anatomic understanding of these complex injuries based on a consecutive series of patients. We hypothesized that current proximal humeral fracture classification systems, regardless of imaging methods, are not sufficiently reliable to aid clinical management of these injuries. Complex fractures in 96 consecutive patients were investigated by generation of rapid sequence prototyping models from computed tomography Digital Imaging and Communications in Medicine (DICOM) imaging data. Four independent senior observers were asked to classify each model using 4 classification systems: Neer, AO, Codman-Hertel, and a prototype classification system by Resch. Interobserver and intraobserver κ coefficient values were calculated for the overall classification system and for selected classification items. The κ coefficient values for the interobserver reliability were 0.33 for Neer, 0.11 for AO, 0.44 for Codman-Hertel, and 0.15 for Resch. Interobserver reliability κ coefficient values were 0.32 for the number of fragments and 0.30 for the anatomic segment involved using the Neer system, 0.30 for the AO type (A, B, C), and 0.53, 0.48, and 0.08 for the Resch impaction/distraction, varus/valgus and flexion/extension subgroups, respectively. Three-part fractures showed low reliability for the Neer and AO systems. Currently available evidence suggests fracture classifications in use have poor intra- and inter-observer reliability despite the modality of imaging used thus making treating these injuries difficult as weak as affecting scientific research as well. This study was undertaken to evaluate the reliability of several systems using rapid sequence prototype models. Overall interobserver κ values represented slight to moderate agreement. The most reliable interobserver scores were found with the Codman-Hertel classification, followed by elements of Resch's trial system. The AO system had the lowest values. The higher interobserver reliability values for the Codman-Hertel system showed that is the only comprehensive fracture description studied, whereas the novel classification by Resch showed clear definition in respect to varus/valgus and impaction/distraction angulation. Copyright © 2011 Journal of Shoulder and Elbow Surgery Board of Trustees. All rights reserved.

Classifying visuomotor workload in a driving simulator using subject specific spatial brain patterns

PubMed Central

Dijksterhuis, Chris; de Waard, Dick; Brookhuis, Karel A.; Mulder, Ben L. J. M.; de Jong, Ritske

2013-01-01

A passive Brain Computer Interface (BCI) is a system that responds to the spontaneously produced brain activity of its user and could be used to develop interactive task support. A human-machine system that could benefit from brain-based task support is the driver-car interaction system. To investigate the feasibility of such a system to detect changes in visuomotor workload, 34 drivers were exposed to several levels of driving demand in a driving simulator. Driving demand was manipulated by varying driving speed and by asking the drivers to comply to individually set lane keeping performance targets. Differences in the individual driver's workload levels were classified by applying the Common Spatial Pattern (CSP) and Fisher's linear discriminant analysis to frequency filtered electroencephalogram (EEG) data during an off line classification study. Several frequency ranges, EEG cap configurations, and condition pairs were explored. It was found that classifications were most accurate when based on high frequencies, larger electrode sets, and the frontal electrodes. Depending on these factors, classification accuracies across participants reached about 95% on average. The association between high accuracies and high frequencies suggests that part of the underlying information did not originate directly from neuronal activity. Nonetheless, average classification accuracies up to 75–80% were obtained from the lower EEG ranges that are likely to reflect neuronal activity. For a system designer, this implies that a passive BCI system may use several frequency ranges for workload classifications. PMID:23970851

[International multidisciplinary classification of acute pancreatitis severity: the 2013 Spanish edition].

PubMed

Maraví-Poma, E; Patchen Dellinger, E; Forsmark, C E; Layer, P; Lévy, P; Shimosegawa, T; Siriwardena, A K; Uomo, G; Whitcomb, D C; Windsor, J A; Petrov, M S

2014-05-01

To develop a new classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of the published evidence, and worldwide consultation. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of specialist in pancreatic diseases, but are suboptimal because these definitions are based on the empiric description of events not associated with severity. A personal invitation to contribute to the development of a new classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists and radiologists currently active in the field of clinical acute pancreatitis. The invitation was not limited to members of certain associations or residents of certain countries. A global web-based survey was conducted, and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new classification of severity is based on the actual local and systemic determinants of severity, rather than on the description of events that are non-causally associated with severity. The local determinant relates to whether there is (peri) pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another, whereby the presence of both infected (peri) pancreatic necrosis and persistent organ failure has a greater impact upon severity than either determinant alone. The derivation of a classification based on the above principles results in four categories of severity: mild, moderate, severe, and critical. This classification is the result of a consultative process among specialists in pancreatic diseases from 49 countries spanning North America, South America, Europe, Asia, Oceania and Africa. It provides a set of concise up to date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research. This ensures that the determinant-based classification can be used in a uniform manner throughout the world. Copyright © 2013 Elsevier España, S.L. and SEMICYUC. All rights reserved.

A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

PubMed

Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

2018-03-01

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

Validation of a new classification system for interprosthetic femoral fractures.

PubMed

Pires, Robinson Esteves Santos; Silveira, Marcelo Peixoto Sena; Resende, Alessandra Regina da Silva; Junior, Egidio Oliveira Santana; Campos, Tulio Vinicius Oliveira; Santos, Leandro Emilio Nascimento; Balbachevsky, Daniel; Andrade, Marco Antônio Percope de

2017-07-01

Interprosthetic femoral fracture (IFF) incidence is gradually increasing as the population is progressively ageing. However, treatment remains challenging due to several contributing factors, such as poor bone quality, patient comorbidities, small interprosthetic fragment, and prostheses instability. An effective and specific classification system is essential to optimize treatment management, therefore diminishing complication rates. This study aims to validate a previously described classification system for interprosthetic femoral fractures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intra- and interobserver reliability of the Eaton classification for trapeziometacarpal arthritis: a systematic review.

PubMed

Berger, Aaron J; Momeni, Arash; Ladd, Amy L

2014-04-01

Trapeziometacarpal, or thumb carpometacarpal (CMC), arthritis is a common problem with a variety of treatment options. Although widely used, the Eaton radiographic staging system for CMC arthritis is of questionable clinical utility, as disease severity does not predictably correlate with symptoms or treatment recommendations. A possible reason for this is that the classification itself may not be reliable, but the literature on this has not, to our knowledge, been systematically reviewed. We therefore performed a systematic review to determine the intra- and interobserver reliability of the Eaton staging system. We systematically reviewed English-language studies published between 1973 and 2013 to assess the degree of intra- and interobserver reliability of the Eaton classification for determining the stage of trapeziometacarpal joint arthritis and pantrapezial arthritis based on plain radiographic imaging. Search engines included: PubMed, Scopus(®), and CINAHL. Four studies, which included a total of 163 patients, met our inclusion criteria and were evaluated. The level of evidence of the studies included in this analysis was determined using the Oxford Centre for Evidence Based Medicine Levels of Evidence Classification by two independent observers. A limited number of studies have been performed to assess intra- and interobserver reliability of the Eaton classification system. The four studies included were determined to be Level 3b. These studies collectively indicate that the Eaton classification demonstrates poor to fair interobserver reliability (kappa values: 0.11-0.56) and fair to moderate intraobserver reliability (kappa values: 0.54-0.657). Review of the literature demonstrates that radiographs assist in the assessment of CMC joint disease, but there is not a reliable system for classification of disease severity. Currently, diagnosis and treatment of thumb CMC arthritis are based on the surgeon's qualitative assessment combining history, physical examination, and radiographic evaluation. Inconsistent agreement using the current common radiographic classification system suggests a need for better radiographic tools to quantify disease severity.

[New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

PubMed

Tsimmerman, Ia S

2008-01-01

The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

Imaging evaluation of traumatic thoracolumbar spine injuries: Radiological review

PubMed Central

Gamanagatti, Shivanand; Rathinam, Deepak; Rangarajan, Krithika; Kumar, Atin; Farooque, Kamran; Sharma, Vijay

2015-01-01

Spine fractures account for a large portion of musculoskeletal injuries worldwide. A classification of spine fractures is necessary in order to develop a common language for treatment indications and outcomes. Several classification systems have been developed based on injury anatomy or mechanisms of action, but they have demonstrated poor reliability, have yielded little prognostic information, and have not been widely used. For this reason, the Arbeitsgemeinschaftfür Osteosynthesefragen (AO) committee has classified thorocolumbar spine injuries based on the pathomorphological criteria into3 types (A: Compression; B: Distraction; C: Axial torque and rotational deformity). Each of these types is further divided into 3 groups and 3 subgroups reflecting progressive scale of morphological damage and the degree of instability. Because of its highly detailed sub classifications, the AO system has shown limited interobserver variability. It is similar to its predecessors in that it does not incorporate the patient’s neurologic status.The need for a reliable, reproducible, clinically relevant, prognostic classification system with an optimal balance of ease of use and detail of injury description contributed to the development of a new classification system, the thoracolumbar injury classification and severity score (TLICS). The TLICS defines injury based on three clinical characteristics: injury morphology, integrity of the posterior ligamentous complex, and neurologic status of the patient. The severity score offers prognostic information and is helpful in decision making about surgical vs nonsurgical management. PMID:26435776

Is there any correlation between the ATS, BTS, ERS and GOLD COPD's severity scales and the frequency of hospital admissions?

PubMed

Tsoumakidou, Maria; Tzanakis, Nikolaos; Voulgaraki, Olga; Mitrouska, Ioanna; Chrysofakis, Georgios; Samiou, Maria; Siafakas, Nikolaos M

2004-02-01

Disagreement exists between different COPD guidelines considering classification of severity of the disease. The aim of our study was to determine whether there is any correlation between severity scales of various COPD guidelines (ATS, BTS, ERS and GOLD) and the frequency of hospitalisations for COPD exacerbation. A cohort of 67 COPD patients (65 male 2 female, 45 ex-smokers, 22 current smokers, aged (69.4 +/- 1.1)) was recruited from those admitted in the pulmonary clinic of the University Hospital of Heraklion, Crete for an acute exacerbation. Lung function tests and arterial blood gases analyses were performed during stable conditions at a scheduled visit 2 months after discharge. The patients were stratified using the FEV1 percent-predicted measurement of this visit into mild, moderate and severe in accordance to the ATS, BTS, ERS and GOLD scales of severity. The number of hospitalisations for acute exacerbation was recorded for the following 18 months. A total of 165 exacerbations were recorded. The correlation between the severity of COPD and the number of hospitalisations per year was statistically significant using the GOLD classification system of severity (P = 0.02 and r = 0.294). A weak correlation was also found between the number of hospitalisations and the ERS classification system (P = 0.05 and r = 0.24). No statistically significant correlation was found between the number of hospitalisations and the ATS or BTS severity scales. In conclusion the GOLD and ERS classification systems of severity of COPD correlated to exacerbations causing hospitalisation. The same was not true for the ATS and BTS severity scales. Better correlation was achieved with the GOLD scale.

How should children with speech sound disorders be classified? A review and critical evaluation of current classification systems.

PubMed

Waring, R; Knight, R

2013-01-01

Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of theoretically differing classification systems have been proposed based on either an aetiological (medical) approach, a descriptive-linguistic approach or a processing approach. To describe and review the supporting evidence, and to provide a critical evaluation of the current childhood SSD classification systems. Descriptions of the major specific approaches to classification are reviewed and research papers supporting the reliability and validity of the systems are evaluated. Three specific paediatric SSD classification systems; the aetiologic-based Speech Disorders Classification System, the descriptive-linguistic Differential Diagnosis system, and the processing-based Psycholinguistic Framework are identified as potentially useful in classifying children with SSD into homogeneous subgroups. The Differential Diagnosis system has a growing body of empirical support from clinical population studies, across language error pattern studies and treatment efficacy studies. The Speech Disorders Classification System is currently a research tool with eight proposed subgroups. The Psycholinguistic Framework is a potential bridge to linking cause and surface level speech errors. There is a need for a universally agreed-upon classification system that is useful to clinicians and researchers. The resulting classification system needs to be robust, reliable and valid. A universal classification system would allow for improved tailoring of treatments to subgroups of SSD which may, in turn, lead to improved treatment efficacy. © 2012 Royal College of Speech and Language Therapists.

Dewey Decimal Classification for U. S. Conn: An Advantage?

ERIC Educational Resources Information Center

Marek, Kate

This paper examines the use of the Dewey Decimal Classification (DDC) system at the U. S. Conn Library at Wayne State College (WSC) in Nebraska. Several developments in the last 20 years which have eliminated the trend toward reclassification of academic library collections from DDC to the Library of Congress (LC) classification scheme are…

Comparison of severity classification in Japanese patients with antineutrophil cytoplasmic antibody-associated vasculitis in a nationwide, prospective, inception cohort study.

PubMed

Sada, Ken-Ei; Harigai, Masayoshi; Amano, Koichi; Atsumi, Tatsuya; Fujimoto, Shouichi; Yuzawa, Yukio; Takasaki, Yoshinari; Banno, Shogo; Sugihara, Takahiko; Kobayashi, Masaki; Usui, Joichi; Yamagata, Kunihiro; Homma, Sakae; Dobashi, Hiroaki; Tsuboi, Naotake; Ishizu, Akihiro; Sugiyama, Hitoshi; Okada, Yasunori; Arimura, Yoshihiro; Matsuo, Seiichi; Makino, Hirofumi

2016-09-01

To compare disease severity classification systems for six-month outcome prediction in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Patients with newly diagnosed AAV from 53 tertiary institutions were enrolled. Six-month remission, overall survival, and end-stage renal disease (ESRD)-free survival were evaluated. According to the European Vasculitis Study Group (EUVAS)-defined disease severity, the 321 enrolled patients were classified as follows: 14, localized; 71, early systemic; 170, generalized; and 66, severe disease. According to the rapidly progressive glomerulonephritis (RPGN) clinical grading system, the patients were divided as follows: 60, grade I; 178, grade II; 66, grade III; and 12, grade IV. According to the Five-Factor Score (FFS) 2009, 103, 109, and 109 patients had ≤1, 2, and ≥3 points, respectively. No significant difference in remission rates was found in any severity classification. The overall and ESRD-free survival rates significantly differed between grades I/II, III, and IV, regardless of renal involvement. Severe disease was a good predictor of six-month overall and ESRD-free survival. The FFS 2009 was useful to predict six-month ESRD-free survival but not overall survival. The RPGN grading system was more useful to predict six-month overall and ESRD-free survival than the EUVAS-defined severity or FFS 2009.

Classification systems in nursing: formalizing nursing knowledge and implications for nursing information systems.

PubMed

Goossen, W T; Epping, P J; Abraham, I L

1996-03-01

The development of nursing information systems (NIS) is often hampered by the fact that nursing lacks a unified nursing terminology and classification system. Currently there exist various initiatives in this area. We address the question as to how current initiatives in the development of nursing terminology and classification systems can contribute towards the development of NIS. First, the rationale behind the formalization of nursing knowledge is discussed. Next, using a framework for nursing information processing, the most important developments in the field of nursing on formalization, terminology and classification are critically reviewed. The initiatives discussed include nursing terminology projects in several countries, and the International Classification of Nursing Practice. Suggestions for further developments in the area are discussed. Finally, implications for NIS are presented, as well as the relationships of these components to other sections of an integrated computerized patient record.

Speech Enhancement based on the Dominant Classification Between Speech and Noise Using Feature Data in Spectrogram of Observation Signal

NASA Astrophysics Data System (ADS)

Nomura, Yukihiro; Lu, Jianming; Sekiya, Hiroo; Yahagi, Takashi

This paper presents a speech enhancement using the classification between the dominants of speech and noise. In our system, a new classification scheme between the dominants of speech and noise is proposed. The proposed classifications use the standard deviation of the spectrum of observation signal in each band. We introduce two oversubtraction factors for the dominants of speech and noise, respectively. And spectral subtraction is carried out after the classification. The proposed method is tested on several noise types from the Noisex-92 database. From the investigation of segmental SNR, Itakura-Saito distance measure, inspection of spectrograms and listening tests, the proposed system is shown to be effective to reduce background noise. Moreover, the enhanced speech using our system generates less musical noise and distortion than that of conventional systems.

Reliability testing of two classification systems for osteoarthritis and post-traumatic arthritis of the elbow.

PubMed

Amini, Michael H; Sykes, Joshua B; Olson, Stephen T; Smith, Richard A; Mauck, Benjamin M; Azar, Frederick M; Throckmorton, Thomas W

2015-03-01

The severity of elbow arthritis is one of many factors that surgeons must evaluate when considering treatment options for a given patient. Elbow surgeons have historically used the Broberg and Morrey (BM) and Hastings and Rettig (HR) classification systems to radiographically stage the severity of post-traumatic arthritis (PTA) and primary osteoarthritis (OA). We proposed to compare the intraobserver and interobserver reliability between systems for patients with either PTA or OA. The radiographs of 45 patients were evaluated at least 2 weeks apart by 6 evaluators of different levels of training. Intraobserver and interobserver reliability were calculated by Spearman correlation coefficients with 95% confidence intervals. Agreement was considered almost perfect for coefficients >0.80 and substantial for coefficients of 0.61 to 0.80. In patients with both PTA and OA, intraobserver reliability and interobserver reliability were substantial, with no difference between classification systems. There were no significant differences in intraobserver or interobserver reliability between attending physicians and trainees for either classification system (all P > .10). The presence of fracture implants did not affect reliability in the BM system but did substantially worsen reliability in the HR system (intraobserver P = .04 and interobserver P = .001). The BM and HR classifications both showed substantial intraobserver and interobserver reliability for PTA and OA. Training level differences did not affect reliability for either system. Both trainees and fellowship-trained surgeons may easily and reliably apply each classification system to the evaluation of primary elbow OA and PTA, although the HR system was less reliable in the presence of fracture implants. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

A domains-based taxonomy of supported accommodation for people with severe and persistent mental illness.

PubMed

Siskind, Dan; Harris, Meredith; Pirkis, Jane; Whiteford, Harvey

2013-06-01

A lack of definitional clarity in supported accommodation and the absence of a widely accepted system for classifying supported accommodation models creates barriers to service planning and evaluation. We undertook a systematic review of existing supported accommodation classification systems. Using a structured system for qualitative data analysis, we reviewed the stratification features in these classification systems, identified the key elements of supported accommodation and arranged them into domains and dimensions to create a new taxonomy. The existing classification systems were mapped onto the new taxonomy to verify the domains and dimensions. Existing classification systems used either a service-level characteristic or programmatic approach. We proposed a taxonomy based around four domains: duration of tenure; patient characteristics; housing characteristics; and service characteristics. All of the domains in the taxonomy were drawn from the existing classification structures; however, none of the existing classification structures covered all of the domains in the taxonomy. Existing classification systems are regionally based, limited in scope and lack flexibility. A domains-based taxonomy can allow more accurate description of supported accommodation services, aid in identifying the service elements likely to improve outcomes for specific patient populations, and assist in service planning.

How Should Children with Speech Sound Disorders be Classified? A Review and Critical Evaluation of Current Classification Systems

ERIC Educational Resources Information Center

Waring, R.; Knight, R.

2013-01-01

Background: Children with speech sound disorders (SSD) form a heterogeneous group who differ in terms of the severity of their condition, underlying cause, speech errors, involvement of other aspects of the linguistic system and treatment response. To date there is no universal and agreed-upon classification system. Instead, a number of…

American Association on Mental Retardation's "Definition, Classification, and System of Supports" and Its Relation to International Trends and Issues in the Field of Intellectual Disabilities

ERIC Educational Resources Information Center

Schalock, Robert L.; Luckasson, Ruth

2004-01-01

This article provides an overview of the 2002 American Association on Mental Retardation's (AAMR's) "Definition, Classification, and Systems of Supports" (the 2002 System) and discusses its relationship to salient international trends and several scientific and judgmental issues currently impacting the field of intellectual disabilities (ID). Five…

Prognostic value of computed tomography classification systems for intra-articular calcaneus fractures.

PubMed

Swords, Michael P; Alton, Timothy B; Holt, Sarah; Sangeorzan, Bruce J; Shank, John R; Benirschke, Stephen K

2014-10-01

There are several published computed tomography (CT) classification systems for calcaneus fractures, each validated by a different standard. The goal of this study was to measure which system would best predict clinical outcomes as measured by a widely used and validated musculoskeletal health status questionnaire. Forty-nine patients with isolated intra-articular joint depression calcaneus fractures more than 2 years after treatment were identified. All had preoperative CT studies and were treated with open reduction and plate fixation using a lateral extensile approach. Four different blinded reviewers classified injuries according to the CT classification systems of Crosby and Fitzgibbons, Eastwood, and Sanders. Functional outcomes evaluated with a Musculoskeletal Functional Assessment (MFA). The mean follow-up was 4.3 years. The mean MFA score was 15.7 (SD = 11.6), which is not significantly different from published values for midfoot injuries, hindfoot injuries, or both, 1 year after injury (mean = 22.1, SD = 18.4). The classification systems of Crosby and Fitzgibbons, Eastwood, and Sanders, the number of fragments of the posterior facet, and payer status were not significantly associated with outcome as determined by the MFA. The Sanders classification trended toward significance. Anterior process comminution and surgeon's overall impression of severity were significantly associated with functional outcome. The amount of anterior process comminution was an important determinant of functional outcome with increasing anterior process comminution significantly associated with worsened functional outcome (P = .04). In addition, the surgeon's overall impression of severity of injury was predictive of functional outcome (P = .02), as determined by MFA. Level III, comparative series. © The Author(s) 2014.

Summary of the NICHD-BPCA Pediatric Formulation Initiatives Workshop-Pediatric Biopharmaceutics Classification System (PBCS) Working Group

PubMed Central

Abdel-Rahman, Susan; Amidon, Gordon L.; Kaul, Ajay; Lukacova, Viera; Vinks, Alexander A.; Knipp, Gregory

2012-01-01

The Biopharmaceutics Classification System (BCS) allows compounds to be classified based on their in vitro solubility and intestinal permeability. The BCS has found widespread use in the pharmaceutical community as an enabling guide for the rational selection of compounds, formulation for clinical advancement and generic biowaivers. The Pediatric Biopharmaceutics Classification System (PBCS) working group was convened to consider the possibility of developing an analogous pediatric based classification system. Since there are distinct developmental differences that can alter intestinal contents, volumes, permeability and potentially biorelevant solubilities at the different ages, the PBCS working group focused on identifying age specific issues that would need to be considered in establishing a flexible, yet rigorous PBCS. Objective To summarize the findings of the PBCS working group and provide insights into considerations required for the development of a pediatric based biopharmaceutics classification system. Methods Through several meetings conducted both at The Eunice Kennedy Shriver National Institute of Child Health, Human Development (NICHD)-US Pediatric Formulation Initiative (PFI) workshop (November 2011) and via teleconferences, the PBCS working group considered several high level questions that were raised to frame the classification system. In addition, the PBCS working group identified a number of knowledge gaps that would need to be addressed in order to develop a rigorous PBCS. Results It was determined that for a PBCS to be truly meaningful, it would need to be broken down into several different age groups that would account for developmental changes in intestinal permeability, luminal contents, and gastrointestinal transit. Several critical knowledge gaps where identified including: 1) a lack of fully understanding the ontogeny of drug metabolizing enzymes and transporters along the gastrointestinal (GI) tract, in the liver and in the kidney; 2) an incomplete understanding of age-based changes in the GI, liver and kidney physiology; 3) a clear need to better understand age-based intestinal permeability and fraction absorbed required to develop the PBCS; 4) a clear need for the development and organization of pediatric tissue biobanks to serve as a source for ontogenic research; and 5) a lack of literature published in age-based pediatric pharmacokinetics in order to build Physiologically- and Population-Based Pharmacokinetic (PBPK) databases. Conclusions To begin the process of establishing a PBPK model, ten pediatric therapeutic agents were selected (based on their adult BCS classifications). Those agents should be targeted for additional research in the future. The PBCS working group also identified several areas where a greater emphasis on research is needed to enable the development of a PBCS. PMID:23149009

Soils [Chapter 4.2

Treesearch

Daniel G. Neary; Johannes W. A. Langeveld

2015-01-01

Soils are crucial for profitable and sustainable biomass feedstock production. They provide nutrients and water, give support for plants, and provide habitat for enormous numbers of biota. There are several systems for soil classification. FAO has provided a generic classification system that was used for a global soil map (Bot et al., 2000). The USDA Natural Resources...

Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

PubMed

Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

2016-02-01

Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, p<0.001), with worse dystonia severity implying worse function. Secondary dystonias had worse dystonia and less function than primary dystonias (p<0.001). A longer proportion of life lived with dystonia is associated with more severe dystonia (rs =0.42, p<0.001). The BFM-M is strongly linked with the GMFCS, MACS, and CFCS, irrespective of aetiology. Each scale offers interrelated but complementary information and is applicable to all aetiologies. Movement disorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

Comparisons of severity classification systems for oropharyngeal dysfunction in children with cerebral palsy: Relations with other functional profiles.

PubMed

Goh, Yu-Ra; Choi, Ja Young; Kim, Seon Ah; Park, Jieun; Park, Eun Sook

2018-01-01

This study aimed to investigate the relationships between various classification systems assessing the severity of oropharyngeal dysphagia and communication function and other functional profiles in children with cerebral palsy (CP). This is a prospective, cross-sectional, study in a university-affiliated, tertiary-care hospital. We recruited 151 children with CP (mean age 6.11 years, SD 3.42, range 3-18yr). The Eating and Drinking Ability Classification System (EDACS) and the dysphagia scales of Functional Oral Intake Scale (FOIS), Swallow Function Scales (SFS), and Food Intake Level Scale (FILS) were used. The Communication Function Classification System (CFCS) and Viking Speech Scale (VSS) were employed to classify communication function and speech intelligibility, respectively. The Pediatric Evaluation of Disability Inventory (PEDI) with the Gross Motor Function Classification System (GFMCS) and the Manual Ability Classification System (MACS) level were also assessed. Spearman correlation analysis to investigate the associations between measures and univariate and multivariate logistic regression models to identify significant factors were used. Median GMFCS level of participants was III (interquartile range II-IV). Significant dysphagia based on EDACS level III-V was noted in 23 children (15.2%). There were strong to very strong relationships between the EDACS level with the dysphagia scales. The EDACS presented strong associations with MACS, CFCS, and VSS, a moderate association with GMFCS level, and a moderate to strong association with each domain of the PEDI. In multivariate analysis, poor functioning in EDACS were associated with poor functioning in gross motor and communication functions. Copyright © 2017. Published by Elsevier Ltd.

Modeling and performance of HF/OTH (High-Frequency/Over-the-Horizon) radar target identification systems

NASA Astrophysics Data System (ADS)

Strausberger, Donald J.

Several Radar Target Identification (RTI) techniques have been developed at The Ohio State University in recent years. Using the ElectroScience Laboratory compact range a large database of coherent RCS measurement has been constructed for several types of targets (aircraft, ships, and ground vehicles) at a variety of polarizations, aspect angles, and frequency bands. This extensive database has been used to analyze the performance of several different classification algorithms through the use of computer simulations. In order to optimize classification performance, it was concluded that the radar frequency range should lie in the Rayleigh-resonance frequency range, where the wavelength is on the order of or larger than the target size. For aircraft and ships with general dimensions on the order of 10 meters to 100 meters it is apparent that the High Frequency (HF) band provides optimal classification performance. Since existing HF radars are currently being used for detection and tracking or aircraft and ships of these dimensions, it is natural to further investigate the possibility of using these existing radars as the measurement devices in a radar target classification system.

A Taxonomy of Coordination Mechanisms Used in Real-Time Software Based on Domain Analysis

DTIC Science & Technology

1993-12-01

real - time operating system . CMU/SEI-93-TR-34 3 1.3 Related Work Several taxonomies...coordination methods supported by a real - time operating system is presented by Ripps. The classification of the coordination methods rests upon a set...mechanisms avail- able today. The classification proposed by Ripps [Ripps 89] includes the mechanisms supported by a real - time operating system .

Understanding the use of standardized nursing terminology and classification systems in published research: A case study using the International Classification for Nursing Practice(®).

PubMed

Strudwick, Gillian; Hardiker, Nicholas R

2016-10-01

In the era of evidenced based healthcare, nursing is required to demonstrate that care provided by nurses is associated with optimal patient outcomes, and a high degree of quality and safety. The use of standardized nursing terminologies and classification systems are a way that nursing documentation can be leveraged to generate evidence related to nursing practice. Several widely-reported nursing specific terminologies and classifications systems currently exist including the Clinical Care Classification System, International Classification for Nursing Practice(®), Nursing Intervention Classification, Nursing Outcome Classification, Omaha System, Perioperative Nursing Data Set and NANDA International. However, the influence of these systems on demonstrating the value of nursing and the professions' impact on quality, safety and patient outcomes in published research is relatively unknown. This paper seeks to understand the use of standardized nursing terminology and classification systems in published research, using the International Classification for Nursing Practice(®) as a case study. A systematic review of international published empirical studies on, or using, the International Classification for Nursing Practice(®) were completed using Medline and the Cumulative Index for Nursing and Allied Health Literature. Since 2006, 38 studies have been published on the International Classification for Nursing Practice(®). The main objectives of the published studies have been to validate the appropriateness of the classification system for particular care areas or populations, further develop the classification system, or utilize it to support the generation of new nursing knowledge. To date, most studies have focused on the classification system itself, and a lesser number of studies have used the system to generate information about the outcomes of nursing practice. Based on the published literature that features the International Classification for Nursing Practice, standardized nursing terminology and classification systems appear to be well developed for various populations, settings and to harmonize with other health-related terminology systems. However, the use of the systems to generate new nursing knowledge, and to validate nursing practice is still in its infancy. There is an opportunity now to utilize the well-developed systems in their current state to further what is know about nursing practice, and how best to demonstrate improvements in patient outcomes through nursing care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries.

PubMed

Wangensteen, Arnlaug; Tol, Johannes L; Roemer, Frank W; Bahr, Roald; Dijkstra, H Paul; Crema, Michel D; Farooq, Abdulaziz; Guermazi, Ali

2017-04-01

To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Male athletes (n=40) with clinical diagnosis of acute hamstring injury and MRI ≤5days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. We observed 'substantial' to 'almost perfect' intra- (κ range 0.65-1.00) and interrater reliability (κ range 0.77-1.00) with percentage agreement 83-100% and 88-100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range -0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated 'substantial' to 'almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving Emergency Department Triage Classification with Computerized Clinical Decision Support at a Pediatric Hospital

ERIC Educational Resources Information Center

Kunisch, Joseph Martin

2012-01-01

Background: The Emergency Severity Index (ESI) is an emergency department (ED) triage classification system based on estimated patient-specific resource utilization. Rules for a computerized clinical decision support (CDS) system based on a patient's chief complaint were developed and tested using a stochastic model for predicting ESI scores.…

Clinical Application of Six Current Classification Systems for Iatrogenic Bile Duct Injuries after Cholecystectomy.

PubMed

Velidedeoglu, Mehmet; Arikan, Akif Enes; Uludag, Sezgin Server; Olgun, Deniz Cebi; Kilic, Fahrettin; Kapan, Metin

2015-05-01

Due to being a severe complication, iatrogenic bile duct injury is still a challenging issue for surgeons in gallbladder surgery. However, a commonly accepted classification describing the type of injury has not been available yet. This study aims to evaluate ability of six current classification systems to discriminate bile duct injury patterns. Twelve patients, who were referred to our clinic because of iatrogenic bile duct injury after laparoscopic cholecystectomy were reviewed retrospectively. We described type of injury for each patient according to current six different classifications. 9 patients underwent definitive biliary reconstruction. Bismuth, Strasberg-Bismuth, Stewart-Way and Neuhaus classifications do not consider vascular involvement, Siewert system does, but only for the tangential lesions without structural loss of duct and lesion with a structural defect of hepatic or common bile duct. Siewert, Neuhaus and Stewart-Way systems do not discriminate between lesions at or above bifurcation of the hepatic duct. The Hannover classification may resolve the missing aspects of other systems by describing additional vascular involvement and location of the lesion at or above bifurcation.

Classification of Airflow Limitation Based on z-Score Underestimates Mortality in Patients with Chronic Obstructive Pulmonary Disease.

PubMed

Tejero, Elena; Prats, Eva; Casitas, Raquel; Galera, Raúl; Pardo, Paloma; Gavilán, Adelaida; Martínez-Cerón, Elisabet; Cubillos-Zapata, Carolina; Del Peso, Luis; García-Río, Francisco

2017-08-01

Global Lung Function Initiative recommends reporting lung function measures as z-score, and a classification of airflow limitation (AL) based on this parameter has recently been proposed. To evaluate the prognostic capacity of the AL classifications based on z-score or percentage predicted of FEV 1 in patients with chronic obstructive pulmonary disease (COPD). A cohort of 2,614 patients with COPD recruited outside the hospital setting was examined after a mean (± SD) of 57 ± 13 months of follow-up, totaling 10,322 person-years. All-cause mortality was analyzed, evaluating the predictive capacity of several AL staging systems. Based on Global Initiative for Chronic Obstructive Lung Disease guidelines, 461 patients (17.6%) had mild, 1,452 (55.5%) moderate, 590 (22.6%) severe, and 111 (4.2%) very severe AL. According to z-score classification, 66.3% of patients remained with the same severity, whereas 23.7% worsened and 10.0% improved. Unlike other staging systems, patients with severe AL according to z-score had higher mortality than those with very severe AL (increase of risk by 5.2 and 3.9 times compared with mild AL, respectively). The predictive capacity for 5-year survival was slightly higher for FEV 1 expressed as percentage of predicted than as z-score (area under the curve: 0.714-0.760 vs. 0.649-0.708, respectively). A severity-dependent relationship between AL grades by z-score and mortality was only detected in patients younger than age 60 years. In patients with COPD, the AL classification based on z-score predicts worse mortality than those based on percentage of predicted. It is possible that the z-score underestimates AL severity in patients older than 60 years of age with severe functional impairment.

On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

NASA Technical Reports Server (NTRS)

Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

1997-01-01

The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

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.

ABCD classification system: a novel classification for subaxial cervical spine injuries.

PubMed

Shousha, Mootaz

2014-04-20

The classification system was derived through a retrospective analysis of 73 consecutive cases of subaxial cervical spine injury as well as thorough literature review. To define a new classification system for subaxial cervical spine injuries. There exist several methods to classify subaxial cervical spine injuries but no single system has emerged as clearly superior to the others. On the basis of a 2-column anatomical model, the first part of the proposed classification is an anatomical description of the injury. It delivers the information whether the injury is bony, ligamentous, or a combined one. The first 4 alphabetical letters have been used for simplicity. Each column is represented by an alphabetical letter from A to D. Each letter has a radiological meaning (A = Absent injury, B = Bony lesion, C = Combined bony and ligamentous, D = Disc or ligamentous injury).The second part of the classification is represented by 3 modifiers. These are the neurological status of the patient (N), the degree of spinal canal stenosis (S), and the degree of instability (I). For simplicity, each modifier was graded in an ascending pattern of severity from zero to 2. The last part is optional and denotes which radiological examination has been used to define the injury type. The new ABCD classification was applicable for all patients. The most common type was anterior ligamentous and posterior combined injury "DC" (37.9%), followed by "DD" injury in 12% of the cases. Through this work a new classification for cervical spine injuries is proposed. The aim is to establish criteria for a common language in description of cervical injuries aiming for simplification, especially for junior residents. Each letter and each sign has a meaning to deliver the largest amount of information. Both the radiological as well as the clinical data are represented in this scheme. However, further evaluation of this classification is needed. 3.

Five systems of psychiatric classification for preschool children: do differences in validity, usefulness and reliability make for competitive or complimentary constellations?

PubMed

Postert, Christian; Averbeck-Holocher, Marlies; Beyer, Thomas; Müller, Jörg; Furniss, Tilman

2009-03-01

DSM-IV and ICD-10 have limitations in the diagnostic classification of psychiatric disorders at preschool age (0-5 years). The publication of the Diagnostic Classification 0-3 (DC:0-3) in 1994, its basically revised second edition (DC:0-3R) in 2005 and the Research Diagnostic Criteria-Preschool Age (RDC-PA) in 2004 have provided several modifications of these manuals. Taking into account the growing empirical evidence highlighting the need for a diagnostic classification system for psychiatric disorders in preschool children, the main categorical classification systems in preschool psychiatry will be presented and discussed. The paper will focus on issues of validity, usefulness and reliability in DSM-IV, ICD-10, RDC-PA, DC:0-3, and DC:0-3R. The reasons for including or excluding postulated psychiatric disorder categories for preschool children with variable degrees of empirical evidence into the different diagnostic systems will be discussed.

Taxonomy of asteroids. [according to polarimetric, spectrophotometric, radiometric, and UBV photometric data

NASA Technical Reports Server (NTRS)

Bowell, E.; Chapman, C. R.; Gradie, J. C.; Zellner, B.; Morrison, D.

1978-01-01

A taxonomic system for asteroids is discussed which is based on seven directly observable parameters from polarimetry, spectrophotometry, radiometry, and UBV photometry. The classification scheme is entirely empirical and independent of specific mineralogical interpretations. Five broad classes (designated C, S, M, E, and R), as well as an 'unclassifiable' designation, are defined on the basis of observational data for 523 asteroids. Computer-generated type classifications and derived diameters are given for the 523 asteroids, and the application of the classification procedure is illustrated. Of the 523 asteroids classified, 190 are identified as C objects, 141 as S type, 13 as type M, three as type E, three as type R, 55 as unclassifiable, and 118 as ambiguous. The present taxonomic system is compared with several other asteroid classification systems.

Meta-learning framework applied in bioinformatics inference system design.

PubMed

Arredondo, Tomás; Ormazábal, Wladimir

2015-01-01

This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.

Interobserver reliability of the young-burgess and tile classification systems for fractures of the pelvic ring.

PubMed

Koo, Henry; Leveridge, Mike; Thompson, Charles; Zdero, Rad; Bhandari, Mohit; Kreder, Hans J; Stephen, David; McKee, Michael D; Schemitsch, Emil H

2008-07-01

The purpose of this study was to measure interobserver reliability of 2 classification systems of pelvic ring fractures and to determine whether computed tomography (CT) improves reliability. The reliability of several radiographic findings was also tested. Thirty patients taken from a database at a Level I trauma facility were reviewed. For each patient, 3 radiographs (AP pelvis, inlet, and outlet) and CT scans were available. Six different reviewers (pelvic and acetabular specialist, orthopaedic traumatologist, or orthopaedic trainee) classified the injury according to Young-Burgess and Tile classification systems after reviewing plain radiographs and then after CT scans. The Kappa coefficient was used to determine interobserver reliability of these classification systems before and after CT scan. For plain radiographs, overall Kappa values for the Young-Burgess and Tile classification systems were 0.72 and 0.30, respectively. For CT scan and plain radiographs, the overall Kappa values for the Young-Burgess and Tile classification systems were 0.63 and 0.33, respectively. The pelvis/acetabular surgeons demonstrated the highest level of agreement using both classification systems. For individual questions, the addition of CT did significantly improve reviewer interpretation of fracture stability. The pre-CT and post-CT Kappa values for fracture stability were 0.59 and 0.93, respectively. The CT scan can improve the reliability of assessment of pelvic stability because of its ability to identify anatomical features of injury. The Young-Burgess system may be optimal for the learning surgeon. The Tile classification system is more beneficial for specialists in pelvic and acetabular surgery.

Test Operation Procedure (TOP) 01-1-010A Vehicle Test Course Severity (Surface Roughness)

DTIC Science & Technology

2017-12-12

Department of Agriculture (USDA) classifications, respectively. TABLE 10. PARTICLE SIZE CLASSES CLASS SIZE Cobble and Gravel >4.75 mm particle diameter...ABBREVIATIONS. USCS Unified Soil Classification System USDA United States Department of Agriculture UTM Universal Transverse Mercator WNS wave number

Invertebrate Iridoviruses: A Glance over the Last Decade

PubMed Central

Özcan, Orhan; Ilter-Akulke, Ayca Zeynep; Scully, Erin D.; Özgen, Arzu

2018-01-01

Members of the family Iridoviridae (iridovirids) are large dsDNA viruses that infect both invertebrate and vertebrate ectotherms and whose symptoms range in severity from minor reductions in host fitness to systemic disease and large-scale mortality. Several characteristics have been useful for classifying iridoviruses; however, novel strains are continuously being discovered and, in many cases, reliable classification has been challenging. Further impeding classification, invertebrate iridoviruses (IIVs) can occasionally infect vertebrates; thus, host range is often not a useful criterion for classification. In this review, we discuss the current classification of iridovirids, focusing on genomic and structural features that distinguish vertebrate and invertebrate iridovirids and viral factors linked to host interactions in IIV6 (Invertebrate iridescent virus 6). In addition, we show for the first time how complete genome sequences of viral isolates can be leveraged to improve classification of new iridovirid isolates and resolve ambiguous relations. Improved classification of the iridoviruses may facilitate the identification of genus-specific virulence factors linked with diverse host phenotypes and host interactions. PMID:29601483

Invertebrate Iridoviruses: A Glance over the Last Decade.

PubMed

İnce, İkbal Agah; Özcan, Orhan; Ilter-Akulke, Ayca Zeynep; Scully, Erin D; Özgen, Arzu

2018-03-30

Members of the family Iridoviridae (iridovirids) are large dsDNA viruses that infect both invertebrate and vertebrate ectotherms and whose symptoms range in severity from minor reductions in host fitness to systemic disease and large-scale mortality. Several characteristics have been useful for classifying iridoviruses; however, novel strains are continuously being discovered and, in many cases, reliable classification has been challenging. Further impeding classification, invertebrate iridoviruses (IIVs) can occasionally infect vertebrates; thus, host range is often not a useful criterion for classification. In this review, we discuss the current classification of iridovirids, focusing on genomic and structural features that distinguish vertebrate and invertebrate iridovirids and viral factors linked to host interactions in IIV6 (Invertebrate iridescent virus 6). In addition, we show for the first time how complete genome sequences of viral isolates can be leveraged to improve classification of new iridovirid isolates and resolve ambiguous relations. Improved classification of the iridoviruses may facilitate the identification of genus-specific virulence factors linked with diverse host phenotypes and host interactions.

Lissencephaly: expanded imaging and clinical classification

PubMed Central

Di Donato, Nataliya; Chiari, Sara; Mirzaa, Ghayda M.; Aldinger, Kimberly; Parrini, Elena; Olds, Carissa; Barkovich, A. James; Guerrini, Renzo; Dobyns, William B.

2017-01-01

Lissencephaly (“smooth brain”, LIS) is a malformation of cortical development associated with deficient neuronal migration and abnormal formation of cerebral convolutions or gyri. The LIS spectrum includes agyria, pachygyria, and subcortical band heterotopia. Our first classification of LIS and subcortical band heterotopia (SBH) was developed to distinguish between the first two genetic causes of LIS – LIS1 (PAFAH1B1) and DCX. However, progress in molecular genetics has led to identification of 19 LIS-associated genes, leaving the existing classification system insufficient to distinguish the increasingly diverse patterns of LIS. To address this challenge, we reviewed clinical, imaging and molecular data on 188 patients with LIS-SBH ascertained during the last five years, and reviewed selected archival data on another ~1,400 patients. Using these data plus published reports, we constructed a new imaging based classification system with 21 recognizable patterns that reliably predict the most likely causative genes. These patterns do not correlate consistently with the clinical outcome, leading us to also develop a new scale useful for predicting clinical severity and outcome. Taken together, our work provides new tools that should prove useful for clinical management and genetic counselling of patients with LIS-SBH (imaging and severity based classifications), and guidance for prioritizing and interpreting genetic testing results (imaging based classification). PMID:28440899

Challenges of interoperability using HL7 v3 in Czech healthcare.

PubMed

Nagy, Miroslav; Preckova, Petra; Seidl, Libor; Zvarova, Jana

2010-01-01

The paper describes several classification systems that could improve patient safety through semantic interoperability among contemporary electronic health record systems (EHR-Ss) with support of the HL7 v3 standard. We describe a proposal and a pilot implementation of a semantic interoperability platform (SIP) interconnecting current EHR-Ss by using HL7 v3 messages and concepts mappings on most widely used classification systems. The increasing number of classification systems and nomenclatures requires designing of various conversion tools for transfer between main classification systems. We present the so-called LIM filler module and the HL7 broker, which are parts of the SIP, playing the role of such conversion tools. The analysis of suitability and usability of individual terminological thesauri has been started by mapping of clinical contents of the Minimal Data Model for Cardiology (MDMC) to various terminological classification systems. A national-wide implementation of the SIP would include adopting and translating international coding systems and nomenclatures, and developing implementation guidelines facilitating the migration from national standards to international ones. Our research showed that creation of such a platform is feasible; however, it will require a huge effort to adapt fully the Czech healthcare system to the European environment.

An ordinal classification approach for CTG categorization.

PubMed

Georgoulas, George; Karvelis, Petros; Gavrilis, Dimitris; Stylios, Chrysostomos D; Nikolakopoulos, George

2017-07-01

Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.

Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL) trial: A description of the severity and extent of disease using the Bollinger angiogram scoring method and the TransAtlantic Inter-Society Consensus II classification.

PubMed

Bradbury, Andrew W; Adam, Donald J; Bell, Jocelyn; Forbes, John F; Fowkes, F Gerry R; Gillespie, Ian; Ruckley, Charles Vaughan; Raab, Gillian M

2010-05-01

The Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL) trial showed in patients with severe lower limb ischemia (rest pain, tissue loss) who survive for 2 years after intervention that initial randomization to bypass surgery, compared with balloon angioplasty, was associated with an improvement in subsequent amputation-free survival and overall survival of about 6 and 7 months, respectively. The aim of this report is to describe the angiographic severity and extent of infrainguinal arterial disease in the BASIL trial cohort so that the trial outcomes can be appropriately generalized to other patient cohorts with similar anatomic (angiographic) patterns of disease. Preintervention angiograms were scored using the Bollinger method and the TransAtlantic Inter-Society Consensus (TASC) II classification system by three consultant interventional radiologists and two consultant vascular surgeons unaware of the treatment received or patient outcomes. As was to be expected from the randomization process, patients in the two trial arms were well matched in terms of angiographic severity and extent of disease as documented by Bollinger and TASC II. In patients with the least overall disease, it tended to be concentrated in the superficial femoral and popliteal arteries, which were the commonest sites of disease overall. The below knee arteries became increasingly involved as the overall severity of disease increased, but the disease in the above knee arteries did not tend to worsen. The posterior tibial artery was the most diseased crural artery, whereas the peroneal appeared relatively spared. There was less interobserver disagreement with the Bollinger method than with the TASC II classification system, which also appears inherently less sensitive to clinically important differences in infrapopliteal disease among patients with severe leg ischemia. Anatomic (angiographic) disease description in patients with severe leg ischemia requires a reproducible scoring system that is sensitive to differences in crural artery disease. The Bollinger system appears well suited for this purpose, but the TASC II classification system less so. We hope this detailed analysis will facilitate appropriate generalization of the BASIL trial data to other groups of patients affected by similar anatomic (angiographic) patterns of disease. Crown Copyright (c) 2010. Published by Mosby, Inc. All rights reserved.

Summary of the National Institute of Child Health and Human Development-best pharmaceuticals for Children Act Pediatric Formulation Initiatives Workshop-Pediatric Biopharmaceutics Classification System Working Group.

PubMed

Abdel-Rahman, Susan M; Amidon, Gordon L; Kaul, Ajay; Lukacova, Viera; Vinks, Alexander A; Knipp, Gregory T

2012-11-01

The Biopharmaceutics Classification System (BCS) allows compounds to be classified based on their in vitro solubility and intestinal permeability. The BCS has found widespread use in the pharmaceutical community to be an enabling guide for the rational selection of compounds, formulation for clinical advancement, and generic biowaivers. The Pediatric Biopharmaceutics Classification System (PBCS) Working Group was convened to consider the possibility of developing an analogous pediatric-based classification system. Because there are distinct developmental differences that can alter intestinal contents, volumes, permeability, and potentially biorelevant solubilities at different ages, the PBCS Working Group focused on identifying age-specific issues that need to be considered in establishing a flexible, yet rigorous PBCS. We summarized the findings of the PBCS Working Group and provided insights into considerations required for the development of a PBCS. Through several meetings conducted both at The Eunice Kennedy Shriver National Institute of Child Health, Human Development-US Pediatric Formulation Initiative Workshop (November 2011) and via teleconferences, the PBCS Working Group considered several high-level questions that were raised to frame the classification system. In addition, the PBCS Working Group identified a number of knowledge gaps that need to be addressed to develop a rigorous PBCS. It was determined that for a PBCS to be truly meaningful, it needs to be broken down into several different age groups that account for developmental changes in intestinal permeability, luminal contents, and gastrointestinal (GI) transit. Several critical knowledge gaps were identified, including (1) a lack of fully understanding the ontogeny of drug metabolizing enzymes and transporters along the GI tract, in the liver, and in the kidney; (2) an incomplete understanding of age-based changes in the GI, liver, and kidney physiology; (3) a clear need to better understand age-based intestinal permeability and fraction absorbed required to develop the PBCS; (4) a clear need for the development and organization of pediatric tissue biobanks to serve as a source for ontogenic research; and (5) a lack of literature published in age-based pediatric pharmacokinetics to build physiologically- and population-based pharmacokinetic (PBPK) databases. To begin the process of establishing a PBPK model, 10 pediatric therapeutic agents were selected (based on their adult BCS classifications). These agents should be targeted for additional research in the future. The PBCS Working Group also identified several areas where greater emphasis on research was needed to enable the development of a PBCS. Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.

Impact of Information based Classification on Network Epidemics

PubMed Central

Mishra, Bimal Kumar; Haldar, Kaushik; Sinha, Durgesh Nandini

2016-01-01

Formulating mathematical models for accurate approximation of malicious propagation in a network is a difficult process because of our inherent lack of understanding of several underlying physical processes that intrinsically characterize the broader picture. The aim of this paper is to understand the impact of available information in the control of malicious network epidemics. A 1-n-n-1 type differential epidemic model is proposed, where the differentiality allows a symptom based classification. This is the first such attempt to add such a classification into the existing epidemic framework. The model is incorporated into a five class system called the DifEpGoss architecture. Analysis reveals an epidemic threshold, based on which the long-term behavior of the system is analyzed. In this work three real network datasets with 22002, 22469 and 22607 undirected edges respectively, are used. The datasets show that classification based prevention given in the model can have a good role in containing network epidemics. Further simulation based experiments are used with a three category classification of attack and defense strengths, which allows us to consider 27 different possibilities. These experiments further corroborate the utility of the proposed model. The paper concludes with several interesting results. PMID:27329348

Classification of damage in structural systems using time series analysis and supervised and unsupervised pattern recognition techniques

NASA Astrophysics Data System (ADS)

Omenzetter, Piotr; de Lautour, Oliver R.

2010-04-01

Developed for studying long, periodic records of various measured quantities, time series analysis methods are inherently suited and offer interesting possibilities for Structural Health Monitoring (SHM) applications. However, their use in SHM can still be regarded as an emerging application and deserves more studies. In this research, Autoregressive (AR) models were used to fit experimental acceleration time histories from two experimental structural systems, a 3- storey bookshelf-type laboratory structure and the ASCE Phase II SHM Benchmark Structure, in healthy and several damaged states. The coefficients of the AR models were chosen as damage sensitive features. Preliminary visual inspection of the large, multidimensional sets of AR coefficients to check the presence of clusters corresponding to different damage severities was achieved using Sammon mapping - an efficient nonlinear data compression technique. Systematic classification of damage into states based on the analysis of the AR coefficients was achieved using two supervised classification techniques: Nearest Neighbor Classification (NNC) and Learning Vector Quantization (LVQ), and one unsupervised technique: Self-organizing Maps (SOM). This paper discusses the performance of AR coefficients as damage sensitive features and compares the efficiency of the three classification techniques using experimental data.

On the use of administrative databases to support planning activities: the case of the evaluation of neonatal case-mix in the Emilia-Romagna region using DRG and APR-DRG classification systems.

PubMed

Fantini, M P; Cisbani, L; Manzoli, L; Vertrees, J; Lorenzoni, L

2003-06-01

There are several versions of the Diagnosis Related Group (DRG) classification systems that are used for case-mix analysis, utilization review, prospective payment, and planning applications. The objective of this study was to assess the adequacy of two of these DRG systems--Medicare DRG and All Patient Refined DRG--to classify neonatal patients. The first part of the paper contains a descriptive analysis that outlines the major differences between the two systems in terms of classification logic and variables used in the assignment process. The second part examines the statistical performance of each system on the basis of the administrative data collected in all public hospitals of the Emilia-Romagna region relating to neonates discharged in 1997 and 1998. The Medicare DRG are less developed in terms of classification structure and yield a poorer statistical performance in terms of reduction in variance for length of stay. This is important because, for specific areas, a more refined system can prove useful at regional level to remove systematic biases in the measurement of case-mix due to the structural characteristics of the Medicare DRGs classification system.

On the impact of different approaches to classify age-related macular degeneration: Results from the German AugUR study.

PubMed

Brandl, Caroline; Zimmermann, Martina E; Günther, Felix; Barth, Teresa; Olden, Matthias; Schelter, Sabine C; Kronenberg, Florian; Loss, Julika; Küchenhoff, Helmut; Helbig, Horst; Weber, Bernhard H F; Stark, Klaus J; Heid, Iris M

2018-06-06

While age-related macular degeneration (AMD) poses an important personal and public health burden, comparing epidemiological studies on AMD is hampered by differing approaches to classify AMD. In our AugUR study survey, recruiting residents from in/around Regensburg, Germany, aged 70+, we analyzed the AMD status derived from color fundus images applying two different classification systems. Based on 1,040 participants with gradable fundus images for at least one eye, we show that including individuals with only one gradable eye (n = 155) underestimates AMD prevalence and we provide a correction procedure. Bias-corrected and standardized to the Bavarian population, late AMD prevalence is 7.3% (95% confidence interval = [5.4; 9.4]). We find substantially different prevalence estimates for "early/intermediate AMD" depending on the classification system: 45.3% (95%-CI = [41.8; 48.7]) applying the Clinical Classification (early/intermediate AMD) or 17.1% (95%-CI = [14.6; 19.7]) applying the Three Continent AMD Consortium Severity Scale (mild/moderate/severe early AMD). We thus provide a first effort to grade AMD in a complete study with different classification systems, a first approach for bias-correction from individuals with only one gradable eye, and the first AMD prevalence estimates from a German elderly population. Our results underscore substantial differences for early/intermediate AMD prevalence estimates between classification systems and an urgent need for harmonization.

Wavelet images and Chou's pseudo amino acid composition for protein classification.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2012-08-01

The last decade has seen an explosion in the collection of protein data. To actualize the potential offered by this wealth of data, it is important to develop machine systems capable of classifying and extracting features from proteins. Reliable machine systems for protein classification offer many benefits, including the promise of finding novel drugs and vaccines. In developing our system, we analyze and compare several feature extraction methods used in protein classification that are based on the calculation of texture descriptors starting from a wavelet representation of the protein. We then feed these texture-based representations of the protein into an Adaboost ensemble of neural network or a support vector machine classifier. In addition, we perform experiments that combine our feature extraction methods with a standard method that is based on the Chou's pseudo amino acid composition. Using several datasets, we show that our best approach outperforms standard methods. The Matlab code of the proposed protein descriptors is available at http://bias.csr.unibo.it/nanni/wave.rar .

Muscle Injuries in Sports: A New Evidence-Informed and Expert Consensus-Based Classification with Clinical Application.

PubMed

Valle, Xavier; Alentorn-Geli, Eduard; Tol, Johannes L; Hamilton, Bruce; Garrett, William E; Pruna, Ricard; Til, Lluís; Gutierrez, Josep Antoni; Alomar, Xavier; Balius, Ramón; Malliaropoulos, Nikos; Monllau, Joan Carles; Whiteley, Rodney; Witvrouw, Erik; Samuelsson, Kristian; Rodas, Gil

2017-07-01

Muscle injuries are among the most common injuries in sport and continue to be a major concern because of training and competition time loss, challenging decision making regarding treatment and return to sport, and a relatively high recurrence rate. An adequate classification of muscle injury is essential for a full understanding of the injury and to optimize its management and return-to-play process. The ongoing failure to establish a classification system with broad acceptance has resulted from factors such as limited clinical applicability, and the inclusion of subjective findings and ambiguous terminology. The purpose of this article was to describe a classification system for muscle injuries with easy clinical application, adequate grouping of injuries with similar functional impairment, and potential prognostic value. This evidence-informed and expert consensus-based classification system for muscle injuries is based on a four-letter initialism system: MLG-R, respectively referring to the mechanism of injury (M), location of injury (L), grading of severity (G), and number of muscle re-injuries (R). The goal of the classification is to enhance communication between healthcare and sports-related professionals and facilitate rehabilitation and return-to-play decision making.

New View on the Initial Development Site and Radiographic Classification System of Osteoarthritis of the Knee Based on Radiographic Analysis

PubMed Central

Moon, Ki-Ho

2012-01-01

Introduction: Radiographic pathology of severe osteoarthritis of the knee (OAK) such as severe osteophyte at tibial spine (TS), compartment narrowing, marginal osteophyte, and subchondral sclerosis is well known. Kellgren-Lawrence grading system, which is widely used to diagnose OAK, describes narrowing-marginal osteophyte in 4-grades but uses osteophyte at TS only as evidence of OAK without detailed-grading. However, kinematically the knee employs medial TS as an axis while medial and lateral compartments carry the load, suggesting that early OAK would occur sooner at TS than at compartment. Then, Kellgren-Lawrence system may be inadequate to diagnose early-stage OAK manifested as a subtle osteophyte at TS without narrowing-marginal osteophyte. This undiagnosed-OAK will deteriorate becoming a contributing factor in an increasing incidence of OAK. Methods: This study developed a radiographic OAK-marker based on both osteophyte at TS and compartment narrowing-marginal osteophyte and graded as normal, mild, moderate, and severe. With this marker, both knee radiographs of 1,728 patients with knee pain were analyzed. Results: Among 611 early-stage mild OAK, 562 or 92% started at TS and 49 or 8% at compartment. It suggests the initial development site of OAK, helping develop new site-specific radiographic classification system of OAK accurately to diagnose all severity of OAK at early, intermediate, or late-stage. It showed that Kellgren-Lawrence system missed 92.0% of early-stage mild OAK from diagnosis. Conclusions: A subtle osteophyte at TS is the earliest radiographic sign of OAK. A new radiographic classification system of OAK was suggested for accurate diagnosis of all OAK in severity and at stage. PMID:23675278

New view on the initial development site and radiographic classification system of osteoarthritis of the knee based on radiographic analysis.

PubMed

Moon, Ki-Ho

2012-12-01

Radiographic pathology of severe osteoarthritis of the knee (OAK) such as severe osteophyte at tibial spine (TS), compartment narrowing, marginal osteophyte, and subchondral sclerosis is well known. Kellgren-Lawrence grading system, which is widely used to diagnose OAK, describes narrowing-marginal osteophyte in 4-grades but uses osteophyte at TS only as evidence of OAK without detailed-grading. However, kinematically the knee employs medial TS as an axis while medial and lateral compartments carry the load, suggesting that early OAK would occur sooner at TS than at compartment. Then, Kellgren-Lawrence system may be inadequate to diagnose early-stage OAK manifested as a subtle osteophyte at TS without narrowing-marginal osteophyte. This undiagnosed-OAK will deteriorate becoming a contributing factor in an increasing incidence of OAK. This study developed a radiographic OAK-marker based on both osteophyte at TS and compartment narrowing-marginal osteophyte and graded as normal, mild, moderate, and severe. With this marker, both knee radiographs of 1,728 patients with knee pain were analyzed. Among 611 early-stage mild OAK, 562 or 92% started at TS and 49 or 8% at compartment. It suggests the initial development site of OAK, helping develop new site-specific radiographic classification system of OAK accurately to diagnose all severity of OAK at early, intermediate, or late-stage. It showed that Kellgren-Lawrence system missed 92.0% of early-stage mild OAK from diagnosis. A subtle osteophyte at TS is the earliest radiographic sign of OAK. A new radiographic classification system of OAK was suggested for accurate diagnosis of all OAK in severity and at stage.

Back-and-Forth Methodology for Objective Voice Quality Assessment: From/to Expert Knowledge to/from Automatic Classification of Dysphonia

NASA Astrophysics Data System (ADS)

Fredouille, Corinne; Pouchoulin, Gilles; Ghio, Alain; Revis, Joana; Bonastre, Jean-François; Giovanni, Antoine

2009-12-01

This paper addresses voice disorder assessment. It proposes an original back-and-forth methodology involving an automatic classification system as well as knowledge of the human experts (machine learning experts, phoneticians, and pathologists). The goal of this methodology is to bring a better understanding of acoustic phenomena related to dysphonia. The automatic system was validated on a dysphonic corpus (80 female voices), rated according to the GRBAS perceptual scale by an expert jury. Firstly, focused on the frequency domain, the classification system showed the interest of 0-3000 Hz frequency band for the classification task based on the GRBAS scale. Later, an automatic phonemic analysis underlined the significance of consonants and more surprisingly of unvoiced consonants for the same classification task. Submitted to the human experts, these observations led to a manual analysis of unvoiced plosives, which highlighted a lengthening of VOT according to the dysphonia severity validated by a preliminary statistical analysis.

Evaluating the NOAA Coastal and Marine Ecological Classification Standard in estuarine systems: A Columbia River Estuary case study

NASA Astrophysics Data System (ADS)

Keefer, Matthew L.; Peery, Christopher A.; Wright, Nancy; Daigle, William R.; Caudill, Christopher C.; Clabough, Tami S.; Griffith, David W.; Zacharias, Mark A.

2008-06-01

A common first step in conservation planning and resource management is to identify and classify habitat types, and this has led to a proliferation of habitat classification systems. Ideally, classifications should be scientifically and conceptually rigorous, with broad applicability across spatial and temporal scales. Successful systems will also be flexible and adaptable, with a framework and supporting lexicon accessible to users from a variety of disciplines and locations. A new, continental-scale classification system for coastal and marine habitats—the Coastal and Marine Ecological Classification Standard (CMECS)—is currently being developed for North America by NatureServe and the National Oceanic and Atmospheric Administration (NOAA). CMECS is a nested, hierarchical framework that applies a uniform set of rules and terminology across multiple habitat scales using a combination of oceanographic (e.g. salinity, temperature), physiographic (e.g. depth, substratum), and biological (e.g. community type) criteria. Estuaries are arguably the most difficult marine environments to classify due to large spatio-temporal variability resulting in rapidly shifting benthic and water column conditions. We simultaneously collected data at eleven subtidal sites in the Columbia River Estuary (CRE) in fall 2004 to evaluate whether the estuarine component of CMECS could adequately classify habitats across several scales for representative sites within the estuary spanning a range of conditions. Using outputs from an acoustic Doppler current profiler (ADCP), CTD (conductivity, temperature, depth) sensor, and PONAR (benthic dredge) we concluded that the CMECS hierarchy provided a spatially explicit framework in which to integrate multiple parameters to define macro-habitats at the 100 m 2 to >1000 m 2 scales, or across several tiers of the CMECS system. The classification's strengths lie in its nested, hierarchical structure and in the development of a standardized, yet flexible classification lexicon. The application of the CMECS to other estuaries in North America should therefore identify similar habitat types at similar scales as we identified in the CRE. We also suggest that the CMECS could be improved by refining classification thresholds to better reflect ecological processes, by direct integration of temporal variability, and by more explicitly linking physical and biological processes with habitat patterns.

Comparing the predictive value of the pelvic ring injury classification systems by Tile and by Young and Burgess.

PubMed

Osterhoff, Georg; Scheyerer, Max J; Fritz, Yannick; Bouaicha, Samy; Wanner, Guido A; Simmen, Hans-Peter; Werner, Clément M L

2014-04-01

Radiology-based classifications of pelvic ring injuries and their relevance for the prognosis of morbidity and mortality are disputed in the literature. The purpose of this study was to evaluate potential differences between the pelvic ring injury classification systems by Tile and by Young and Burgess with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Two-hundred-and-eighty-five consecutive patients with pelvic ring fractures were analyzed for mortality within 30 days after admission, number of blood units and total volume of fluid infused during the first 24h after trauma, the Abbreviated Injury Severity (AIS) scores for head, chest, spine, abdomen and extremities as a function of the Tile and the Young-Burgess classifications. There was no significant relationship between occurrence of death and fracture pattern but a significant relationship between fracture pattern and need for blood units/total fluid volume for Tile (p<.001/p<.001) and Young-Burgess (p<.001/p<.001). In both classifications, open book fractures were associated with more fluid requirement and more severe injuries of the abdomen, spine and extremities (p<.05). When divided into the larger subgroups "partially stable" and "unstable", unstable fractures were associated with a higher mortality rate in the Young-Burgess system (p=.036). In both classifications, patients with unstable fractures required significantly more blood transfusions (p<.001) and total fluid infusion (p<.001) and higher AIS scores. In this first direct comparison of both classifications, we found no clinical relevant differences with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of Classification Methods for Forecasting Mid-Term Power Load Patterns

NASA Astrophysics Data System (ADS)

Piao, Minghao; Lee, Heon Gyu; Park, Jin Hyoung; Ryu, Keun Ho

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed approach in this paper consists of three stages: (i) data preprocessing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

Osteochondritis dissecans of the humeral capitellum: reliability of four classification systems using radiographs and computed tomography.

PubMed

Claessen, Femke M A P; van den Ende, Kimberly I M; Doornberg, Job N; Guitton, Thierry G; Eygendaal, Denise; van den Bekerom, Michel P J

2015-10-01

The radiographic appearance of osteochondritis dissecans (OCD) of the humeral capitellum varies according to the stage of the lesion. It is important to evaluate the stage of OCD lesion carefully to guide treatment. We compared the interobserver reliability of currently used classification systems for OCD of the humeral capitellum to identify the most reliable classification system. Thirty-two musculoskeletal radiologists and orthopaedic surgeons specialized in elbow surgery from several countries evaluated anteroposterior and lateral radiographs and corresponding computed tomography (CT) scans of 22 patients to classify the stage of OCD of the humeral capitellum according to the classification systems developed by (1) Minami, (2) Berndt and Harty, (3) Ferkel and Sgaglione, and (4) Anderson on a Web-based study platform including a Digital Imaging and Communications in Medicine viewer. Magnetic resonance imaging was not evaluated as part of this study. We measured agreement among observers using the Siegel and Castellan multirater κ. All OCD classification systems, except for Berndt and Harty, which had poor agreement among observers (κ = 0.20), had fair interobserver agreement: κ was 0.27 for the Minami, 0.23 for Anderson, and 0.22 for Ferkel and Sgaglione classifications. The Minami Classification was significantly more reliable than the other classifications (P < .001). The Minami Classification was the most reliable for classifying different stages of OCD of the humeral capitellum. However, it is unclear whether radiographic evidence of OCD of the humeral capitellum, as categorized by the Minami Classification, guides treatment in clinical practice as a result of this fair agreement. Copyright © 2015 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Staging of chronic myeloid leukemia in the imatinib era: an evaluation of the World Health Organization proposal.

PubMed

Cortes, Jorge E; Talpaz, Moshe; O'Brien, Susan; Faderl, Stefan; Garcia-Manero, Guillermo; Ferrajoli, Alessandra; Verstovsek, Srdan; Rios, Mary B; Shan, Jenny; Kantarjian, Hagop M

2006-03-15

Several staging classification systems, all of which were designed in the preimatinib era, are used for chronic myeloid leukemia (CML). The World Health Organization (WHO) recently proposed a new classification system that has not been validated clinically. The authors investigated the significance of the WHO classification system and compared it with the classification systems used to date in imatinib trials ("standard definition") to determine its impact in establishing the outcome of patients after therapy with imatinib. In total, 809 patients who received imatinib for CML were classified into chronic phase (CP), accelerated phase (AP), and blast phase (BP) based on standard definitions and then were reclassified according to the new WHO classification system. Their outcomes with imatinib therapy were compared, and the value of individual components of these classification systems was determined. With the WHO classification, 78 patients (10%) were reclassified: 45 patients (6%) were reclassified from CP to AP, 14 patients (2%) were reclassified from AP to CP, and 19 patients (2%) were reclassified from AP to BP. The rates of complete cytogenetic response for patients in CP, AP, and BP according to the standard definition were 72%, 45%, and 8%, respectively. After these patients were reclassified according to WHO criteria, the response rates were 77% (P = 0.07), 39% (P = 0.28), and 11% (P = 0.61), respectively. The 3-year survival rates were 91%, 65%, and 10%, respectively, according to the standard classification and 95% (P = 0.05), 63% (P = 0.76), and 16% (P = 0.18), respectively, according to the WHO classification. Patients who had a blast percentage of 20-29%, which is considered CML-BP according to the WHO classification, had a significantly better response rate (21% vs. 8%; P = 0.11) and 3-year survival rate (42% vs. 10%; P = 0.0001) compared with patients who had blasts > or = 30%. Different classification systems had an impact on the outcome of patients, and some prognostic features had different prognostic implications in the imatinib era. The authors believe that a new, uniform staging system for CML is warranted, and they propose such a system. (c) 2006 American Cancer Society.

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

Evolution and classification of the CRISPR-Cas systems

PubMed Central

S. Makarova, Kira; H. Haft, Daniel; Barrangou, Rodolphe; J. J. Brouns, Stan; Charpentier, Emmanuelle; Horvath, Philippe; Moineau, Sylvain; J. M. Mojica, Francisco; I. Wolf, Yuri; Yakunin, Alexander F.; van der Oost, John; V. Koonin, Eugene

2012-01-01

The CRISPR–Cas (clustered regularly interspaced short palindromic repeats–CRISPR-associated proteins) modules are adaptive immunity systems that are present in many archaea and bacteria. These defence systems are encoded by operons that have an extraordinarily diverse architecture and a high rate of evolution for both the cas genes and the unique spacer content. Here, we provide an updated analysis of the evolutionary relationships between CRISPR–Cas systems and Cas proteins. Three major types of CRISPR–Cas system are delineated, with a further division into several subtypes and a few chimeric variants. Given the complexity of the genomic architectures and the extremely dynamic evolution of the CRISPR–Cas systems, a unified classification of these systems should be based on multiple criteria. Accordingly, we propose a `polythetic' classification that integrates the phylogenies of the most common cas genes, the sequence and organization of the CRISPR repeats and the architecture of the CRISPR–cas loci. PMID:21552286

The classification based on intrahepatic portal system for congenital portosystemic shunts.

PubMed

Kanazawa, Hiroyuki; Nosaka, Shunsuke; Miyazaki, Osamu; Sakamoto, Seisuke; Fukuda, Akinari; Shigeta, Takanobu; Nakazawa, Atsuko; Kasahara, Mureo

2015-04-01

Liver transplantation was previously indicated as a curative operation for congenital absence of portal vein. Recent advances in radiological interventional techniques can precisely visualize the architecture of the intrahepatic portal system (IHPS). Therefore, the therapeutic approach for congenital portosystemic shunt (CPS) needs to be reevaluated from a viewpoint of radiological appearances. The aim of this study was to propose the IHPS classification which could explain the pathophysiological characteristics and play a complementary role of a therapeutic approach and management for CPS. Nineteen patients with CPS were retrospectively reviewed. The median age at diagnosis was 6.8 years old. Eighteen of these patients underwent angiography with a shunt occlusion test and were classified based of the severity of the hypoplasia of IHPS. The eighteen cases who could undergo the shunt occlusion test were classified into mild (n=7), moderate (n=6) and severe types (n=5) according to the IHPS classification. The IHPS classification correlated with the portal venous pressure under shunt occlusion, the histopathological findings, postoperative portal venous flow and liver regeneration. Shunt closure resulted in dramatic improvement in the laboratory data and subclinical encephalopathy. Two patients with the severe type suffered from sepsis associated with portal hypertension after treatment, and from the portal flow steal phenomenon because of the development of unexpected collateral vessels. The patients with the severe type had a high risk of postoperative complications after shunt closure in one step, even if the PVP was relatively low during the shunt occlusion test. The IHPS could be visualized by the shunt occlusion test. The IHPS classification reflected the clinicopathological features of CPS, and was useful to determine the therapeutic approach and management for CPS. Copyright © 2015 Elsevier Inc. All rights reserved.

Association Between Severity and the Determinant-Based Classification, Atlanta 2012 and Atlanta 1992, in Acute Pancreatitis

PubMed Central

Chen, Yuhui; Ke, Lu; Tong, Zhihui; Li, Weiqin; Li, Jieshou

2015-01-01

Abstract Recently, the determinant-based classification (DBC) and the Atlanta 2012 have been proposed to provide a basis for study and treatment of acute pancreatitis (AP). The present study aimed to evaluate the association between severity and the DBC, the Atlanta 2012 and the Atlanta 1992, in AP. Patients admitted to our center with AP from January 2007 to July 2013 were reviewed retrospectively. Patients were assigned to severity categories for all the 3 classification systems. The primary outcomes include long-term clinical prognosis (mortality and length-of-hospital stay), major complications (intraabdominal hemorrhage, multiple-organ dysfunction, single organ failure [OF], and sepsis) and clinical interventions (surgical drainage, continuous renal replace therapy [CRRT] lasting time, and mechanical ventilation [MV] lasting time). The classification systems were validated and compared in terms of these abovementioned primary outcomes. A total of 395 patients were enrolled in this retrospective study with an overall 8.86% in-hospital mortality. Intraabdominal hemorrhage was present in 27 (6.84%) of the patients, multiple-organ dysfunction in 73(18.48%), single OF in 67 (16.96%), and sepsis in 73(18.48%). For each classification system, different categories regarding severity were associated with statistically different clinical mortality, major complications, and clinical interventions (P < 0.05). However, the Atlanta 2012 and the DBC performed better than the Atlanta 1992, and they were comparable in predicting mortality (area under curve [AUC] 0.899 and 0.955 vs 0.585, P < 0.05); intraabdominal hemorrhage (AUC 0.930 and 0.961 vs 0.583, P < 0.05), multiple-organ dysfunction (AUC 0.858 and 0.881 vs 0.595, P < 0.05), sepsis (AUC 0.826 and 0.879 vs 0.590, P < 0.05), and surgical drainage (AUC 0.900 and 0.847 vs 0.606, P < 0.05). For continuous variables, the Atlanta 2012 and the DBC were also better than the Atlanta 1992, and they were similar in predicting CRRT lasting time (Somer D 0.379 and 0.360 vs 0.210, P < 0.05) and MV lasting time (Somer D 0.344 and 0.336 vs 0.186, P < 0.05). All the 3 classification systems accurately classify the severity of AP. However, the Atlanta 2012 and the DBC performed better than the Atlanta 1992, and they were comparable in predicting long-term clinical prognosis, major complications, and clinical interventions. PMID:25837754

Update and validation of the Society for Vascular Surgery wound, ischemia, and foot infection threatened limb classification system.

PubMed

Mills, Joseph L

2014-03-01

The diagnosis of critical limb ischemia, first defined in 1982, was intended to delineate a patient cohort with a threatened limb and at risk for amputation due to severe peripheral arterial disease. The influence of diabetes and its associated neuropathy on the pathogenesis-threatened limb was an excluded comorbidity, despite its known contribution to amputation risk. The Fontaine and Rutherford classifications of limb ischemia severity have also been used to predict amputation risk and the likelihood of tissue healing. The dramatic increase in the prevalence of diabetes mellitus and the expanding techniques of arterial revascularization has prompted modification of peripheral arterial disease classification schemes to improve outcomes analysis for patients with threatened limbs. The diabetic patient with foot ulceration and infection is at risk for limb loss, with abnormal arterial perfusion as only one determinant of outcome. The wound extent and severity of infection also impact the likelihood of limb loss. To better predict amputation risk, the Society for Vascular Surgery Lower Extremity Guidelines Committee developed a classification of the threatened lower extremity that reflects these important clinical considerations. Risk stratification is based on three major factors that impact amputation risk and clinical management: wound, ischemia, and foot infection. This classification scheme is relevant to the patient with critical limb ischemia because many are also diabetic. Implementation of the wound, ischemia, and foot infection classification system in critical limb ischemia patients is recommended and should assist the clinician in more meaningful analysis of outcomes for various forms of wound and arterial revascularizations procedures required in this challenging, patient population. Copyright © 2014 Elsevier Inc. All rights reserved.

Study of USGS/NASA land use classification system. [computer analysis from LANDSAT data

NASA Technical Reports Server (NTRS)

Spann, G. W.

1975-01-01

The results of a computer mapping project using LANDSAT data and the USGS/NASA land use classification system are summarized. During the computer mapping portion of the project, accuracies of 67 percent to 79 percent were achieved using Level II of the classification system and a 4,000 acre test site centered on Douglasville, Georgia. Analysis of response to a questionaire circulated to actual and potential LANDSAT data users reveals several important findings: (1) there is a substantial desire for additional information related to LANDSAT capabilities; (2) a majority of the respondents feel computer mapping from LANDSAT data could aid present or future projects; and (3) the costs of computer mapping are substantially less than those of other methods.

Major morbidity after video-assisted thoracic surgery lung resections: a comparison between the European Society of Thoracic Surgeons definition and the Thoracic Morbidity and Mortality system.

PubMed

Sandri, Alberto; Papagiannopoulos, Kostas; Milton, Richard; Kefaloyannis, Emmanuel; Chaudhuri, Nilanjan; Poyser, Emily; Spencer, Nicholas; Brunelli, Alessandro

2015-07-01

The thoracic morbidity and mortality (TM&M) classification system univocally encodes the postoperative adverse events by their management complexity. This study aims to compare the distribution of the severity of complications according to the TM&M system versus the distribution according to the classification proposed by European Society of Thoracic Surgeons (ESTS) Database in a population of patients submitted to video assisted thoracoscopic surgery (VATS) lung resection. A total of 227 consecutive patients submitted to VATS lobectomy for lung cancer were analyzed. Any complication developed postoperatively was graded from I to V according to the TM&M system, reflecting the increasing severity of its management. We verified the distribution of the different grades of complications and analyzed their frequency among those defined as "major cardiopulmonary complications" by the ESTS Database. Following the ESTS definitions, 20 were the major cardiopulmonary complications [atrial fibrillation (AF): 10, 50%; adult respiratory distress syndrome (ARDS): 1, 5%; pulmonary embolism: 2, 10%; mechanical ventilation >24 h: 1, 5%; pneumonia: 3, 15%; myocardial infarct: 1, 5%; atelectasis requiring bronchoscopy: 2, 10%] of which 9 (45%) were reclassified as minor complications (grade II) by the TM&M classification system. According to the TM&M system, 10/34 (29.4%) of all complications were considered minor (grade I or II) while 21/34 (71.4%) as major (IIIa: 8, 23.5%; IIIb: 4, 11.7%; IVa: 8, 23.5%; IVb: 1, 2.9%; V: 3, 8.8%). Other 14 surgical complications occurred and were classified as major complications according to the TM&M system. The distribution of postoperative complications differs between the two classification systems. The TM&M grading system questions the traditional classification of major complications following VATS lung resection and may be used as an additional endpoint for outcome analyses.

Intrarater and interrater reliability and validity in the assessment of the mechanism of injury and integrity of the posterior ligamentous complex: a novel injury severity scoring system for thoracolumbar injuries. Invited submission from the Joint Section Meeting On Disorders of the Spine and Peripheral Nerves, March 2005.

PubMed

Harrop, James S; Vaccaro, Alexander R; Hurlbert, R John; Wilsey, Jared T; Baron, Eli M; Shaffrey, Christopher I; Fisher, Charles G; Dvorak, Marcel F; Oner, F C; Wood, Kirkham B; Anand, Neel; Anderson, D Greg; Lim, Moe R; Lee, Joon Y; Bono, Christopher M; Arnold, Paul M; Rampersaud, Y Raja; Fehlings, Michael G

2006-02-01

A new classification and treatment algorithm for thoracolumbar injuries was recently introduced by Vaccaro and colleagues in 2005. A thoracolumbar injury severity scale (TLISS) was proposed for grading and guiding treatment for these injuries. The scale is based on the following: 1) the mechanism of injury; 2) the integrity of the posterior ligamentous complex (PLC); and 3) the patient's neurological status. The reliability and validity of assessing injury mechanism and the integrity of the PLC was assessed. Forty-eight spine surgeons, consisting of neurosurgeons and orthopedic surgeons, reviewed 56 clinical thoracolumbar injury case histories. Each was classified and scored to determine treatment recommendations according to a novel classification system. After 3 months the case histories were reordered and the physicians repeated the exercise. Validity of this classification was good among reviewers; the vast majority (> 90%) agreed with the system's treatment recommendations. Surgeons were unclear as to a cogent description of PLC disruption and fracture mechanism. The TLISS demonstrated acceptable reliability in terms of intra- and interobserver agreement on the algorithm's treatment recommendations. Replacing injury mechanism with a description of injury morphology and better definition of PLC injury will improve inter- and intraobserver reliability of this injury classification system.

Classification and evaluation for forest sites in the Cumberland Mountains

Treesearch

Glendon W. Smalley

1984-01-01

This report classifies and evaluates forest sites in the Cumberland Mountains (fig. 1) for the management of several commercially valuable tree species. It provides forest managers with a land classification system that will enable them to subdivide forest land into logical segments (landtypes), allow them to rate productivity, and alert them to any limitations and...

Rule-driven defect detection in CT images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2000-01-01

This paper deals with automated detection and identification of internal defects in hardwood logs using computed tomography (CT) images. We have developed a system that employs artificial neural networks to perform tentative classification of logs on a pixel-by-pixel basis. This approach achieves a high level of classification accuracy for several hardwood species (...

Feeding and gastrointestinal problems in children with cerebral palsy.

PubMed

Erkin, Gulten; Culha, Canan; Ozel, Sumru; Kirbiyik, Eylem Gulsen

2010-09-01

The aim of our study was to identify feeding and gastrointestinal system (GIS) problems in children with cerebral palsy (CP), and to evaluate the relationship between these problems and the severity of CP. A total of 120 children with CP were enrolled consecutively into the study (67 males, 53 females; mean age: 6.0±2.4 years; range: 2-12 years). The children were classified according to the Swedish classification as diplegic, hemiplegic, or quadriplegic. Severity of CP was classified based on the Gross Motor Function Classification System. The amount of time that the caregiver allocated to mealtimes, modifications of the food, as well as feeding and GIS problems was evaluated. Feeding dysfunction was classified as mild, moderate, or severe. Comparisons of GIS and feeding disorders and the severity of CP were carried out using χ test. The results indicated lack of appetite in 46 of the 120 children (38.3%), sialorrhea in 37 (30.8%), constipation in 30 (25%), difficulty in swallowing in 23 (19.2%), and feeding dysfunction in 26 (21.7%). On the basis of the Gross Motor Function Classification System (GMFCS), the incidence of GIS problems and feeding dysfunction was found to be significantly higher in the children classified in the severe group. The time taken to consume meals was significantly longer among children with feeding dysfunction. Feeding and GIS problems are frequent in children with CP, and more marked in those with severe CP. Approximately one fourth of children with CP suffer from feeding dysfunction, and more time has to be allocated to consume meals.

Empirical Wavelet Transform Based Features for Classification of Parkinson's Disease Severity.

PubMed

Oung, Qi Wei; Muthusamy, Hariharan; Basah, Shafriza Nisha; Lee, Hoileong; Vijean, Vikneswaran

2017-12-29

Parkinson's disease (PD) is a type of progressive neurodegenerative disorder that has affected a large part of the population till now. Several symptoms of PD include tremor, rigidity, slowness of movements and vocal impairments. In order to develop an effective diagnostic system, a number of algorithms were proposed mainly to distinguish healthy individuals from the ones with PD. However, most of the previous works were conducted based on a binary classification, with the early PD stage and the advanced ones being treated equally. Therefore, in this work, we propose a multiclass classification with three classes of PD severity level (mild, moderate, severe) and healthy control. The focus is to detect and classify PD using signals from wearable motion and audio sensors based on both empirical wavelet transform (EWT) and empirical wavelet packet transform (EWPT) respectively. The EWT/EWPT was applied to decompose both speech and motion data signals up to five levels. Next, several features are extracted after obtaining the instantaneous amplitudes and frequencies from the coefficients of the decomposed signals by applying the Hilbert transform. The performance of the algorithm was analysed using three classifiers - K-nearest neighbour (KNN), probabilistic neural network (PNN) and extreme learning machine (ELM). Experimental results demonstrated that our proposed approach had the ability to differentiate PD from non-PD subjects, including their severity level - with classification accuracies of more than 90% using EWT/EWPT-ELM based on signals from motion and audio sensors respectively. Additionally, classification accuracy of more than 95% was achieved when EWT/EWPT-ELM is applied to signals from integration of both signal's information.

Classification of upper limb disability levels of children with spastic unilateral cerebral palsy using K-means algorithm.

PubMed

Raouafi, Sana; Achiche, Sofiane; Begon, Mickael; Sarcher, Aurélie; Raison, Maxime

2018-01-01

Treatment for cerebral palsy depends upon the severity of the child's condition and requires knowledge about upper limb disability. The aim of this study was to develop a systematic quantitative classification method of the upper limb disability levels for children with spastic unilateral cerebral palsy based on upper limb movements and muscle activation. Thirteen children with spastic unilateral cerebral palsy and six typically developing children participated in this study. Patients were matched on age and manual ability classification system levels I to III. Twenty-three kinematic and electromyographic variables were collected from two tasks. Discriminative analysis and K-means clustering algorithm were applied using 23 kinematic and EMG variables of each participant. Among the 23 kinematic and electromyographic variables, only two variables containing the most relevant information for the prediction of the four levels of severity of spastic unilateral cerebral palsy, which are fixed by manual ability classification system, were identified by discriminant analysis: (1) the Falconer index (CAI E ) which represents the ratio of biceps to triceps brachii activity during extension and (2) the maximal angle extension (θ Extension,max ). A good correlation (Kendall Rank correlation coefficient = -0.53, p = 0.01) was found between levels fixed by manual ability classification system and the obtained classes. These findings suggest that the cost and effort needed to assess and characterize the disability level of a child can be further reduced.

[Classification of memory systems: a revision].

PubMed

Agrest, M

2001-12-01

The present paper exposes the arguments against considering memory as a monolytic entity and how is it to be divided into several systems in order to understand its operation. Historically this division was acknowledge by different authors but in the last few decades it received the confirmation from the scientific research. The most accepted taxonomy establishes the existence of two major memory systems: declarative and non declarative memory. The article also presents the arguments for and against this kind of division, as well as an alternative classification in five major systems: procedural, perceptual representation, semantic, primary and episodic.

Cognitive-motivational deficits in ADHD: development of a classification system.

PubMed

Gupta, Rashmi; Kar, Bhoomika R; Srinivasan, Narayanan

2011-01-01

The classification systems developed so far to detect attention deficit/hyperactivity disorder (ADHD) do not have high sensitivity and specificity. We have developed a classification system based on several neuropsychological tests that measure cognitive-motivational functions that are specifically impaired in ADHD children. A total of 240 (120 ADHD children and 120 healthy controls) children in the age range of 6-9 years and 32 Oppositional Defiant Disorder (ODD) children (aged 9 years) participated in the study. Stop-Signal, Task-Switching, Attentional Network, and Choice Delay tests were administered to all the participants. Receiver operating characteristic (ROC) analysis indicated that percentage choice of long-delay reward best classified the ADHD children from healthy controls. Single parameters were not helpful in making a differential classification of ADHD with ODD. Multinominal logistic regression (MLR) was performed with multiple parameters (data fusion) that produced improved overall classification accuracy. A combination of stop-signal reaction time, posterror-slowing, mean delay, switch cost, and percentage choice of long-delay reward produced an overall classification accuracy of 97.8%; with internal validation, the overall accuracy was 92.2%. Combining parameters from different tests of control functions not only enabled us to accurately classify ADHD children from healthy controls but also in making a differential classification with ODD. These results have implications for the theories of ADHD.

Injuries from Intimate Partner and Sexual Violence: Significance and Classification Systems

PubMed Central

Sommers, Marilyn S.; Brunner, Lillian S.; Brown, Kathleen M.; Buschur, Carole; Everett, Janine S.; Fargo, Jamison D.; Fisher, Bonnie S.; Hinkle, Christina; Zink, Therese M.

2012-01-01

While intimate partner violence (IPV) and sexual violence (SV) are highly associated with injury, the healthcare and legal significance of these injuries is controversial. Purpose: Herein we propose to explore the significance of injury in IPV and SV and examine the current status of injury classification systems from the perspectives of the healthcare and criminal justice systems. We will review current injury classification systems and suggest a typology of injury that could be tested empirically. Findings: Within the published literature, we found that no commonly-accepted injury typology exists. While nuanced and controversial issues surround the role of injury detection in the sexual assault forensic examination, enough evidence exists to support the continued pursuance of a scientific approach to injury classification. We propose an injury typology that is measureable, is applicable to the healthcare setting and criminal justice system, and allows us to use uses a matrix approach that includes a severity score, anatomic location, and injury type. We suggest a typology that might be used for further empirical testing on the validity and reliability of IPV and SV injury data. Conclusion: We recommend that the community of scientists concerned about IPV and SV develop a more rigorous injury classification system that will improve the quality of forensic evidence proffered and decisions made throughout the criminal justice process. PMID:22687765

Proposal for a functional classification system of heart failure in patients with end-stage renal disease: proceedings of the acute dialysis quality initiative (ADQI) XI workgroup.

PubMed

Chawla, Lakhmir S; Herzog, Charles A; Costanzo, Maria Rosa; Tumlin, James; Kellum, John A; McCullough, Peter A; Ronco, Claudio

2014-04-08

Structural heart disease is highly prevalent in patients with chronic kidney disease requiring dialysis. More than 80% of patients with end-stage renal disease (ESRD) are reported to have cardiovascular disease. This observation has enormous clinical relevance because the leading causes of death for patients with ESRD are of cardiovascular disease etiology, including heart failure, myocardial infarction, and sudden cardiac death. The 2 systems most commonly used to classify the severity of heart failure are the New York Heart Association (NYHA) functional classification and the American Heart Association (AHA)/American College of Cardiology (ACC) staging system. With rare exceptions, patients with ESRD who do not receive renal replacement therapy (RRT) develop signs and symptoms of heart failure, including dyspnea and edema due to inability of the severely diseased kidneys to excrete sodium and water. Thus, by definition, nearly all patients with ESRD develop a symptomatology consistent with heart failure if fluid removal by RRT is delayed. Neither the AHA/ACC heart failure staging nor the NYHA functional classification system identifies the variable symptomatology that patients with ESRD experience depending upon whether evaluation occurs before or after fluid removal by RRT. Consequently, the incidence, severity, and outcomes of heart failure in patients with ESRD are poorly characterized. The 11th Acute Dialysis Quality Initiative has identified this issue as a critical unmet need for the proper evaluation and treatment of heart failure in patients with ESRD. We propose a classification schema based on patient-reported dyspnea assessed both pre- and post-ultrafiltration, in conjunction with echocardiography. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

[GRADE system: classification of quality of evidence and strength of recommendation].

PubMed

Aguayo-Albasini, José Luis; Flores-Pastor, Benito; Soria-Aledo, Víctor

2014-02-01

The acquisition and classification of scientific evidence, and subsequent formulation of recommendations constitute the basis for the development of clinical practice guidelines. There are several systems for the classification of evidence and strength of recommendations; the most commonly used nowadays is the Grading of Recommendations, Assessment, Development and Evaluation system (GRADE). The GRADE system initially classifies the evidence into high or low, coming from experimental or observational studies; subsequently and following a series of considerations, the evidence is classified into high, moderate, low or very low. The strength of recommendations is based not only on the quality of the evidence, but also on a series of factors such as the risk/benefit balance, values and preferences of the patients and professionals, and the use of resources or costs. Copyright © 2013 AEC. Published by Elsevier Espana. All rights reserved.

Low-cost real-time automatic wheel classification system

NASA Astrophysics Data System (ADS)

Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

1992-11-01

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

Classifications for Cesarean Section: A Systematic Review

PubMed Central

Torloni, Maria Regina; Betran, Ana Pilar; Souza, Joao Paulo; Widmer, Mariana; Allen, Tomas; Gulmezoglu, Metin; Merialdi, Mario

2011-01-01

Background Rising cesarean section (CS) rates are a major public health concern and cause worldwide debates. To propose and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification. Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1) identify the main CS classifications used worldwide, 2) analyze advantages and deficiencies of each system. Methods and Findings Three electronic databases were searched for classifications published 1968–2008. Two reviewers independently assessed classifications using a form created based on items rated as important by international experts. Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of categories, reproducibility, implementability) were assessed and graded. Classifications were tested in 12 hypothetical clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications identified. Indications classifications present important limitations and their overall score ranged from 2–9 (maximum grade = 14). Degree of urgency classifications also had several drawbacks (overall scores 6–9). Woman-based classifications performed best (scores 5–14). Other types of classifications require data not routinely collected and may not be relevant in all settings (scores 3–8). Conclusions This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and Robson's classification, in particular, would be in the best position to fulfill current international and local needs and that efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this classification. The use of a single CS classification will facilitate auditing, analyzing and comparing CS rates across different settings and help to create and implement effective strategies specifically targeted to optimize CS rates where necessary. PMID:21283801

The debate over diagnosis related groups.

PubMed

Spiegel, A D; Kavaler, F

1985-01-01

With the advent of the Prospective Payment System (PPS) using Diagnosis Related Groups (DRGs) as a classification method, the pros and cons of that mechanism have been sharply debated. Grouping the comments into categories related to administration/management, DRG system and quality of care, a review of relevant literature highlights the pertinent attitudes and views of professionals and organizations. Points constantly argued include data utilization, meaningful medical classifications, resource use, gaming, profit centers, patient homogeneity, severity of illness, length of stay, technology limitations and the erosion of standards.

78 FR 28258 - mPower\\TM\\ Design-Specific Review Standard

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-14

... Public Documents'' and then select ``Begin Web- based ADAMS Search.'' For problems with ADAMS, please... Classification ML12272A013 3.2.2 System Quality Group ML12272A015 Classification. 3.3.1 Severe Wind Loading... ML12324A156 3.3.2 Extreme Wind Loads ML12324A166 (Tornado and Hurricane Loads). 3.4.1 Internal Flood...

Study of USGS/NASA land use classification system. [compatibility of land use classification system with computer processing techniques employed for land use mapping from ERTS data

NASA Technical Reports Server (NTRS)

Spann, G. W.; Faust, N. L.

1974-01-01

It is known from several previous investigations that many categories of land-use can be mapped via computer processing of Earth Resources Technology Satellite data. The results are presented of one such experiment using the USGS/NASA land-use classification system. Douglas County, Georgia, was chosen as the test site for this project. It was chosen primarily because of its recent rapid growth and future growth potential. Results of the investigation indicate an overall land-use mapping accuracy of 67% with higher accuracies in rural areas and lower accuracies in urban areas. It is estimated, however, that 95% of the State of Georgia could be mapped by these techniques with an accuracy of 80% to 90%.

The role of identity in the DSM-5 classification of personality disorders

PubMed Central

2013-01-01

In the revised Diagnostic and Statistical Manual DSM-5 the definition of personality disorder diagnoses has not been changed from that in the DSM-IV-TR. However, an alternative model for diagnosing personality disorders where the construct “identity” has been integrated as a central diagnostic criterion for personality disorders has been placed in section III of the manual. The alternative model’s hybrid nature leads to the simultaneous use of diagnoses and the newly developed “Level of Personality Functioning-Scale” (a dimensional tool to define the severity of the disorder). Pathological personality traits are assessed in five broad domains which are divided into 25 trait facets. With this dimensional approach, the new classification system gives, both clinicians and researchers, the opportunity to describe the patient in much more detail than previously possible. The relevance of identity problems in assessing and understanding personality pathology is illustrated using the new classification system applied in two case examples of adolescents with a severe personality disorder. PMID:23902698

The role of identity in the DSM-5 classification of personality disorders.

PubMed

Schmeck, Klaus; Schlüter-Müller, Susanne; Foelsch, Pamela A; Doering, Stephan

2013-07-31

In the revised Diagnostic and Statistical Manual DSM-5 the definition of personality disorder diagnoses has not been changed from that in the DSM-IV-TR. However, an alternative model for diagnosing personality disorders where the construct "identity" has been integrated as a central diagnostic criterion for personality disorders has been placed in section III of the manual. The alternative model's hybrid nature leads to the simultaneous use of diagnoses and the newly developed "Level of Personality Functioning-Scale" (a dimensional tool to define the severity of the disorder). Pathological personality traits are assessed in five broad domains which are divided into 25 trait facets. With this dimensional approach, the new classification system gives, both clinicians and researchers, the opportunity to describe the patient in much more detail than previously possible. The relevance of identity problems in assessing and understanding personality pathology is illustrated using the new classification system applied in two case examples of adolescents with a severe personality disorder.

Validation of a systems-actuarial computer process for multidimensional classification of child psychopathology.

PubMed

McDermott, P A; Hale, R L

1982-07-01

Tested diagnostic classifications of child psychopathology produced by a computerized technique known as multidimensional actuarial classification (MAC) against the criterion of expert psychological opinion. The MAC program applies series of statistical decision rules to assess the importance of and relationships among several dimensions of classification, i.e., intellectual functioning, academic achievement, adaptive behavior, and social and behavioral adjustment, to perform differential diagnosis of children's mental retardation, specific learning disabilities, behavioral and emotional disturbance, possible communication or perceptual-motor impairment, and academic under- and overachievement in reading and mathematics. Classifications rendered by MAC are compared to those offered by two expert child psychologists for cases of 73 children referred for psychological services. Experts' agreement with MAC was significant for all classification areas, as was MAC's agreement with the experts held as a conjoint reference standard. Whereas the experts' agreement with MAC averaged 86.0% above chance, their agreement with one another averaged 76.5% above chance. Implications of the findings are explored and potential advantages of the systems-actuarial approach are discussed.

The Advantages and Limitations of International Classification of Diseases, Injuries and Causes of Death from Aspect of Existing Health Care System of Bosnia and Herzegovina

PubMed Central

Kurbasic, Izeta; Pandza, Haris; Masic, Izet; Huseinagic, Senad; Tandir, Salih; Alicajic, Fredi; Toromanovic, Selim

2008-01-01

CONFLICT OF INTEREST: NONE DECLARED Introduction The International classification of diseases (ICD) is the most important classification in medicine. It is used by all medical professionals. Concept The basic concept of ICD is founded on the standardization of the nomenclature for the names of diseases and their basic systematization in the hierarchically structured category. Advantages and disadvantages The health care provider institutions such as hospitals are subjects that should facilitate implementation of medical applications that follows the patient medical condition and facts connected with him. The definitive diagnosis that can be coded using ICD can be achieved after several visits of patient and rarely during the first visit. Conclusion The ICD classification is one of the oldest and most important classifications in medicine. In the scope of ICD are all fields of medicine. It is used in statistical purpose and as a coding system in medical databases. PMID:24109155

[CT morphometry for calcaneal fractures and comparison of the Zwipp and Sanders classifications].

PubMed

Andermahr, J; Jesch, A B; Helling, H J; Jubel, A; Fischbach, R; Rehm, K E

2002-01-01

The aim of the study is to correlate the CT-morphological changes of fractured calcaneus and the classifications of Zwipp and Sanders with the clinical outcome. In a retrospective clinical study, the preoperative CT scans of 75 calcaneal fractures were analysed. The morphometry of the fractures was determined by measuring height, length diameter and calcaneo-cuboidal angle in comparison to the intact contralateral side. At a mean of 38 months after trauma 44 patients were clinically followed-up. The data of CT image morphometry were correlated with the severity of fracture classified by Zwipp or Sanders as well as with the functional outcome. There was a good correlation between the fracture classifications and the morphometric data. Both fracture classifying systems have a predictive impact for functional outcome. The more exacting and accurate Zwipp classification considers the most important cofactors like involvement of the calcaneo-cuboidal joint, soft tissue damage, additional fractures etc. The Sanders classification is easier to use during clinical routine. The Zwipp classification includes more relevant cofactors (fracture of the calcaneo-cuboidal-joint, soft tissue swelling, etc.) and presents a higher correlation to the choice of therapy. Both classification systems present a prognostic impact concerning the clinical outcome.

Validation of the Japanese disease severity classification and the GAP model in Japanese patients with idiopathic pulmonary fibrosis.

PubMed

Kondoh, Shun; Chiba, Hirofumi; Nishikiori, Hirotaka; Umeda, Yasuaki; Kuronuma, Koji; Otsuka, Mitsuo; Yamada, Gen; Ohnishi, Hirofumi; Mori, Mitsuru; Kondoh, Yasuhiro; Taniguchi, Hiroyuki; Homma, Sakae; Takahashi, Hiroki

2016-09-01

The clinical course of idiopathic pulmonary fibrosis (IPF) shows great inter-individual differences. It is important to standardize the severity classification to accurately evaluate each patient׳s prognosis. In Japan, an original severity classification (the Japanese disease severity classification, JSC) is used. In the United States, the new multidimensional index and staging system (the GAP model) has been proposed. The objective of this study was to evaluate the model performance for the prediction of mortality risk of the JSC and GAP models using a large cohort of Japanese patients with IPF. This is a retrospective cohort study including 326 patients with IPF in the Hokkaido prefecture from 2003 to 2007. We obtained the survival curves of each stage of the GAP and JSC models to perform a comparison. In the GAP model, the prognostic value for mortality risk of Japanese patients was also evaluated. In the JSC, patient prognoses were roughly divided into two groups, mild cases (Stages I and II) and severe cases (Stages III and IV). In the GAP model, there was no significant difference in survival between Stages II and III, and the mortality rates in the patients classified into the GAP Stages I and II were underestimated. It is difficult to predict accurate prognosis of IPF using the JSC and the GAP models. A re-examination of the variables from the two models is required, as well as an evaluation of the prognostic value to revise the severity classification for Japanese patients with IPF. Copyright © 2016 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

A four-tier classification system of pulmonary artery metrics on computed tomography for the diagnosis and prognosis of pulmonary hypertension.

PubMed

Truong, Quynh A; Bhatia, Harpreet Singh; Szymonifka, Jackie; Zhou, Qing; Lavender, Zachary; Waxman, Aaron B; Semigran, Marc J; Malhotra, Rajeev

We aimed to develop a severity classification system of the main pulmonary artery diameter (mPA) and its ratio to the ascending aorta diameter (ratio PA) for the diagnosis and prognosis of pulmonary hypertension (PH) on computed tomography (CT) scans. In 228 patients (136 with PH) undergoing right heart catheterization (RHC) and CT for dyspnea, we measured mPA and ratio PA. In a derivation cohort (n = 114), we determined cutpoints for a four-tier severity grading system that would maximize sensitivity and specificity, and validated it in a separate cohort (n = 114). Cutpoints for mPA were defined with ≤27 mm(F) and ≤29 mm(M) as the normal reference range; mild as >27 to <31 mm(F) and >29 to <31 mm(M); moderate≥31-34 mm; and severe>34 mm. Cutpoints for ratio PA were defined as normal ≤0.9; mild>0.9 to 1.0; moderate>1.0 to 1.1; and severe>1.1. Sensitivities for normal tier were 99% for mPA and 93% for ratio PA; while specificities for severe tier were 98% for mPA>34 mm and 100% for ratio PA>1.1. C-statistics for four-tier mPA and ratio PA were both 0.90 (derivation) and both 0.85 (validation). Severity of mPA and ratio PA corresponded to hemodynamics by RHC and echocardiography (both p < 0.001). Moderate-severe mPA values of ≥31 mm and ratio PA>1.1 had worse survival than normal values (all p ≤ 0.01). A CT-based four-tier severity classification system of PA diameter and its ratio to the aortic diameter has high accuracy for PH diagnosis with increased mortality in patients with moderate-severe severity grades. These results may support clinical utilization on chest and cardiac CT reports. Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Development and Reliability Testing of the FEDS System for Classifying Glenohumeral Instability

PubMed Central

Kuhn, John E.; Helmer, Tara T.; Dunn, Warren R.; Throckmorton V, Thomas W.

2010-01-01

Background Classification systems for glenohumeral instability (GHI) are opinion based, not validated, and poorly defined. This study is designed to methodologically develop and test a GHI classification system. Methods: Classification System Development A systematic literature review identified 18 systems for classifying GHI. The frequency characteristics used was recorded. Additionally 31 members of the American Shoulder and Elbow Surgeons responded to a survey to identify features important to characterize GHI. Frequency, Etiology, Direction, and Severity (FEDS), were found to be most important. Frequency was defined as solitary (one episode), occasional (2–5x/year), or frequent (>5x/year). Etiology was defined as traumatic or atraumatic. Direction referred to the primary direction of instability (anterior, posterior, or inferior). Severity was defined as either subluxation or dislocation. Methods: Reliability Testing Fifty GHI patients completed a questionnaire at their initial visit. One of six sports medicine fellowship trained physicians completed a similar questionnaire after examining the patient. Patients returned after two weeks and were examined by the original physician and two other physicians. Inter- and intra-rater agreement for the FEDS classification system was calculated. Results Agreement between patients and physicians was lowest for frequency (39%; k=0.130) and highest for direction (82%; k=0.636). Physician intra-rater agreement was 84– 97% for the individual FEDS characteristics (k=0.69 to 0.87)). Physician inter-rater agreement ranged from 82–90% (k=0.44 to 0.76). Conclusions The FEDS system has content validity and is highly reliable for classifying GHI. Physical examination using provocative testing to determine the primary direction of instability produces very high levels of inter- and intra-rater agreement. Level of evidence Level II, Development of Diagnostic Criteria with Consecutive Series of Patients, Diagnosis Study. PMID:21277809

Modern radiosurgical and endovascular classification schemes for brain arteriovenous malformations.

PubMed

Tayebi Meybodi, Ali; Lawton, Michael T

2018-05-04

Stereotactic radiosurgery (SRS) and endovascular techniques are commonly used for treating brain arteriovenous malformations (bAVMs). They are usually used as ancillary techniques to microsurgery but may also be used as solitary treatment options. Careful patient selection requires a clear estimate of the treatment efficacy and complication rates for the individual patient. As such, classification schemes are an essential part of patient selection paradigm for each treatment modality. While the Spetzler-Martin grading system and its subsequent modifications are commonly used for microsurgical outcome prediction for bAVMs, the same system(s) may not be easily applicable to SRS and endovascular therapy. Several radiosurgical- and endovascular-based grading scales have been proposed for bAVMs. However, a comprehensive review of these systems including a discussion on their relative advantages and disadvantages is missing. This paper is dedicated to modern classification schemes designed for SRS and endovascular techniques.

Improved GART neural network model for pattern classification and rule extraction with application to power systems.

PubMed

Yap, Keem Siah; Lim, Chee Peng; Au, Mau Teng

2011-12-01

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

GHS additivity formula: can it predict the acute systemic toxicity of agrochemical formulations that contain acutely toxic ingredients?

PubMed

Van Cott, Andrew; Hastings, Charles E; Landsiedel, Robert; Kolle, Susanne; Stinchcombe, Stefan

2018-02-01

In vivo acute systemic testing is a regulatory requirement for agrochemical formulations. GHS specifies an alternative computational approach (GHS additivity formula) for calculating the acute toxicity of mixtures. We collected acute systemic toxicity data from formulations that contained one of several acutely-toxic active ingredients. The resulting acute data set includes 210 formulations tested for oral toxicity, 128 formulations tested for inhalation toxicity and 31 formulations tested for dermal toxicity. The GHS additivity formula was applied to each of these formulations and compared with the experimental in vivo result. In the acute oral assay, the GHS additivity formula misclassified 110 formulations using the GHS classification criteria (48% accuracy) and 119 formulations using the USEPA classification criteria (43% accuracy). With acute inhalation, the GHS additivity formula misclassified 50 formulations using the GHS classification criteria (61% accuracy) and 34 formulations using the USEPA classification criteria (73% accuracy). For acute dermal toxicity, the GHS additivity formula misclassified 16 formulations using the GHS classification criteria (48% accuracy) and 20 formulations using the USEPA classification criteria (36% accuracy). This data indicates the acute systemic toxicity of many formulations is not the sum of the ingredients' toxicity (additivity); but rather, ingredients in a formulation can interact to result in lower or higher toxicity than predicted by the GHS additivity formula. Copyright © 2018 Elsevier Inc. All rights reserved.

Speaker gender identification based on majority vote classifiers

NASA Astrophysics Data System (ADS)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2017-03-01

Speaker gender identification is considered among the most important tools in several multimedia applications namely in automatic speech recognition, interactive voice response systems and audio browsing systems. Gender identification systems performance is closely linked to the selected feature set and the employed classification model. Typical techniques are based on selecting the best performing classification method or searching optimum tuning of one classifier parameters through experimentation. In this paper, we consider a relevant and rich set of features involving pitch, MFCCs as well as other temporal and frequency-domain descriptors. Five classification models including decision tree, discriminant analysis, nave Bayes, support vector machine and k-nearest neighbor was experimented. The three best perming classifiers among the five ones will contribute by majority voting between their scores. Experimentations were performed on three different datasets spoken in three languages: English, German and Arabic in order to validate language independency of the proposed scheme. Results confirm that the presented system has reached a satisfying accuracy rate and promising classification performance thanks to the discriminating abilities and diversity of the used features combined with mid-level statistics.

Injuries from intimate partner and sexual violence: Significance and classification systems.

PubMed

Sommers, Marilyn S; Brown, Kathleen M; Buschur, Carole; Everett, Janine S; Fargo, Jamison D; Fisher, Bonnie S; Hinkle, Christina; Zink, Therese M

2012-07-01

While intimate partner violence (IPV) and sexual violence (SV) are highly associated with injury, the healthcare and legal significance of these injuries is controversial. Herein we propose to explore the significance of injury in IPV and SV and examine the current status of injury classification systems from the perspectives of the healthcare and criminal justice systems. We will review current injury classification systems and suggest a typology of injury that could be tested empirically. Within the published literature, we found that no commonly accepted injury typology exists. While nuanced and controversial issues surround the role of injury detection in the sexual assault forensic examination, enough evidence exists to support the continued pursuance of a scientific approach to injury classification. We propose an injury typology that is measurable, is applicable to the healthcare setting and criminal justice system, and allows us to use uses a matrix approach that includes a severity score, anatomic location, and injury type. We suggest a typology that might be used for further empirical testing on the validity and reliability of IPV and SV injury data. We recommend that the community of scientists concerned about IPV and SV develop a more rigorous injury classification system that will improve the quality of forensic evidence proffered and decisions made throughout the criminal justice process. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Designing boosting ensemble of relational fuzzy systems.

PubMed

Scherer, Rafał

2010-10-01

A method frequently used in classification systems for improving classification accuracy is to combine outputs of several classifiers. Among various types of classifiers, fuzzy ones are tempting because of using intelligible fuzzy if-then rules. In the paper we build an AdaBoost ensemble of relational neuro-fuzzy classifiers. Relational fuzzy systems bond input and output fuzzy linguistic values by a binary relation; thus, fuzzy rules have additional, comparing to traditional fuzzy systems, weights - elements of a fuzzy relation matrix. Thanks to this the system is better adjustable to data during learning. In the paper an ensemble of relational fuzzy systems is proposed. The problem is that such an ensemble contains separate rule bases which cannot be directly merged. As systems are separate, we cannot treat fuzzy rules coming from different systems as rules from the same (single) system. In the paper, the problem is addressed by a novel design of fuzzy systems constituting the ensemble, resulting in normalization of individual rule bases during learning. The method described in the paper is tested on several known benchmarks and compared with other machine learning solutions from the literature.

A scope classification of data quality requirements for food composition data.

PubMed

Presser, Karl; Hinterberger, Hans; Weber, David; Norrie, Moira

2016-02-15

Data quality is an important issue when managing food composition data since the usage of the data can have a significant influence on policy making and further research. Although several frameworks for data quality have been proposed, general tools and measures are still lacking. As a first step in this direction, we investigated data quality requirements for an information system to manage food composition data, called FoodCASE. The objective of our investigation was to find out if different requirements have different impacts on the intrinsic data quality that must be regarded during data quality assessment and how these impacts can be described. We refer to the resulting classification with its categories as the scope classification of data quality requirements. As proof of feasibility, the scope classification has been implemented in the FoodCASE system. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of quantum-behaved particle swarm optimization to motor imagery EEG classification.

PubMed

Hsu, Wei-Yen

2013-12-01

In this study, we propose a recognition system for single-trial analysis of motor imagery (MI) electroencephalogram (EEG) data. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system chiefly consists of automatic artifact elimination, feature extraction, feature selection and classification. In addition to the use of independent component analysis, a similarity measure is proposed to further remove the electrooculographic (EOG) artifacts automatically. Several potential features, such as wavelet-fractal features, are then extracted for subsequent classification. Next, quantum-behaved particle swarm optimization (QPSO) is used to select features from the feature combination. Finally, selected sub-features are classified by support vector machine (SVM). Compared with without artifact elimination, feature selection using a genetic algorithm (GA) and feature classification with Fisher's linear discriminant (FLD) on MI data from two data sets for eight subjects, the results indicate that the proposed method is promising in brain-computer interface (BCI) applications.

New insights into the classification and nomenclature of cortical GABAergic interneurons.

PubMed

DeFelipe, Javier; López-Cruz, Pedro L; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R; Huang, Josh; Jones, Edward G; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A; Marín, Oscar; Markram, Henry; McBain, Chris J; Meyer, Hanno S; Monyer, Hannah; Nelson, Sacha B; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L R; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M; Sherwood, Chet C; Staiger, Jochen F; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A

2013-03-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

New insights into the classification and nomenclature of cortical GABAergic interneurons

PubMed Central

DeFelipe, Javier; López-Cruz, Pedro L.; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F.; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R.; Huang, Josh; Jones, Edward G.; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A.; Marín, Oscar; Markram, Henry; McBain, Chris J.; Meyer, Hanno S.; Monyer, Hannah; Nelson, Sacha B.; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L. R.; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M.; Sherwood, Chet C.; Staiger, Jochen F.; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A.

2013-01-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts’ assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus. PMID:23385869

Classification and evolution of human rhinoviruses.

PubMed

Palmenberg, Ann C; Gern, James E

2015-01-01

The historical classification of human rhinoviruses (RV) by serotyping has been replaced by a logical system of comparative sequencing. Given that strains must diverge within their capsid sequenced by a reasonable degree (>12-13 % pairwise base identities) before becoming immunologically distinct, the new nomenclature system makes allowances for the addition of new, future types, without compromising historical designations. Currently, three species, the RV-A, RV-B, and RV-C, are recognized. Of these, the RV-C, discovered in 2006, are the most unusual in terms of capsid structure, receptor use, and association with severe disease in children.

Classification of maxillectomy defects: a systematic review and criteria necessary for a universal description.

PubMed

Bidra, Avinash S; Jacob, Rhonda F; Taylor, Thomas D

2012-04-01

Maxillectomy defects are complex and involve a number of anatomic structures. Several maxillectomy defect classifications have been proposed with no universal acceptance among surgeons and prosthodontists. Established criteria for describing the maxillectomy defect are lacking. This systematic review aimed to evaluate classification systems in the available literature, to provide a critical appraisal, and to identify the criteria necessary for a universal description of maxillectomy and midfacial defects. An electronic search of the English language literature between the periods of 1974 and June 2011 was performed by using PubMed, Scopus, and Cochrane databases with predetermined inclusion criteria. Key terms included in the search were maxillectomy classification, maxillary resection classification, maxillary removal classification, maxillary reconstruction classification, midfacial defect classification, and midfacial reconstruction classification. This was supplemented by a manual search of selected journals. After application of predetermined exclusion criteria, the final list of articles was reviewed in-depth to provide a critical appraisal and identify criteria for a universal description of a maxillectomy defect. The electronic database search yielded 261 titles. Systematic application of inclusion and exclusion criteria resulted in identification of 14 maxillectomy and midfacial defect classification systems. From these articles, 6 different criteria were identified as necessary for a universal description of a maxillectomy defect. Multiple deficiencies were noted in each classification system. Though most articles described the superior-inferior extent of the defect, only a small number of articles described the anterior-posterior and medial-lateral extent of the defect. Few articles listed dental status and soft palate involvement when describing maxillectomy defects. No classification system has accurately described the maxillectomy defect, based on criteria that satisfy both surgical and prosthodontic needs. The 6 criteria identified in this systematic review for a universal description of a maxillectomy defect are: 1) dental status; 2) oroantral/nasal communication status; 3) soft palate and other contiguous structure involvement; 4) superior-inferior extent; 5) anterior-posterior extent; and 6) medial-lateral extent of the defect. A criteria-based description appears more objective and amenable for universal use than a classification-based description. Copyright © 2012 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System.

PubMed

de Moura, Karina de O A; Balbinot, Alexandre

2018-05-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior.

Virtual Sensor of Surface Electromyography in a New Extensive Fault-Tolerant Classification System

PubMed Central

Balbinot, Alexandre

2018-01-01

A few prosthetic control systems in the scientific literature obtain pattern recognition algorithms adapted to changes that occur in the myoelectric signal over time and, frequently, such systems are not natural and intuitive. These are some of the several challenges for myoelectric prostheses for everyday use. The concept of the virtual sensor, which has as its fundamental objective to estimate unavailable measures based on other available measures, is being used in other fields of research. The virtual sensor technique applied to surface electromyography can help to minimize these problems, typically related to the degradation of the myoelectric signal that usually leads to a decrease in the classification accuracy of the movements characterized by computational intelligent systems. This paper presents a virtual sensor in a new extensive fault-tolerant classification system to maintain the classification accuracy after the occurrence of the following contaminants: ECG interference, electrode displacement, movement artifacts, power line interference, and saturation. The Time-Varying Autoregressive Moving Average (TVARMA) and Time-Varying Kalman filter (TVK) models are compared to define the most robust model for the virtual sensor. Results of movement classification were presented comparing the usual classification techniques with the method of the degraded signal replacement and classifier retraining. The experimental results were evaluated for these five noise types in 16 surface electromyography (sEMG) channel degradation case studies. The proposed system without using classifier retraining techniques recovered of mean classification accuracy was of 4% to 38% for electrode displacement, movement artifacts, and saturation noise. The best mean classification considering all signal contaminants and channel combinations evaluated was the classification using the retraining method, replacing the degraded channel by the virtual sensor TVARMA model. This method recovered the classification accuracy after the degradations, reaching an average of 5.7% below the classification of the clean signal, that is the signal without the contaminants or the original signal. Moreover, the proposed intelligent technique minimizes the impact of the motion classification caused by signal contamination related to degrading events over time. There are improvements in the virtual sensor model and in the algorithm optimization that need further development to provide an increase the clinical application of myoelectric prostheses but already presents robust results to enable research with virtual sensors on biological signs with stochastic behavior. PMID:29723994

An approach to the diagnosis of flat intraepithelial lesions of the urinary bladder using the World Health Organization/ International Society of Urological Pathology consensus classification system.

PubMed

Amin, Mahul B; McKenney, Jesse K

2002-07-01

The classification of flat urothelial (transitional cell) lesions with atypia has historically varied in its application from institution to institution with no fewer than six major nomenclature systems proposed in the past 25 years. In 1998, the World Health Organization/ International Society of Urological Pathology (WHO/ISUP) published a consensus classification that included the following categories for flat urinary bladder lesions: reactive atypia, atypia of unknown significance, dysplasia (low-grade intraepithelial neoplasia), and carcinoma in situ (high-grade intraepithelial neoplasia). This classification expands the definition traditionally used for urothelial carcinoma in situ, basing its diagnosis primarily on the severity of cytologic changes. In proposing the classification system for flat lesions of the bladder with atypia, it was hoped that consistent use of uniform diagnostic terminology would ultimately aid in a better understanding of the biology of these lesions. In this review, the authors discuss the history of the concept of flat urothelial neoplasia, the rationale and histologic criteria for the WHO/ISUP diagnostic categories, an approach to the diagnosis of flat lesions, and problems and pitfalls associated with their recognition in routine surgical pathology specimens.

A systematic review of the Robson classification for caesarean section: what works, doesn't work and how to improve it.

PubMed

Betrán, Ana Pilar; Vindevoghel, Nadia; Souza, Joao Paulo; Gülmezoglu, A Metin; Torloni, Maria Regina

2014-01-01

Caesarean sections (CS) rates continue to increase worldwide without a clear understanding of the main drivers and consequences. The lack of a standardized internationally-accepted classification system to monitor and compare CS rates is one of the barriers to a better understanding of this trend. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) and does not involve the indication for CS. This classification has become very popular over the last years in many countries. We conducted a systematic review to synthesize the experience of users on the implementation of this classification and proposed adaptations. Four electronic databases were searched. A three-step thematic synthesis approach and a qualitative metasummary method were used. 232 unique reports were identified, 97 were selected for full-text evaluation and 73 were included. These publications reported on the use of Robson's classification in over 33 million women from 31 countries. According to users, the main strengths of the classification are its simplicity, robustness, reliability and flexibility. However, missing data, misclassification of women and lack of definition or consensus on core variables of the classification are challenges. To improve the classification for local use and to decrease heterogeneity within groups, several subdivisions in each of the 10 groups have been proposed. Group 5 (women with previous CS) received the largest number of suggestions. The use of the Robson classification is increasing rapidly and spontaneously worldwide. Despite some limitations, this classification is easy to implement and interpret. Several suggested modifications could be useful to help facilities and countries as they work towards its implementation.

A Systematic Review of the Robson Classification for Caesarean Section: What Works, Doesn't Work and How to Improve It

PubMed Central

Betrán, Ana Pilar; Vindevoghel, Nadia; Souza, Joao Paulo; Gülmezoglu, A. Metin; Torloni, Maria Regina

2014-01-01

Background Caesarean sections (CS) rates continue to increase worldwide without a clear understanding of the main drivers and consequences. The lack of a standardized internationally-accepted classification system to monitor and compare CS rates is one of the barriers to a better understanding of this trend. The Robson's 10-group classification is based on simple obstetrical parameters (parity, previous CS, gestational age, onset of labour, fetal presentation and number of fetuses) and does not involve the indication for CS. This classification has become very popular over the last years in many countries. We conducted a systematic review to synthesize the experience of users on the implementation of this classification and proposed adaptations. Methods Four electronic databases were searched. A three-step thematic synthesis approach and a qualitative metasummary method were used. Results 232 unique reports were identified, 97 were selected for full-text evaluation and 73 were included. These publications reported on the use of Robson's classification in over 33 million women from 31 countries. According to users, the main strengths of the classification are its simplicity, robustness, reliability and flexibility. However, missing data, misclassification of women and lack of definition or consensus on core variables of the classification are challenges. To improve the classification for local use and to decrease heterogeneity within groups, several subdivisions in each of the 10 groups have been proposed. Group 5 (women with previous CS) received the largest number of suggestions. Conclusions The use of the Robson classification is increasing rapidly and spontaneously worldwide. Despite some limitations, this classification is easy to implement and interpret. Several suggested modifications could be useful to help facilities and countries as they work towards its implementation. PMID:24892928

Comparing the usefulness of the 1997 and 2009 WHO dengue case classification: a systematic literature review.

PubMed

Horstick, Olaf; Jaenisch, Thomas; Martinez, Eric; Kroeger, Axel; See, Lucy Lum Chai; Farrar, Jeremy; Ranzinger, Silvia Runge

2014-09-01

The 1997 and 2009 WHO dengue case classifications were compared in a systematic review with 12 eligible studies (4 prospective). Ten expert opinion articles were used for discussion. For the 2009 WHO classification studies show: when determining severe dengue sensitivity ranges between 59-98% (88%/98%: prospective studies), specificity between 41-99% (99%: prospective study) - comparing the 1997 WHO classification: sensitivity 24.8-89.9% (24.8%/74%: prospective studies), specificity: 25%/100% (100%: prospective study). The application of the 2009 WHO classification is easy, however for (non-severe) dengue there may be a risk of monitoring increased case numbers. Warning signs validation studies are needed. For epidemiological/pathogenesis research use of the 2009 WHO classification, opinion papers show that ease of application, increased sensitivity (severe dengue) and international comparability are advantageous; 3 severe dengue criteria (severe plasma leakage, severe bleeding, severe organ manifestation) are useful research endpoints. The 2009 WHO classification has clear advantages for clinical use, use in epidemiology is promising and research use may at least not be a disadvantage. © The American Society of Tropical Medicine and Hygiene.

Histopathologic features in actinic cheilitis by the comparison of grading dysplasia systems.

PubMed

Pilati, Sfm; Bianco, B C; Vieira, Dsc; Modolo, F

2017-03-01

This study aimed to determine the histopathologic findings in actinic cheilitis (AC) and lip squamous cell carcinomas (LSCC) diagnosed at Federal University of Santa Catarina in order to attempt to predict the evolution from AC to LSCC based on the comparison of two dysplasia classification systems. Histopathologic features were evaluated according to the World Health Organization classification of dysplasia and binary system of classification. Also, in LSCC, pattern, stage of invasion, and degree of keratinization were evaluated. A total of 58 cases of AC and 70 cases of LSCC were studied, and data correlation was performed using statistical analysis. The presence of dyskeratosis and keratin pearls was found to be strongly associated with severe dysplasia and could represent higher proximity between the severe dysplasia in AC and LSCC. Also, changes related to the nuclei, such as hyperchromasia, nuclear pleomorphism, anisonucleosis, increase in the number and size of nucleoli, increased number of mitoses, and atypical mitoses, indicate progression in dysplasia spectrum. Knowledge of clinical and histological features of AC and LSCC leads to better understanding of factors possibly associated with malignant transformation of epithelial dysplasia. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Prevention of musculoskeletal disorders in workers: classification and health surveillance - statements of the Scientific Committee on Musculoskeletal Disorders of the International Commission on Occupational Health.

PubMed

Hagberg, Mats; Violante, Francesco Saverio; Bonfiglioli, Roberta; Descatha, Alexis; Gold, Judith; Evanoff, Brad; Sluiter, Judith K

2012-06-21

The underlying purpose of this commentary and position paper is to achieve evidence-based recommendations on prevention of work-related musculoskeletal disorders (MSDs). Such prevention can take different forms (primary, secondary and tertiary), occur at different levels (i.e. in a clinical setting, at the workplace, at national level) and involve several types of activities. Members of the Scientific Committee (SC) on MSDs of the International Commission on Occupational Health (ICOH) and other interested scientists and members of the public recently discussed the scientific and clinical future of prevention of (work-related) MSDs during five round-table sessions at two ICOH conferences (in Cape Town, South Africa, in 2009, and in Angers, France, in 2010). Approximately 50 researchers participated in each of the sessions. More specifically, the sessions aimed to discuss new developments since 1996 in measures and classification systems used both in research and in practice, and agree on future needs in the field. The discussion focused on three questions: At what degree of severity does musculoskeletal ill health, and do health problems related to MSDs, in an individual worker or in a group of workers justify preventive action in occupational health? What reliable and valid instruments do we have in research to distinguish 'normal musculoskeletal symptoms' from 'serious musculoskeletal symptoms' in workers? What measures or classification system of musculoskeletal health will we need in the near future to address musculoskeletal health and related work ability? Four new, agreed-upon statements were extrapolated from the discussions: 1. Musculoskeletal discomfort that is at risk of worsening with work activities, and that affects work ability or quality of life, needs to be identified. 2. We need to know our options of actions before identifying workers at risk (providing evidence-based medicine and applying the principle of best practice). 3. Classification systems and measures must include aspects such as the severity, frequency, and intensity of pain, as well as measures of impairment of functioning, which can help in prevention, treatment and prognosis. 4. We need to be aware of economic and/or socio-cultural consequences of classification systems and measures.

Assessment of incidence of severe sepsis in Sweden using different ways of abstracting International Classification of Diseases codes: difficulties with methods and interpretation of results.

PubMed

Wilhelms, Susanne B; Huss, Fredrik R; Granath, Göran; Sjöberg, Folke

2010-06-01

To compare three International Classification of Diseases code abstraction strategies that have previously been reported to mirror severe sepsis by examining retrospective Swedish national data from 1987 to 2005 inclusive. Retrospective cohort study. Swedish hospital discharge database. All hospital admissions during the period 1987 to 2005 were extracted and these patients were screened for severe sepsis using the three International Classification of Diseases code abstraction strategies, which were adapted for the Swedish version of the International Classification of Diseases. Two code abstraction strategies included both International Classification of Diseases, Ninth Revision and International Classification of Diseases, Tenth Revision codes, whereas one included International Classification of Diseases, Tenth Revision codes alone. None. The three International Classification of Diseases code abstraction strategies identified 37,990, 27,655, and 12,512 patients, respectively, with severe sepsis. The incidence increased over the years, reaching 0.35 per 1000, 0.43 per 1000, and 0.13 per 1000 inhabitants, respectively. During the International Classification of Diseases, Ninth Revision period, we found 17,096 unique patients and of these, only 2789 patients (16%) met two of the code abstraction strategy lists and 14,307 (84%) met one list. The International Classification of Diseases, Tenth Revision period included 46,979 unique patients, of whom 8% met the criteria of all three International Classification of Diseases code abstraction strategies, 7% met two, and 84% met one only. The three different International Classification of Diseases code abstraction strategies generated three almost separate cohorts of patients with severe sepsis. Thus, the International Classification of Diseases code abstraction strategies for recording severe sepsis in use today provides an unsatisfactory way of estimating the true incidence of severe sepsis. Further studies relating International Classification of Diseases code abstraction strategies to the American College of Chest Physicians/Society of Critical Care Medicine scores are needed.

A classification of marked hijaiyah letters' pronunciation using hidden Markov model

NASA Astrophysics Data System (ADS)

Wisesty, Untari N.; Mubarok, M. Syahrul; Adiwijaya

2017-08-01

Hijaiyah letters are the letters that arrange the words in Al Qur'an consisting of 28 letters. They symbolize the consonant sounds. On the other hand, the vowel sounds are symbolized by harokat/marks. Speech recognition system is a system used to process the sound signal to be data so that it can be recognized by computer. To build the system, some stages are needed i.e characteristics/feature extraction and classification. In this research, LPC and MFCC extraction method, K-Means Quantization vector and Hidden Markov Model classification are used. The data used are the 28 letters and 6 harakat with the total class of 168. After several are testing done, it can be concluded that the system can recognize the pronunciation pattern of marked hijaiyah letter very well in the training data with its highest accuracy of 96.1% using the feature of LPC extraction and 94% using the MFCC. Meanwhile, when testing system is used, the accuracy decreases up to 41%.

Genetic burden associated with varying degrees of disease severity in endometriosis

PubMed Central

Sapkota, Yadav; Attia, John; Gordon, Scott D.; Henders, Anjali K.; Holliday, Elizabeth G.; Rahmioglu, Nilufer; MacGregor, Stuart; Martin, Nicholas G.; McEvoy, Mark; Morris, Andrew P.; Scott, Rodney J.; Zondervan, Krina T.; Montgomery, Grant W.; Nyholt, Dale R.

2015-01-01

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities. PMID:25882541

An evaluation of computer assisted clinical classification algorithms.

PubMed

Chute, C G; Yang, Y; Buntrock, J

1994-01-01

The Mayo Clinic has a long tradition of indexing patient records in high resolution and volume. Several algorithms have been developed which promise to help human coders in the classification process. We evaluate variations on code browsers and free text indexing systems with respect to their speed and error rates in our production environment. The more sophisticated indexing systems save measurable time in the coding process, but suffer from incompleteness which requires a back-up system or human verification. Expert Network does the best job of rank ordering clinical text, potentially enabling the creation of thresholds for the pass through of computer coded data without human review.

Feasibility and Reliability of the Modified Berg Balance Scale in Persons with Severe Intellectual and Visual Disabilities

ERIC Educational Resources Information Center

Waninge, A.; van Wijck, R.; Steenbergen, B.; van der Schans, C. P.

2011-01-01

Background: The purpose of this study was to determine the feasibility and reliability of the modified Berg Balance Scale (mBBS) in persons with severe intellectual and visual disabilities (severe multiple disabilities, SMD) assigned Gross Motor Function Classification System (GMFCS) grades I and II. Method: Thirty-nine participants with SMD and…

Classifying psychosis--challenges and opportunities.

PubMed

Gaebel, Wolfgang; Zielasek, Jürgen; Cleveland, Helen-Rose

2012-12-01

Within the efforts to revise ICD-10 and DSM-IV-TR, work groups on the classification of psychotic disorders appointed by the World Health Organization (WHO) and the American Psychiatric Association (APA) have proposed several changes to the corresponding classification criteria of schizophrenia and other psychotic disorders in order to increase the clinical utility, reliability and validity of these diagnoses. These proposed revisions are subject to field trials with the objective of studying whether they will lead to an improvement of the classification systems in comparison to their previous versions. Both a challenge and an opportunity, the APA and WHO have also considered harmonizing between the two classifications. The current status of both suggests that this goal can only be met in part. The main proposed revisions include changes to the number and types of symptoms of schizophrenia, the replacement of existing schizophrenia subtypes with dimensional assessments or symptom specifiers, different modifications of the criteria for schizoaffective disorder, a reorganization of the delusional disorders and the acute and transient psychotic disorders in ICD-11, as well as the revision of course and psychomotor symptoms/catatonia specifiers in both classification systems.

Categorization of intraoperative ureteroscopy complications using modified Satava classification system.

PubMed

Tepeler, Abdulkadir; Resorlu, Berkan; Sahin, Tolga; Sarikaya, Selcuk; Bayindir, Mirze; Oguz, Ural; Armagan, Abdullah; Unsal, Ali

2014-02-01

To review our experience with ureteroscopy (URS) in the treatment of ureteral calculi and stratify intraoperative complications of URS according to the modified Satava classification system. We performed a retrospective analysis of 1,208 patients (672 males and 536 females), with a mean age of 43.1 years (range 1-78), who underwent ureteroscopic procedures for removal of ureteral stones. Intraoperative complications were recorded according to modified Satava classification system. Grade 1 complications included incidents without consequences for the patient; grade 2 complications, which are treated intraoperatively with endoscopic surgery (grade 2a) or required endoscopic re-treatment (grade 2b); and grade 3 complications included incidents requiring open or laparoscopic surgery. The stones were completely removed in 1,067 (88.3%) patients after primary procedure by either simple extraction or after fragmentation. The overall incidence of intraoperative complications was 12.6%. The most common complications were proximal stone migration (3.9%), mucosal injury (2.8%), bleeding (1.9%), inability to reach stone (1.8%), malfunctioning or breakage of instruments (0.8%), ureteral perforation (0.8%) and ureteral avulsion (0.16%). According to modified Satava classification system, there were 4.5% grade 1; 4.4% grade 2a; 3.2% grade 2b; and 0.57% grade 3 complications. We think that modified Satava classification is a quick and simple system for describing the severity of intraoperative URS complications and this grading system will facilitate a better comparison for the surgical outcomes obtained from different centers.

The Ilac-Project Supporting Ancient Coin Classification by Means of Image Analysis

NASA Astrophysics Data System (ADS)

Kavelar, A.; Zambanini, S.; Kampel, M.; Vondrovec, K.; Siegl, K.

2013-07-01

This paper presents the ILAC project, which aims at the development of an automated image-based classification system for ancient Roman Republican coins. The benefits of such a system are manifold: operating at the suture between computer vision and numismatics, ILAC can reduce the day-to-day workload of numismatists by assisting them in classification tasks and providing a preselection of suitable coin classes. This is especially helpful for large coin hoard findings comprising several thousands of coins. Furthermore, this system could be implemented in an online platform for hobby numismatists, allowing them to access background information about their coin collection by simply uploading a photo of obverse and reverse for the coin of interest. ILAC explores different computer vision techniques and their combinations for the use of image-based coin recognition. Some of these methods, such as image matching, use the entire coin image in the classification process, while symbol or legend recognition exploit certain characteristics of the coin imagery. An overview of the methods explored so far and the respective experiments is given as well as an outlook on the next steps of the project.

Classification systems for lower extremity amputation prediction in subjects with active diabetic foot ulcer: a systematic review and meta-analysis.

PubMed

Monteiro-Soares, M; Martins-Mendes, D; Vaz-Carneiro, A; Sampaio, S; Dinis-Ribeiro, M

2014-10-01

We systematically review the available systems used to classify diabetic foot ulcers in order to synthesize their methodological qualitative issues and accuracy to predict lower extremity amputation, as this may represent a critical point in these patients' care. Two investigators searched, in EBSCO, ISI, PubMed and SCOPUS databases, and independently selected studies published until May 2013 and reporting prognostic accuracy and/or reliability of specific systems for patients with diabetic foot ulcer in order to predict lower extremity amputation. We included 25 studies reporting a prevalence of lower extremity amputation between 6% and 78%. Eight different diabetic foot ulcer descriptions and seven prognostic stratification classification systems were addressed with a variable (1-9) number of factors included, specially peripheral arterial disease (n = 12) or infection at the ulcer site (n = 10) or ulcer depth (n = 10). The Meggitt-Wagner, S(AD)SAD and Texas University Classification systems were the most extensively validated, whereas ten classifications were derived or validated only once. Reliability was reported in a single study, and accuracy measures were reported in five studies with another eight allowing their calculation. Pooled accuracy ranged from 0.65 (for gangrene) to 0.74 (for infection). There are numerous classification systems for diabetic foot ulcer outcome prediction, but only few studies evaluated their reliability or external validity. Studies rarely validated several systems simultaneously and only a few reported accuracy measures. Further studies assessing reliability and accuracy of the available systems and their composing variables are needed. Copyright © 2014 John Wiley & Sons, Ltd.

Localized contourlet features in vehicle make and model recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, B. S.

2009-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic Number Plate Recognition (ANPR) systems. Several vehicle MMR systems have been proposed in literature. In parallel to this, the usefulness of multi-resolution based feature analysis techniques leading to efficient object classification algorithms have received close attention from the research community. To this effect, Contourlet transforms that can provide an efficient directional multi-resolution image representation has recently been introduced. Already an attempt has been made in literature to use Curvelet/Contourlet transforms in vehicle MMR. In this paper we propose a novel localized feature detection method in Contourlet transform domain that is capable of increasing the classification rates up to 4%, as compared to the previously proposed Contourlet based vehicle MMR approach in which the features are non-localized and thus results in sub-optimal classification. Further we show that the proposed algorithm can achieve the increased classification accuracy of 96% at significantly lower computational complexity due to the use of Two Dimensional Linear Discriminant Analysis (2DLDA) for dimensionality reduction by preserving the features with high between-class variance and low inter-class variance.

[Evaluation of the appropriateness of hospital admissions using the iso-gravity classification systems APR-DRG and Disease Staging and the Italian version of Appropriateness Evaluation Protocol (AEP)].

PubMed

D'Andrea, G; Capalbo, G; Volpe, M; Marchetti, M; Vicentini, F; Capelli, G; Cambieri, A; Cicchetti, A; Ricciardi, G; Catananti, C

2006-01-01

Our main purpose was to evaluate the organizational appropriateness of admissions made in a university hospital, by comparing two iso-gravity classification systems, APR-DRG and Disease Staging, with the Italian version of AEP (PRUO). Our analysis focused on admissions made in 2001, related to specific Diagnosis Related Groups (DRGs), which, according an Italian Law, would be considered at high risk of inappropriateness, if treated as ordinary admissions. The results obtained by using the 2 classification systems did not show statistically significant differences with respect to the total number of admissions. On the other hand, some DRGs showed statistically significant differences due to different algorithms of attribution of the severity levels used by the two systems. For almost all of the DRGs studied, the AEP-based analysis of a sample of medical records showed an higher number of inappropriate admissions in comparison with the number expected by iso-gravity classification methods. The difference is possibly due to the percentage limits of tolerability fixed by the Law for each DRG. Therefore, the authors suggest an integrated use of the two methods to evaluate organizational appropriateness of hospital admissions.

New Atlanta Classification of acute pancreatitis in intensive care unit: Complications and prognosis.

PubMed

Pintado, María-Consuelo; Trascasa, María; Arenillas, Cristina; de Zárate, Yaiza Ortiz; Pardo, Ana; Blandino Ortiz, Aaron; de Pablo, Raúl

2016-05-01

The updated Atlanta Classification of acute pancreatitis (AP) in adults defined three levels of severity according to the presence of local and/or systemic complications and presence and length of organ failure. No study focused on complications and mortality of patients with moderately severe AP admitted to intensive care unit (ICU). The main aim of this study is to describe the complications developed and outcomes of these patients and compare them to those with severe AP. Prospective, observational study. We included patients with acute moderately severe or severe AP admitted in a medical-surgical ICU during 5years. We collected demographic data, admission criteria, pancreatitis etiology, severity of illness, presence of organ failure, local and systemic complications, ICU length of stay, and mortality. Fifty-six patients were included: 12 with moderately severe AP and 44 with severe. All patients developed some kind of complications without differences on complications rate between moderately severe or severe AP. All the patients present non-infectious systemic complications, mainly acute respiratory failure and hemodynamic failure. 82.1% had an infectious complication, mainly non-pancreatic infection (66.7% on moderately severe AP vs. 79.5% on severe, p=0.0443). None of the patients with moderately severe AP died during their intensive care unit stay vs. 29.5% with severe AP (p=0.049). Moderately severe AP has a high rate of complications with similar rates to patients with severe AP admitted to ICU. However, their ICU mortality remains very low, which supports the existence of this new group of pancreatitis according to their severity. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Analysis of DSN software anomalies

NASA Technical Reports Server (NTRS)

Galorath, D. D.; Hecht, H.; Hecht, M.; Reifer, D. J.

1981-01-01

A categorized data base of software errors which were discovered during the various stages of development and operational use of the Deep Space Network DSN/Mark 3 System was developed. A study team identified several existing error classification schemes (taxonomies), prepared a detailed annotated bibliography of the error taxonomy literature, and produced a new classification scheme which was tuned to the DSN anomaly reporting system and encapsulated the work of others. Based upon the DSN/RCI error taxonomy, error data on approximately 1000 reported DSN/Mark 3 anomalies were analyzed, interpreted and classified. Next, error data are summarized and histograms were produced highlighting key tendencies.

Cognitive context detection in UAS operators using eye-gaze patterns on computer screens

NASA Astrophysics Data System (ADS)

Mannaru, Pujitha; Balasingam, Balakumar; Pattipati, Krishna; Sibley, Ciara; Coyne, Joseph

2016-05-01

In this paper, we demonstrate the use of eye-gaze metrics of unmanned aerial systems (UAS) operators as effective indices of their cognitive workload. Our analyses are based on an experiment where twenty participants performed pre-scripted UAS missions of three different difficulty levels by interacting with two custom designed graphical user interfaces (GUIs) that are displayed side by side. First, we compute several eye-gaze metrics, traditional eye movement metrics as well as newly proposed ones, and analyze their effectiveness as cognitive classifiers. Most of the eye-gaze metrics are computed by dividing the computer screen into "cells". Then, we perform several analyses in order to select metrics for effective cognitive context classification related to our specific application; the objective of these analyses are to (i) identify appropriate ways to divide the screen into cells; (ii) select appropriate metrics for training and classification of cognitive features; and (iii) identify a suitable classification method.

A graduated food addiction classification approach significantly differentiates obesity among people with type 2 diabetes.

PubMed

Raymond, Karren-Lee; Kannis-Dymand, Lee; Lovell, Geoff P

2016-10-01

This study examined a graduated severity level approach to food addiction classification against associations with World Health Organization obesity classifications (body mass index, kg/m 2 ) among 408 people with type 2 diabetes. A survey including the Yale Food Addiction Scale and several demographic questions demonstrated four distinct Yale Food Addiction Scale symptom severity groups (in line with Diagnostic and Statistical Manual of Mental Disorders (5th ed.) severity indicators): non-food addiction, mild food addiction, moderate food addiction and severe food addiction. Analysis of variance with post hoc tests demonstrated each severity classification group was significantly different in body mass index, with each grouping being associated with increased World Health Organization obesity classifications. These findings have implications for diagnosing food addiction and implementing treatment and prevention methodologies of obesity among people with type 2 diabetes.

Variability of lotic macroinvertebrate assemblages and stream habitat characteristics across hierarchical landscape classifications.

PubMed

Mykrä, Heikki; Heino, Jani; Muotka, Timo

2004-09-01

Streams are naturally hierarchical systems, and their biota are affected by factors effective at regional to local scales. However, there have been only a few attempts to quantify variation in ecological attributes across multiple spatial scales. We examined the variation in several macroinvertebrate metrics and environmental variables at three hierarchical scales (ecoregions, drainage systems, streams) in boreal headwater streams. In nested analyses of variance, significant spatial variability was observed for most of the macroinvertebrate metrics and environmental variables examined. For most metrics, ecoregions explained more variation than did drainage systems. There was, however, much variation attributable to residuals, suggesting high among-stream variation in macroinvertebrate assemblage characteristics. Nonmetric multidimensional scaling (NMDS) and multiresponse permutation procedure (MRPP) showed that assemblage composition differed significantly among both drainage systems and ecoregions. The associated R-statistics were, however, very low, indicating wide variation among sites within the defined landscape classifications. Regional delineations explained most of the variation in stream water chemistry, ecoregions being clearly more influential than drainage systems. For physical habitat characteristics, by contrast, the among-stream component was the major source of variation. Distinct differences attributable to stream size were observed for several metrics, especially total number of taxa and abundance of algae-scraping invertebrates. Although ecoregions clearly account for a considerable amount of variation in macroinvertebrate assemblage characteristics, we suggest that a three-tiered classification system (stratification through ecoregion and habitat type, followed by assemblage prediction within these ecologically meaningful units) will be needed for effective bioassessment of boreal running waters.

Nasal Septal Deviations: A Systematic Review of Classification Systems.

PubMed

Teixeira, Jeffrey; Certal, Victor; Chang, Edward T; Camacho, Macario

2016-01-01

Objective. To systematically review the international literature for internal nasal septal deviation classification systems and summarize them for clinical and research purposes. Data Sources. Four databases (including PubMed/MEDLINE) were systematically searched through December 16, 2015. Methods. Systematic review, adhering to PRISMA. Results. After removal of duplicates, this study screened 952 articles for relevance. A final comprehensive review of 50 articles identified that 15 of these articles met the eligibility criteria. The classification systems defined in these articles included C-shaped, S-shaped, reverse C-shaped, and reverse S-shaped descriptions of the septal deviation in both the cephalocaudal and anteroposterior dimensions. Additional studies reported use of computed tomography and categorized deviation based on predefined locations. Three studies graded the severity of septal deviations based on the amount of deflection. The systems defined in the literature also included an evaluation of nasal septal spurs and perforations. Conclusion. This systematic review ascertained that the majority of the currently published classification systems for internal nasal septal deviations can be summarized by C-shaped or reverse C-shaped, as well as S-shaped or reverse S-shaped deviations in the anteroposterior and cephalocaudal dimensions. For imaging studies, predefined points have been defined along the septum. Common terminology can facilitate future research.

[Classification of severely injured patients in the G-DRG System 2008].

PubMed

Juhra, C; Franz, D; Roeder, N; Vordemvenne, T; Raschke, M J

2009-05-01

Since the introduction of a per-case reimbursement system in Germany (German Diagnosis-Related Groups, G-DRG), the correct reimbursement for the treatment of severely injured patients has been much debated. While the classification of a patient in a polytrauma DRG follows different rules than the usual clinical definition, leading to a high number of patients not grouped as severely injured by the system, the system was also criticized in 2005 for its shortcomings in financing the treatment of severely injured patients. The development of financial reimbursement will be discussed in this paper. 167 patients treated in 2006 and 2007 due to a severe injury at the University-Hospital Münster and grouped into a polytrauma-DRG were included in this study. For each patient, cost-equivalents were estimated. For those patients treated in 2007 (n=110), exact costs were calculated following the InEK cost-calculation method. The reimbursement was calculated using the G-DRG-Systems of 2007, 2008 and 2009. Cost-equivalents/costs and clinical parameters were correlated. A total of 167 patients treated in 2006 and 2007 for a severe injury at the Münster University Hospital and grouped into a polytrauma DRG were included in this study. Cost equivalents were estimated for each patient. For those patients treated in 2007 (n=110), exact costs were calculated following the InEK (Institute for the Hospital Remuneration System) cost calculation method. Reimbursement was calculated using the G-DRG systems of 2007, 2008 and 2009. Cost equivalents/costs and clinical parameters were correlated. With the ongoing development of the G-DRG system, reimbursement for the treatment of severely injured patient has improved, but the amount of underfinancing remains substantial. As treatment of severely injured patients must be reimbursed using the G-DRG system, this system must be further adapted to better meet the needs of severely injured patients. Parameters such as total surgery time, injury severity score (ISS) and LOS in ICU could be used for this purpose. In future, data obtained in trauma networks can help optimize reimbursement for the treatment of these patients.

A comparative study of machine learning models for ethnicity classification

NASA Astrophysics Data System (ADS)

Trivedi, Advait; Bessie Amali, D. Geraldine

2017-11-01

This paper endeavours to adopt a machine learning approach to solve the problem of ethnicity recognition. Ethnicity identification is an important vision problem with its use cases being extended to various domains. Despite the multitude of complexity involved, ethnicity identification comes naturally to humans. This meta information can be leveraged to make several decisions, be it in target marketing or security. With the recent development of intelligent systems a sub module to efficiently capture ethnicity would be useful in several use cases. Several attempts to identify an ideal learning model to represent a multi-ethnic dataset have been recorded. A comparative study of classifiers such as support vector machines, logistic regression has been documented. Experimental results indicate that the logical classifier provides a much accurate classification than the support vector machine.

Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces.

PubMed

Micera, Silvestro; Rossini, Paolo M; Rigosa, Jacopo; Citi, Luca; Carpaneto, Jacopo; Raspopovic, Stanisa; Tombini, Mario; Cipriani, Christian; Assenza, Giovanni; Carrozza, Maria C; Hoffmann, Klaus-Peter; Yoshida, Ken; Navarro, Xavier; Dario, Paolo

2011-09-05

The restoration of complex hand functions by creating a novel bidirectional link between the nervous system and a dexterous hand prosthesis is currently pursued by several research groups. This connection must be fast, intuitive, with a high success rate and quite natural to allow an effective bidirectional flow of information between the user's nervous system and the smart artificial device. This goal can be achieved with several approaches and among them, the use of implantable interfaces connected with the peripheral nervous system, namely intrafascicular electrodes, is considered particularly interesting. Thin-film longitudinal intra-fascicular electrodes were implanted in the median and ulnar nerves of an amputee's stump during a four-week trial. The possibility of decoding motor commands suitable to control a dexterous hand prosthesis was investigated for the first time in this research field by implementing a spike sorting and classification algorithm. The results showed that motor information (e.g., grip types and single finger movements) could be extracted with classification accuracy around 85% (for three classes plus rest) and that the user could improve his ability to govern motor commands over time as shown by the improved discrimination ability of our classification algorithm. These results open up new and promising possibilities for the development of a neuro-controlled hand prosthesis.

[Effects of residents' care needs classification (and misclassification) in nursing homes: the example of SOSIA classification].

PubMed

Nebuloni, G; Di Giulio, P; Gregori, D; Sandonà, P; Berchialla, P; Foltran, F; Renga, G

2011-01-01

Since 2003, the Lombardy region has introduced a case-mix reimbursement system for nursing homes based on the SOSIA form which classifies residents into eight classes of frailty. In the present study the agreement between SOSIA classification and other well documented instruments, including Barthel Index, Mini Mental State Examination and Clinical Dementia Rating Scale is evaluated in 100 nursing home residents. Only 50% of residents with severe dementia have been recognized as seriously impaired when assessed with SOSIA form; since misclassification errors underestimate residents' care needs, they determine an insufficient reimbursement limiting nursing home possibility to offer care appropriate for the case-mix.

Comparison of Pixel-Based and Object-Based Classification Using Parameters and Non-Parameters Approach for the Pattern Consistency of Multi Scale Landcover

NASA Astrophysics Data System (ADS)

Juniati, E.; Arrofiqoh, E. N.

2017-09-01

Information extraction from remote sensing data especially land cover can be obtained by digital classification. In practical some people are more comfortable using visual interpretation to retrieve land cover information. However, it is highly influenced by subjectivity and knowledge of interpreter, also takes time in the process. Digital classification can be done in several ways, depend on the defined mapping approach and assumptions on data distribution. The study compared several classifiers method for some data type at the same location. The data used Landsat 8 satellite imagery, SPOT 6 and Orthophotos. In practical, the data used to produce land cover map in 1:50,000 map scale for Landsat, 1:25,000 map scale for SPOT and 1:5,000 map scale for Orthophotos, but using visual interpretation to retrieve information. Maximum likelihood Classifiers (MLC) which use pixel-based and parameters approach applied to such data, and also Artificial Neural Network classifiers which use pixel-based and non-parameters approach applied too. Moreover, this study applied object-based classifiers to the data. The classification system implemented is land cover classification on Indonesia topographic map. The classification applied to data source, which is expected to recognize the pattern and to assess consistency of the land cover map produced by each data. Furthermore, the study analyse benefits and limitations the use of methods.

Systematic Model-in-the-Loop Test of Embedded Control Systems

NASA Astrophysics Data System (ADS)

Krupp, Alexander; Müller, Wolfgang

Current model-based development processes offer new opportunities for verification automation, e.g., in automotive development. The duty of functional verification is the detection of design flaws. Current functional verification approaches exhibit a major gap between requirement definition and formal property definition, especially when analog signals are involved. Besides lack of methodical support for natural language formalization, there does not exist a standardized and accepted means for formal property definition as a target for verification planning. This article addresses several shortcomings of embedded system verification. An Enhanced Classification Tree Method is developed based on the established Classification Tree Method for Embeded Systems CTM/ES which applies a hardware verification language to define a verification environment.

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects.

PubMed

Schwaibold, M; Schöchlin, J; Bolz, A

2002-01-01

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

Inference of Ancestry in Forensic Analysis II: Analysis of Genetic Data.

PubMed

Santos, Carla; Phillips, Chris; Gomez-Tato, A; Alvarez-Dios, J; Carracedo, Ángel; Lareu, Maria Victoria

2016-01-01

Three approaches applicable to the analysis of forensic ancestry-informative marker data-STRUCTURE, principal component analysis, and the Snipper Bayesian classification system-are reviewed. Detailed step-by-step guidance is provided for adjusting parameter settings in STRUCTURE with particular regard to their effect when differentiating populations. Several enhancements to the Snipper online forensic classification portal are described, highlighting the added functionality they bring to particular aspects of ancestry-informative SNP analysis in a forensic context.

Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports

PubMed Central

Yim, Wen-wai; Kwan, Sharon W; Johnson, Guy; Yetisgen, Meliha

2017-01-01

Cancer stage information is important for clinical research. However, they are not always explicitly noted in electronic medical records. In this paper, we present our work on automatic classification of hepatocellular carcinoma (HCC) stages from free-text clinical and radiology notes. To accomplish this, we defined 11 stage parameters used in the three HCC staging systems, American Joint Committee on Cancer (AJCC), Barcelona Clinic Liver Cancer (BCLC), and Cancer of the Liver Italian Program (CLIP). After aggregating stage parameters to the patient-level, the final stage classifications were achieved using an expert-created decision logic. Each stage parameter relevant for staging was extracted using several classification methods, e.g. sentence classification and automatic information structuring, to identify and normalize text as cancer stage parameter values. Stage parameter extraction for the test set performed at 0.81 F1. Cancer stage prediction for AJCC, BCLC, and CLIP stage classifications were 0.55, 0.50, and 0.43 F1.

An efficient abnormal cervical cell detection system based on multi-instance extreme learning machine

NASA Astrophysics Data System (ADS)

Zhao, Lili; Yin, Jianping; Yuan, Lihuan; Liu, Qiang; Li, Kuan; Qiu, Minghui

2017-07-01

Automatic detection of abnormal cells from cervical smear images is extremely demanded in annual diagnosis of women's cervical cancer. For this medical cell recognition problem, there are three different feature sections, namely cytology morphology, nuclear chromatin pathology and region intensity. The challenges of this problem come from feature combination s and classification accurately and efficiently. Thus, we propose an efficient abnormal cervical cell detection system based on multi-instance extreme learning machine (MI-ELM) to deal with above two questions in one unified framework. MI-ELM is one of the most promising supervised learning classifiers which can deal with several feature sections and realistic classification problems analytically. Experiment results over Herlev dataset demonstrate that the proposed method outperforms three traditional methods for two-class classification in terms of well accuracy and less time.

Healthcare Text Classification System and its Performance Evaluation: A Source of Better Intelligence by Characterizing Healthcare Text.

PubMed

Srivastava, Saurabh Kumar; Singh, Sandeep Kumar; Suri, Jasjit S

2018-04-13

A machine learning (ML)-based text classification system has several classifiers. The performance evaluation (PE) of the ML system is typically driven by the training data size and the partition protocols used. Such systems lead to low accuracy because the text classification systems lack the ability to model the input text data in terms of noise characteristics. This research study proposes a concept of misrepresentation ratio (MRR) on input healthcare text data and models the PE criteria for validating the hypothesis. Further, such a novel system provides a platform to amalgamate several attributes of the ML system such as: data size, classifier type, partitioning protocol and percentage MRR. Our comprehensive data analysis consisted of five types of text data sets (TwitterA, WebKB4, Disease, Reuters (R8), and SMS); five kinds of classifiers (support vector machine with linear kernel (SVM-L), MLP-based neural network, AdaBoost, stochastic gradient descent and decision tree); and five types of training protocols (K2, K4, K5, K10 and JK). Using the decreasing order of MRR, our ML system demonstrates the mean classification accuracies as: 70.13 ± 0.15%, 87.34 ± 0.06%, 93.73 ± 0.03%, 94.45 ± 0.03% and 97.83 ± 0.01%, respectively, using all the classifiers and protocols. The corresponding AUC is 0.98 for SMS data using Multi-Layer Perceptron (MLP) based neural network. All the classifiers, the best accuracy of 91.84 ± 0.04% is shown to be of MLP-based neural network and this is 6% better over previously published. Further we observed that as MRR decreases, the system robustness increases and validated by standard deviations. The overall text system accuracy using all data types, classifiers, protocols is 89%, thereby showing the entire ML system to be novel, robust and unique. The system is also tested for stability and reliability.

Texture characterization for joint compression and classification based on human perception in the wavelet domain.

PubMed

Fahmy, Gamal; Black, John; Panchanathan, Sethuraman

2006-06-01

Today's multimedia applications demand sophisticated compression and classification techniques in order to store, transmit, and retrieve audio-visual information efficiently. Over the last decade, perceptually based image compression methods have been gaining importance. These methods take into account the abilities (and the limitations) of human visual perception (HVP) when performing compression. The upcoming MPEG 7 standard also addresses the need for succinct classification and indexing of visual content for efficient retrieval. However, there has been no research that has attempted to exploit the characteristics of the human visual system to perform both compression and classification jointly. One area of HVP that has unexplored potential for joint compression and classification is spatial frequency perception. Spatial frequency content that is perceived by humans can be characterized in terms of three parameters, which are: 1) magnitude; 2) phase; and 3) orientation. While the magnitude of spatial frequency content has been exploited in several existing image compression techniques, the novel contribution of this paper is its focus on the use of phase coherence for joint compression and classification in the wavelet domain. Specifically, this paper describes a human visual system-based method for measuring the degree to which an image contains coherent (perceptible) phase information, and then exploits that information to provide joint compression and classification. Simulation results that demonstrate the efficiency of this method are presented.

Revision concepts and distinctive points of the new Japanese classification for biliary tract cancers in comparison with the 7(th) edition of the Union for International Cancer Control and the American Joint Committee on Cancer staging system.

PubMed

Ohtsuka, Masayuki; Miyakawa, Shuichi; Nagino, Masato; Takada, Tadahiro; Miyazaki, Masaru

2015-03-01

The 3(rd) English edition of the Japanese classification of the biliary tract cancers (JC) is now available in this journal. The primary aim of this revision is to provide all clinicians and researchers with a common language of cancer staging at an international level. On the other hand, there are several important issues that should be solved for the optimization of the staging system. Revision concepts and major revision points of the 3(rd) English edition of the JC were reviewed. Furthermore, comparing with the 7(th) edition of staging system developed by the Union for International Cancer Control (UICC) and the American Joint Committee on Cancer (AJCC), distinctive points in the JC was discussed. In this edition of the JC, the same stage groupings as those in the UICC/AJCC staging system were basically adopted. T, N, and M categories were also identical in principle with those in the UICC/AJCC staging system, although slight modifications were proposed as the "Japanese rules". As distinctive points, perihilar cholangiocarcinomas and ampullary region carcinomas were clearly defined. Intraepithelial tumor was discriminated from invasive carcinoma at ductal resection margins. Classifications of site-specific surgical margin status remained in this edition. Histological classification was based on that in the former editions of the JC, but adopted some parts of the World Health Organization classification. The JC now share its staging system of the biliary tact carcinomas with the UICC/AJCC staging system. Future validation of the "Japanese rules" could provide important evidence to make globally standardized staging system. © 2015 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

NASA Astrophysics Data System (ADS)

Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

2016-03-01

The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

Patient casemix classification for medicare psychiatric prospective payment.

PubMed

Drozd, Edward M; Cromwell, Jerry; Gage, Barbara; Maier, Jan; Greenwald, Leslie M; Goldman, Howard H

2006-04-01

For a proposed Medicare prospective payment system for inpatient psychiatric facility treatment, the authors developed a casemix classification to capture differences in patients' real daily resource use. Primary data on patient characteristics and daily time spent in various activities were collected in a survey of 696 patients from 40 inpatient psychiatric facilities. Survey data were combined with Medicare claims data to estimate intensity-adjusted daily cost. Classification and Regression Trees (CART) analysis of average daily routine and ancillary costs yielded several hierarchical classification groupings. Regression analysis was used to control for facility and day-of-stay effects in order to compare hierarchical models with models based on the recently proposed payment system of the Centers for Medicare & Medicaid Services. CART analysis identified a small set of patient characteristics strongly associated with higher daily costs, including age, psychiatric diagnosis, deficits in daily living activities, and detox or ECT use. A parsimonious, 16-group, fully interactive model that used five major DSM-IV categories and stratified by age, illness severity, deficits in daily living activities, dangerousness, and use of ECT explained 40% (out of a possible 76%) of daily cost variation not attributable to idiosyncratic daily changes within patients. A noninteractive model based on diagnosis-related groups, age, and medical comorbidity had explanatory power of only 32%. A regression model with 16 casemix groups restricted to using "appropriate" payment variables (i.e., those with clinical face validity and low administrative burden that are easily validated and provide proper care incentives) produced more efficient and equitable payments than did a noninteractive system based on diagnosis-related groups.

Survey on large scale system control methods

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1987-01-01

The problem inherent to large scale systems such as power network, communication network and economic or ecological systems were studied. The increase in size and flexibility of future spacecraft has put those dynamical systems into the category of large scale systems, and tools specific to the class of large systems are being sought to design control systems that can guarantee more stability and better performance. Among several survey papers, reference was found to a thorough investigation on decentralized control methods. Especially helpful was the classification made of the different existing approaches to deal with large scale systems. A very similar classification is used, even though the papers surveyed are somehow different from the ones reviewed in other papers. Special attention is brought to the applicability of the existing methods to controlling large mechanical systems like large space structures. Some recent developments are added to this survey.

Correlation-based pattern recognition for implantable defibrillators.

PubMed Central

Wilkins, J.

1996-01-01

An estimated 300,000 Americans die each year from cardiac arrhythmias. Historically, drug therapy or surgery were the only treatment options available for patients suffering from arrhythmias. Recently, implantable arrhythmia management devices have been developed. These devices allow abnormal cardiac rhythms to be sensed and corrected in vivo. Proper arrhythmia classification is critical to selecting the appropriate therapeutic intervention. The classification problem is made more challenging by the power/computation constraints imposed by the short battery life of implantable devices. Current devices utilize heart rate-based classification algorithms. Although easy to implement, rate-based approaches have unacceptably high error rates in distinguishing supraventricular tachycardia (SVT) from ventricular tachycardia (VT). Conventional morphology assessment techniques used in ECG analysis often require too much computation to be practical for implantable devices. In this paper, a computationally-efficient, arrhythmia classification architecture using correlation-based morphology assessment is presented. The architecture classifies individuals heart beats by assessing similarity between an incoming cardiac signal vector and a series of prestored class templates. A series of these beat classifications are used to make an overall rhythm assessment. The system makes use of several new results in the field of pattern recognition. The resulting system achieved excellent accuracy in discriminating SVT and VT. PMID:8947674

Applicability of geomechanical classifications for estimation of strength properties in Brazilian rock masses.

PubMed

Santos, Tatiana B; Lana, Milene S; Santos, Allan E M; Silveira, Larissa R C

2017-01-01

Many authors have been proposed several correlation equations between geomechanical classifications and strength parameters. However, these correlation equations have been based in rock masses with different characteristics when compared to Brazilian rock masses. This paper aims to study the applicability of the geomechanical classifications to obtain strength parameters of three Brazilian rock masses. Four classification systems have been used; the Rock Mass Rating (RMR), the Rock Mass Quality (Q), the Geological Strength Index (GSI) and the Rock Mass Index (RMi). A strong rock mass and two soft rock masses with different degrees of weathering located in the cities of Ouro Preto and Mariana, Brazil; were selected for the study. Correlation equations were used to estimate the strength properties of these rock masses. However, such correlations do not always provide compatible results with the rock mass behavior. For the calibration of the strength values obtained through the use of classification systems, ​​stability analyses of failures in these rock masses have been done. After calibration of these parameters, the applicability of the various correlation equations found in the literature have been discussed. According to the results presented in this paper, some of these equations are not suitable for the studied rock masses.

Evaluating Support for the Current Classification of Eukaryotic Diversity

PubMed Central

Parfrey, Laura Wegener; Barbero, Erika; Lasser, Elyse; Dunthorn, Micah; Bhattacharya, Debashish; Patterson, David J; Katz, Laura A

2006-01-01

Perspectives on the classification of eukaryotic diversity have changed rapidly in recent years, as the four eukaryotic groups within the five-kingdom classification—plants, animals, fungi, and protists—have been transformed through numerous permutations into the current system of six “supergroups.” The intent of the supergroup classification system is to unite microbial and macroscopic eukaryotes based on phylogenetic inference. This supergroup approach is increasing in popularity in the literature and is appearing in introductory biology textbooks. We evaluate the stability and support for the current six-supergroup classification of eukaryotes based on molecular genealogies. We assess three aspects of each supergroup: (1) the stability of its taxonomy, (2) the support for monophyly (single evolutionary origin) in molecular analyses targeting a supergroup, and (3) the support for monophyly when a supergroup is included as an out-group in phylogenetic studies targeting other taxa. Our analysis demonstrates that supergroup taxonomies are unstable and that support for groups varies tremendously, indicating that the current classification scheme of eukaryotes is likely premature. We highlight several trends contributing to the instability and discuss the requirements for establishing robust clades within the eukaryotic tree of life. PMID:17194223

A Q-backpropagated time delay neural network for diagnosing severity of gait disturbances in Parkinson's disease.

PubMed

Nancy Jane, Y; Khanna Nehemiah, H; Arputharaj, Kannan

2016-04-01

Parkinson's disease (PD) is a movement disorder that affects the patient's nervous system and health-care applications mostly uses wearable sensors to collect these data. Since these sensors generate time stamped data, analyzing gait disturbances in PD becomes challenging task. The objective of this paper is to develop an effective clinical decision-making system (CDMS) that aids the physician in diagnosing the severity of gait disturbances in PD affected patients. This paper presents a Q-backpropagated time delay neural network (Q-BTDNN) classifier that builds a temporal classification model, which performs the task of classification and prediction in CDMS. The proposed Q-learning induced backpropagation (Q-BP) training algorithm trains the Q-BTDNN by generating a reinforced error signal. The network's weights are adjusted through backpropagating the generated error signal. For experimentation, the proposed work uses a PD gait database, which contains gait measures collected through wearable sensors from three different PD research studies. The experimental result proves the efficiency of Q-BP in terms of its improved classification accuracy of 91.49%, 92.19% and 90.91% with three datasets accordingly compared to other neural network training algorithms. Copyright © 2016 Elsevier Inc. All rights reserved.

Heterogeneity of road traffic accident rate in the Russian cities and the need of usage various methods of transport safety management

NASA Astrophysics Data System (ADS)

Petrov, A. I.; Petrova, D. A.

2017-10-01

The article considers one of the topical problems of road safety management at the federal level - the problem of the heterogeneity of road traffic accident rate in Russian cities. The article analyzes actual statistical data on road traffic accident rate in the administrative centers of Russia. The histograms of the distribution of the values of two most important road accidents characteristics - Social Risk HR and Severity Rate of Road Accidents - formed in 2016 in administrative centers of Russia are presented. On the basis of the regression model of the statistical connection between Severity Rate of Road Accidents and Social Risk HR, a classification of the Russian cities based on the level of actual road traffic accident rate was developed. On the basis of this classification a differentiated system of priority methods for organizing the safe functioning of transport systems in the cities of Russia is proposed.

Human error analysis of commercial aviation accidents: application of the Human Factors Analysis and Classification system (HFACS).

PubMed

Wiegmann, D A; Shappell, S A

2001-11-01

The Human Factors Analysis and Classification System (HFACS) is a general human error framework originally developed and tested within the U.S. military as a tool for investigating and analyzing the human causes of aviation accidents. Based on Reason's (1990) model of latent and active failures, HFACS addresses human error at all levels of the system, including the condition of aircrew and organizational factors. The purpose of the present study was to assess the utility of the HFACS framework as an error analysis and classification tool outside the military. The HFACS framework was used to analyze human error data associated with aircrew-related commercial aviation accidents that occurred between January 1990 and December 1996 using database records maintained by the NTSB and the FAA. Investigators were able to reliably accommodate all the human causal factors associated with the commercial aviation accidents examined in this study using the HFACS system. In addition, the classification of data using HFACS highlighted several critical safety issues in need of intervention research. These results demonstrate that the HFACS framework can be a viable tool for use within the civil aviation arena. However, additional research is needed to examine its applicability to areas outside the flight deck, such as aircraft maintenance and air traffic control domains.

Artificial bee colony algorithm for single-trial electroencephalogram analysis.

PubMed

Hsu, Wei-Yen; Hu, Ya-Ping

2015-04-01

In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise removal, feature extraction, feature selection, and feature classification. First, the artifacts and background noise are removed automatically by means of independent component analysis and surface Laplacian filter, respectively. Several potential features, such as band power, autoregressive model, and coherence and phase-locking value, are then extracted for subsequent classification. Next, artificial bee colony (ABC) algorithm is used to select features from the aforementioned feature combination. Finally, selected subfeatures are classified by support vector machine. Comparing with and without artifact removal and feature selection, using a genetic algorithm on single-trial EEG data for 6 subjects, the results indicate that the proposed system is promising and suitable for brain-computer interface applications. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Bridging the Gap in Military Robotics (Combler le Fosse Existant dans le Domaine de la Robotique Militaire)

DTIC Science & Technology

2008-11-01

systems must be evaluated at the platform level as well ( regenerative braking and similar systems). 4.4.4 The Important Gaps Several gaps on robot...in three main categories : • Mobility function: • Obstacle avoidance and negotiation; • Terrain modelling and classification; and • Transport in

Characteristics of dysphagia in children with cerebral palsy, related to gross motor function.

PubMed

Kim, Joon-Sung; Han, Zee-A; Song, Dae Heon; Oh, Hyun-Mi; Chung, Myung Eun

2013-10-01

The aim of this study was to report the characteristics of dysphagia in children with cerebral palsy (CP), related to gross motor function. Videofluoroscopic swallow study was performed in 29 children with CP, according to the manual of Logemann. Five questions about oromotor dysfunction were answered. Gross motor function level was classified by the Gross Motor Function Classification System Expanded and Revised. The results of the videofluoroscopic swallowing studies showed that reduced lip closure, inadequate bolus formation, residue in the oral cavity, delayed triggering of pharyngeal swallow, reduced larynx elevation, coating on the pharyngeal wall, delayed pharyngeal transit time, multiple swallow, and aspiration were significantly more common in the severe group (Gross Motor Function Classification System Expanded and Revised IV or V). As for aspiration, 50% of the children with severe CP had problems, but only 14.3% of them with moderate (Gross Motor Function Classification System Expanded and Revised III) CP and none of them with mild CP had abnormalities. In addition, five of the seven aspiration cases occurred silently. This study shows that dysphagia is closely related to gross motor function in children with CP. Silent aspiration was observed in the moderate to severe CP groups. Aspiration is an important cause of medical problems such as acute and chronic lung disease, and associated respiratory complications contribute significantly in increasing morbidity and mortality in these patient groups. Therefore, the authors suggest that early dysphagia evaluation including videofluoroscopic swallow study is necessary in managing feeding problems and may prevent chronic aspiration, malnutrition, and infections.

Comparison of World Health Organization and Asia-Pacific body mass index classifications in COPD patients.

PubMed

Lim, Jeong Uk; Lee, Jae Ha; Kim, Ju Sang; Hwang, Yong Il; Kim, Tae-Hyung; Lim, Seong Yong; Yoo, Kwang Ha; Jung, Ki-Suck; Kim, Young Kyoon; Rhee, Chin Kook

2017-01-01

A low body mass index (BMI) is associated with increased mortality and low health-related quality of life in patients with COPD. The Asia-Pacific classification of BMI has a lower cutoff for overweight and obese categories compared to the World Health Organization (WHO) classification. The present study assessed patients with COPD among different BMI categories according to two BMI classification systems: WHO and Asia-Pacific. Patients with COPD aged 40 years or older from the Korean COPD Subtype Study cohort were selected for evaluation. We enrolled 1,462 patients. Medical history including age, sex, St George's Respiratory Questionnaire (SGRQ-C), the modified Medical Research Council (mMRC) dyspnea scale, and post-bronchodilator forced expiratory volume in 1 second (FEV 1 ) were evaluated. Patients were categorized into different BMI groups according to the two BMI classification systems. FEV 1 and the diffusing capacity of the lung for carbon monoxide (DLCO) percentage revealed an inverse "U"-shaped pattern as the BMI groups changed from underweight to obese when WHO cutoffs were applied. When Asia-Pacific cutoffs were applied, FEV 1 and DLCO (%) exhibited a linearly ascending relationship as the BMI increased, and the percentage of patients in the overweight and obese groups linearly decreased with increasing severity of the Global Initiative for Chronic Obstructive Lung Disease criteria. From the underweight to the overweight groups, SGRQ-C and mMRC had a decreasing relationship in both the WHO and Asia-Pacific classifications. The prevalence of comorbidities in the different BMI groups showed similar trends in both BMI classifications systems. The present study demonstrated that patients with COPD who have a high BMI have better pulmonary function and health-related quality of life and reduced dyspnea symptoms. Furthermore, the Asia-Pacific BMI classification more appropriately reflects the correlation of obesity and disease manifestation in Asian COPD patients than the WHO classification.

A standard lexicon for biodiversity conservation: unified classifications of threats and actions.

PubMed

Salafsky, Nick; Salzer, Daniel; Stattersfield, Alison J; Hilton-Taylor, Craig; Neugarten, Rachel; Butchart, Stuart H M; Collen, Ben; Cox, Neil; Master, Lawrence L; O'Connor, Sheila; Wilkie, David

2008-08-01

An essential foundation of any science is a standard lexicon. Any given conservation project can be described in terms of the biodiversity targets, direct threats, contributing factors at the project site, and the conservation actions that the project team is employing to change the situation. These common elements can be linked in a causal chain, which represents a theory of change about how the conservation actions are intended to bring about desired project outcomes. If project teams want to describe and share their work and learn from one another, they need a standard and precise lexicon to specifically describe each node along this chain. To date, there have been several independent efforts to develop standard classifications for the direct threats that affect biodiversity and the conservation actions required to counteract these threats. Recognizing that it is far more effective to have only one accepted global scheme, we merged these separate efforts into unified classifications of threats and actions, which we present here. Each classification is a hierarchical listing of terms and associated definitions. The classifications are comprehensive and exclusive at the upper levels of the hierarchy, expandable at the lower levels, and simple, consistent, and scalable at all levels. We tested these classifications by applying them post hoc to 1191 threatened bird species and 737 conservation projects. Almost all threats and actions could be assigned to the new classification systems, save for some cases lacking detailed information. Furthermore, the new classification systems provided an improved way of analyzing and comparing information across projects when compared with earlier systems. We believe that widespread adoption of these classifications will help practitioners more systematically identify threats and appropriate actions, managers to more efficiently set priorities and allocate resources, and most important, facilitate cross-project learning and the development of a systematic science of conservation.

Performances of Machine Learning Algorithms for Binary Classification of Network Anomaly Detection System

NASA Astrophysics Data System (ADS)

Nawir, Mukrimah; Amir, Amiza; Lynn, Ong Bi; Yaakob, Naimah; Badlishah Ahmad, R.

2018-05-01

The rapid growth of technologies might endanger them to various network attacks due to the nature of data which are frequently exchange their data through Internet and large-scale data that need to be handle. Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. Several issues regarding these available labelled network datasets are discussed in this paper. The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.

Feature Extraction and Selection Strategies for Automated Target Recognition

NASA Technical Reports Server (NTRS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-01-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory region of-interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Feature extraction and selection strategies for automated target recognition

NASA Astrophysics Data System (ADS)

Greene, W. Nicholas; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin

2010-04-01

Several feature extraction and selection methods for an existing automatic target recognition (ATR) system using JPLs Grayscale Optical Correlator (GOC) and Optimal Trade-Off Maximum Average Correlation Height (OT-MACH) filter were tested using MATLAB. The ATR system is composed of three stages: a cursory regionof- interest (ROI) search using the GOC and OT-MACH filter, a feature extraction and selection stage, and a final classification stage. Feature extraction and selection concerns transforming potential target data into more useful forms as well as selecting important subsets of that data which may aide in detection and classification. The strategies tested were built around two popular extraction methods: Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Performance was measured based on the classification accuracy and free-response receiver operating characteristic (FROC) output of a support vector machine(SVM) and a neural net (NN) classifier.

Brain-computer interface design using alpha wave

NASA Astrophysics Data System (ADS)

Zhao, Hai-bin; Wang, Hong; Liu, Chong; Li, Chun-sheng

2010-01-01

A brain-computer interface (BCI) is a novel communication system that translates brain activity into commands for a computer or other electronic devices. BCI system based on non-invasive scalp electroencephalogram (EEG) has become a hot research area in recent years. BCI technology can help improve the quality of life and restore function for people with severe motor disabilities. In this study, we design a real-time asynchronous BCI system using Alpha wave. The basic theory of this BCI system is alpha wave-block phenomenon. Alpha wave is the most prominent wave in the whole realm of brain activity. This system includes data acquisition, feature selection and classification. The subject can use this system easily and freely choose anyone of four commands with only short-time training. The results of the experiment show that this BCI system has high classification accuracy, and has potential application for clinical engineering and is valuable for further research.

Severity of Airflow Obstruction in Chronic Obstructive Pulmonary Disease (COPD): Proposal for a New Classification.

PubMed

Coton, Sonia; Vollmer, William M; Bateman, Eric; Marks, Guy B; Tan, Wan; Mejza, Filip; Juvekar, Sanjay; Janson, Christer; Mortimer, Kevin; P A, Mahesh; Buist, A Sonia; Burney, Peter G J

2017-10-01

Current classifications of Chronic Obstructive Pulmonary Disease (COPD) severity are complex and do not grade levels of obstruction. Obstruction is a simpler construct and independent of ethnicity. We constructed an index of obstruction severity based on the FEV 1 /FVC ratio, with cut-points dividing the Burden of Obstructive Lung Disease (BOLD) study population into four similarly sized strata to those created by the GOLD criteria that uses FEV 1 . We measured the agreement between classifications and the validity of the FEV 1 -based classification in identifying the level of obstruction as defined by the new groupings. We compared the strengths of association of each classification with quality of life (QoL), MRC dyspnoea score and the self-reported exacerbation rate. Agreement between classifications was only fair. FEV 1 -based criteria for moderate COPD identified only 79% of those with moderate obstruction and misclassified half of the participants with mild obstruction as having more severe COPD. Both scales were equally strongly associated with QoL, exertional dyspnoea and respiratory exacerbations. Severity assessed using the FEV 1 /FVC ratio is only in moderate agreement with the severity assessed using FEV 1 but is equally strongly associated with other outcomes. Severity assessed using the FEV 1 /FVC ratio is likely to be independent of ethnicity.

Serum C-reactive protein level in COPD patients stratified according to GOLD 2011 grading classification

PubMed Central

Lin, Yi-Hua; Wang, Wan-Yu; Hu, Su-Xian; Shi, Yong-Hong

2016-01-01

Background and Objective: The Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2011 grading classification has been used to evaluate the severity of patients with chronic obstructive pulmonary disease (COPD). However, little is known about the relationship between the systemic inflammation and this classification. We aimed to study the relationship between serum CRP and the components of the GOLD 2011 grading classification. Methods: C-reactive protein (CRP) levels were measured in 391 clinically stable COPD patients and in 50 controls from June 2, 2015 to October 31, 2015 in the First Affiliated Hospital of Xiamen University. The association between CRP levels and the components of the GOLD 2011 grading classification were assessed. Results: Correlation was found with the following variables: GOLD 2011 group (0.240), age (0.227), pack year (0.136), forced expiratory volume in one second % predicted (FEV1%; -0.267), forced vital capacity % predicted (-0.210), number of acute exacerbations in the past year (0.265), number of hospitalized exacerbations in the past year (0.165), British medical Research Council dyspnoea scale (0.121), COPD assessment test score (CAT, 0.233). Using multivariate analysis, FEV1% and CAT score manifested the strongest negative association with CRP levels. Conclusions: CRP levels differ in COPD patients among groups A-D based on GOLD 2011 grading classification. CRP levels are associated with several important clinical variables, of which FEV1% and CAT score manifested the strongest negative correlation. PMID:28083044

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

[Research progress in molecular classification of gastric cancer].

PubMed

Zhou, Menglong; Li, Guichao; Zhang, Zhen

2016-09-25

Gastric cancer(GC) is a highly heterogeneous malignancy. The present widely used histopathological classifications have gradually failed to meet the needs of individualized diagnosis and treatment. Development of technologies such as microarray and next-generation sequencing (NGS) has allowed GC to be studied at the molecular level. Mechanisms about tumorigenesis and progression of GC can be elucidated in the aspects of gene mutations, chromosomal alterations, transcriptional and epigenetic changes, on the basis of which GC can be divided into several subtypes. The classifications of Tan's, Lei's, TCGA and ACRG are relatively comprehensive. Especially the TCGA and ACRG classifications have large sample size and abundant molecular profiling data, thus, the genomic characteristics of GC can be depicted more accurately. However, significant differences between both classifications still exist so that they cannot be substituted for each other. So far there is no widely accepted molecular classification of GC. Compared with TCGA classification, ACRG system may have more clinical significance in Chinese GC patients since the samples are mostly from Asian population and show better association with prognosis. The molecular classification of GC may provide the theoretical and experimental basis for early diagnosis, therapeutic efficacy prediction and treatment stratification while their clinical application is still limited. Future work should involve the application of molecular classifications in the clinical settings for improving the medical management of GC.

A hybrid computational approach for efficient Alzheimer's disease classification based on heterogeneous data.

PubMed

Ding, Xuemei; Bucholc, Magda; Wang, Haiying; Glass, David H; Wang, Hui; Clarke, Dave H; Bjourson, Anthony John; Dowey, Le Roy C; O'Kane, Maurice; Prasad, Girijesh; Maguire, Liam; Wong-Lin, KongFatt

2018-06-27

There is currently a lack of an efficient, objective and systemic approach towards the classification of Alzheimer's disease (AD), due to its complex etiology and pathogenesis. As AD is inherently dynamic, it is also not clear how the relationships among AD indicators vary over time. To address these issues, we propose a hybrid computational approach for AD classification and evaluate it on the heterogeneous longitudinal AIBL dataset. Specifically, using clinical dementia rating as an index of AD severity, the most important indicators (mini-mental state examination, logical memory recall, grey matter and cerebrospinal volumes from MRI and active voxels from PiB-PET brain scans, ApoE, and age) can be automatically identified from parallel data mining algorithms. In this work, Bayesian network modelling across different time points is used to identify and visualize time-varying relationships among the significant features, and importantly, in an efficient way using only coarse-grained data. Crucially, our approach suggests key data features and their appropriate combinations that are relevant for AD severity classification with high accuracy. Overall, our study provides insights into AD developments and demonstrates the potential of our approach in supporting efficient AD diagnosis.

Clashing Diagnostic Approaches: DSM-ICD versus RDoC

PubMed Central

Lilienfeld, Scott O.; Treadway, Michael T.

2016-01-01

Since at least the middle of the past century, one overarching model of psychiatric classification, namely, that of the Diagnostic and Statistical Manual of Mental Disorders and International Classification of Diseases (DSM-ICD), has reigned supreme. This DSM-ICD approach embraces an Aristotelian view of mental disorders as largely discrete entities that are characterized by distinctive signs, symptoms, and natural histories. Over the past several years, however, a competing vision, namely, the Research Domain Criteria (RDoC) initiative launched by the National Institute of Mental Health, has emerged in response to accumulating anomalies within the DSM-ICD system. In contrast to DSM-ICD, RDoC embraces a Galilean view of psychopathology as the product of dysfunctions in neural circuitry. RDoC appears to be a valuable endeavor that holds out the long-term promise of an alternative system of mental illness classification. We delineate three sets of pressing challenges – conceptual, methodological, and logistical/pragmatic – that must be addressed for RDoC to realize its scientific potential, and conclude with a call for further research, including investigation of a rapprochement between Aristotelian and Galilean approaches to psychiatric classification. PMID:26845519

Impact of IRT item misfit on score estimates and severity classifications: an examination of PROMIS depression and pain interference item banks.

PubMed

Zhao, Yue

2017-03-01

In patient-reported outcome research that utilizes item response theory (IRT), using statistical significance tests to detect misfit is usually the focus of IRT model-data fit evaluations. However, such evaluations rarely address the impact/consequence of using misfitting items on the intended clinical applications. This study was designed to evaluate the impact of IRT item misfit on score estimates and severity classifications and to demonstrate a recommended process of model-fit evaluation. Using secondary data sources collected from the Patient-Reported Outcome Measurement Information System (PROMIS) wave 1 testing phase, analyses were conducted based on PROMIS depression (28 items; 782 cases) and pain interference (41 items; 845 cases) item banks. The identification of misfitting items was assessed using Orlando and Thissen's summed-score item-fit statistics and graphical displays. The impact of misfit was evaluated according to the agreement of both IRT-derived T-scores and severity classifications between inclusion and exclusion of misfitting items. The examination of the presence and impact of misfit suggested that item misfit had a negligible impact on the T-score estimates and severity classifications with the general population sample in the PROMIS depression and pain interference item banks, implying that the impact of item misfit was insignificant. Findings support the T-score estimates in the two item banks as robust against item misfit at both the group and individual levels and add confidence to the use of T-scores for severity diagnosis in the studied sample. Recommendations on approaches for identifying item misfit (statistical significance) and assessing the misfit impact (practical significance) are given.

Diagnostic criteria, severity classification and guidelines of systemic sclerosis.

PubMed

Asano, Yoshihide; Jinnin, Masatoshi; Kawaguchi, Yasushi; Kuwana, Masataka; Goto, Daisuke; Sato, Shinichi; Takehara, Kazuhiko; Hatano, Masaru; Fujimoto, Manabu; Mugii, Naoki; Ihn, Hironobu

2018-06-01

Several effective drugs have been identified for the treatment of systemic sclerosis (SSc). However, in advanced cases, not only their effectiveness is reduced but they may be also harmful due to their side-effects. Therefore, early diagnosis and early treatment is most important for the treatment of SSc. We established diagnostic criteria for SSc in 2003 and early diagnostic criteria for SSc in 2011, for the purpose of developing evaluation of each organ in SSc. Moreover, in November 2013, the American College of Rheumatology and the European Rheumatology Association jointly developed new diagnostic criteria for increasing their sensitivity and specificity, so we revised our diagnostic criteria and severity classification of SSc. Furthermore, we have revised the clinical guideline based on the newest evidence. In particular, the clinical guideline was established by clinical questions based on evidence-based medicine according to the New Minds Clinical Practice Guideline Creation Manual (version 1.0). We aimed to make the guideline easy to use and reliable based on the newest evidence, and to present guidance as specific as possible for various clinical problems in treatment of SSc. © 2018 Japanese Dermatological Association.

PI2GIS: processing image to geographical information systems, a learning tool for QGIS

NASA Astrophysics Data System (ADS)

Correia, R.; Teodoro, A.; Duarte, L.

2017-10-01

To perform an accurate interpretation of remote sensing images, it is necessary to extract information using different image processing techniques. Nowadays, it became usual to use image processing plugins to add new capabilities/functionalities integrated in Geographical Information System (GIS) software. The aim of this work was to develop an open source application to automatically process and classify remote sensing images from a set of satellite input data. The application was integrated in a GIS software (QGIS), automating several image processing steps. The use of QGIS for this purpose is justified since it is easy and quick to develop new plugins, using Python language. This plugin is inspired in the Semi-Automatic Classification Plugin (SCP) developed by Luca Congedo. SCP allows the supervised classification of remote sensing images, the calculation of vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) and other image processing operations. When analysing SCP, it was realized that a set of operations, that are very useful in teaching classes of remote sensing and image processing tasks, were lacking, such as the visualization of histograms, the application of filters, different image corrections, unsupervised classification and several environmental indices computation. The new set of operations included in the PI2GIS plugin can be divided into three groups: pre-processing, processing, and classification procedures. The application was tested consider an image from Landsat 8 OLI from a North area of Portugal.

Definition and classification of chyle leak after pancreatic operation: A consensus statement by the International Study Group on Pancreatic Surgery.

PubMed

Besselink, Marc G; van Rijssen, L Bengt; Bassi, Claudio; Dervenis, Christos; Montorsi, Marco; Adham, Mustapha; Asbun, Horacio J; Bockhorn, Maximillian; Strobel, Oliver; Büchler, Markus W; Busch, Olivier R; Charnley, Richard M; Conlon, Kevin C; Fernández-Cruz, Laureano; Fingerhut, Abe; Friess, Helmut; Izbicki, Jakob R; Lillemoe, Keith D; Neoptolemos, John P; Sarr, Michael G; Shrikhande, Shailesh V; Sitarz, Robert; Vollmer, Charles M; Yeo, Charles J; Hartwig, Werner; Wolfgang, Christopher L; Gouma, Dirk J

2017-02-01

Recent literature suggests that chyle leak may complicate up to 10% of pancreatic resections. Treatment depends on its severity, which may include chylous ascites. No international consensus definition or grading system of chyle leak currently is available. The International Study Group on Pancreatic Surgery, an international panel of pancreatic surgeons working in well-known, high-volume centers, reviewed the literature and worked together to establish a consensus on the definition and classification of chyle leak after pancreatic operation. Chyle leak was defined as output of milky-colored fluid from a drain, drain site, or wound on or after postoperative day 3, with a triglyceride content ≥110 mg/dL (≥1.2 mmol/L). Three different grades of severity were defined according to the management needed: grade A, no specific intervention other than oral dietary restrictions; grade B, prolongation of hospital stay, nasoenteral nutrition with dietary restriction, total parenteral nutrition, octreotide, maintenance of surgical drains, or placement of new percutaneous drains; and grade C, need for other more invasive in-hospital treatment, intensive care unit admission, or mortality. This classification and grading system for chyle leak after pancreatic resection allows for comparison of outcomes between series. As with the other the International Study Group on Pancreatic Surgery consensus statements, this classification should facilitate communication and evaluation of different approaches to the prevention and treatment of this complication. Copyright © 2016 Elsevier Inc. All rights reserved.

[Scores and stages in pneumology].

PubMed

Kuhn, Max

2013-10-01

Useful scales and classifications for patients with pulmonary diseases are discussed. The modified Medical Research Council breathlessness scale (mMRC) is a measure of disability in lung patients. The GOLD classifications, the COPD-Assessment Test (CAT) and the BODE Index are important to classify the severity of COPD and to measure the disability of these patients. The Geneva score is a clinical prediction rule used in determining the pre-test probability of pulmonary embolism. The Pulmonary Embolism Severity Index (PESI) is a scoring system used to predict 30 day mortality in patients with pulmonary embolism. The Epworth Sleepiness Scale is intended to measure daytime sleepiness in patients with sleep apnea syndrome. The Asthma Controll Test (ACT) determines if asthma symptoms are well controlled.

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines

PubMed Central

del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J.; Raboso, Mariano

2015-01-01

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements. PMID:26091392

Acoustic Biometric System Based on Preprocessing Techniques and Linear Support Vector Machines.

PubMed

del Val, Lara; Izquierdo-Fuente, Alberto; Villacorta, Juan J; Raboso, Mariano

2015-06-17

Drawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation-based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking-to reduce the dimensions of images-and binarization-to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements.

Diagnosis and treatment of movement system impairment syndromes.

PubMed

Sahrmann, Shirley; Azevedo, Daniel C; Dillen, Linda Van

Diagnoses and treatments based on movement system impairment syndromes were developed to guide physical therapy treatment. This masterclass aims to describe the concepts on that are the basis of the syndromes and treatment and to provide the current research on movement system impairment syndromes. The conceptual basis of the movement system impairment syndromes is that sustained alignment in a non-ideal position and repeated movements in a specific direction are thought to be associated with several musculoskeletal conditions. Classification into movement system impairment syndromes and treatment has been described for all body regions. The classification involves interpreting data from standardized tests of alignments and movements. Treatment is based on correcting the impaired alignment and movement patterns as well as correcting the tissue adaptations associated with the impaired alignment and movement patterns. The reliability and validity of movement system impairment syndromes have been partially tested. Although several case reports involving treatment using the movement system impairment syndromes concept have been published, efficacy of treatment based on movement system impairment syndromes has not been tested in randomized controlled trials, except in people with chronic low back pain. Copyright © 2017 Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia. Publicado por Elsevier Editora Ltda. All rights reserved.

Are All Community Colleges Alike?

ERIC Educational Resources Information Center

Cohen, Arthur M.

While there are many ways to differentiate among community colleges (size, control, student characteristics, etc.), there have been few attempts to categorize them. The Carnegie Foundation's classification system, published first in 1971 and since revised several times, categorizes research universities, comprehensive institutions, liberal arts…

Email recruitment to use web decision support tools for pneumonia.

PubMed

Flanagan, James R; Peterson, Michael; Dayton, Charles; Strommer Pace, Lori; Plank, Andrew; Walker, Kristy; Carlson, William S

2002-01-01

Application of guidelines to improve clinical decisions for Community Acquired Pneumonia (CAP) patients depends on accurate information about specific facts of each case and on presenting guideline support at the time decisions are being made. We report here on a system designed to solicit information from physicians about their CAP patients in order to classify CAP and present appropriate guidelines for type of care, length of stay, and use of antibiotics. We used elements of three existing information systems to create a achieve these goals: professionals coding diagnoses captured by the existing clinical information system (CIS), email, and web-based decision support tools including a pneumonia severity evaluation tool (SET). The non-secure IS components (email and web) were able to link to information in the CIS using tokens that do not reveal confidential patient-identifiable information. We examined their response to this strategy and the accuracy of pneumonia classification using this approach compared to chart review as a gold standard. On average physicians responded to email solicitations 50% of the time over the 14 month study. Also using this standard, we examined various information triggers for case finding. Professional coding of the primary reason for admission as pneumonia was fairly sensitive as an indicator of CAP. Physician use of the web SET was insensitive but fairly specific. Pneumonia classification using the SET was very reliable compared to experts' chart review using the same algorithm. We examined the distribution of severity of pneumonia for cases of pneumonia found by the various information triggers and for each severity the average length of stay. The distribution found by both chart review and by SET has demonstrated a shift toward more severe cases being admitted compared to only 3 years ago. The length of stay for level of severity is above expectations published by guidelines even for cases of true CAP by chart review. We suggest that the Fine classification system may not adequately describe patients in this setting. Physicians frequently responded that the guidelines presented did not fit their patients.

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

An automatic graph-based approach for artery/vein classification in retinal images.

PubMed

Dashtbozorg, Behdad; Mendonça, Ana Maria; Campilho, Aurélio

2014-03-01

The classification of retinal vessels into artery/vein (A/V) is an important phase for automating the detection of vascular changes, and for the calculation of characteristic signs associated with several systemic diseases such as diabetes, hypertension, and other cardiovascular conditions. This paper presents an automatic approach for A/V classification based on the analysis of a graph extracted from the retinal vasculature. The proposed method classifies the entire vascular tree deciding on the type of each intersection point (graph nodes) and assigning one of two labels to each vessel segment (graph links). Final classification of a vessel segment as A/V is performed through the combination of the graph-based labeling results with a set of intensity features. The results of this proposed method are compared with manual labeling for three public databases. Accuracy values of 88.3%, 87.4%, and 89.8% are obtained for the images of the INSPIRE-AVR, DRIVE, and VICAVR databases, respectively. These results demonstrate that our method outperforms recent approaches for A/V classification.

The 7th lung cancer TNM classification and staging system: Review of the changes and implications.

PubMed

Mirsadraee, Saeed; Oswal, Dilip; Alizadeh, Yalda; Caulo, Andrea; van Beek, Edwin

2012-04-28

Lung cancer is the most common cause of death from cancer in males, accounting for more than 1.4 million deaths in 2008. It is a growing concern in China, Asia and Africa as well. Accurate staging of the disease is an important part of the management as it provides estimation of patient's prognosis and identifies treatment sterategies. It also helps to build a database for future staging projects. A major revision of lung cancer staging has been announced with effect from January 2010. The new classification is based on a larger surgical and non-surgical cohort of patients, and thus more accurate in terms of outcome prediction compared to the previous classification. There are several original papers regarding this new classification which give comprehensive description of the methodology, the changes in the staging and the statistical analysis. This overview is a simplified description of the changes in the new classification and their potential impact on patients' treatment and prognosis.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality and intensive care admission among traumatic brain-injured patients.

PubMed

Gagné, Mathieu; Moore, Lynne; Sirois, Marie-Josée; Simard, Marc; Beaudoin, Claudia; Kuimi, Brice Lionel Batomen

2017-02-01

The International Classification of Diseases (ICD) is the main classification system used for population-based traumatic brain injury (TBI) surveillance activities but does not contain direct information on injury severity. International Classification of Diseases-based injury severity measures can be empirically derived or mapped to the Abbreviated Injury Scale, but no single approach has been formally recommended for TBI. The aim of this study was to compare the accuracy of different ICD-based injury severity measures for predicting in-hospital mortality and intensive care unit (ICU) admission in TBI patients. We conducted a population-based retrospective cohort study. We identified all patients 16 years or older with a TBI diagnosis who received acute care between April 1, 2006, and March 31, 2013, from the Quebec Hospital Discharge Database. The accuracy of five ICD-based injury severity measures for predicting mortality and ICU admission was compared using measures of discrimination (area under the receiver operating characteristic curve [AUC]) and calibration (calibration plot and the Hosmer-Lemeshow goodness-of-fit statistic). Of 31,087 traumatic brain-injured patients in the study population, 9.0% died in hospital, and 34.4% were admitted to the ICU. Among ICD-based severity measures that were assessed, the multiplied derivative of ICD-based Injury Severity Score (ICISS-Multiplicative) demonstrated the best discriminative ability for predicting in-hospital mortality (AUC, 0.858; 95% confidence interval, 0.852-0.864) and ICU admissions (AUC, 0.813; 95% confidence interval, 0.808-0.818). Calibration assessments showed good agreement between observed and predicted in-hospital mortality for ICISS measures. All severity measures presented high agreement between observed and expected probabilities of ICU admission for all deciles of risk. The ICD-based injury severity measures can be used to accurately predict in-hospital mortality and ICU admission in TBI patients. The ICISS-Multiplicative generally outperformed other ICD-based injury severity measures and should be preferred to control for differences in baseline characteristics between TBI patients in surveillance activities or injury research when only ICD codes are available. Prognostic study, level III.

A spatially constrained ecological classification: rationale, methodology and implementation

Treesearch

Franz Mora; Louis Iverson; Louis Iverson

2002-01-01

The theory, methodology and implementation for an ecological and spatially constrained classification are presented. Ecological and spatial relationships among several landscape variables are analyzed in order to define a new approach for a landscape classification. Using ecological and geostatistical analyses, several ecological and spatial weights are derived to...

Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting.

PubMed

Lam, Carlos; Chen, Chang-I; Chuang, Chia-Chang; Wu, Chia-Chieh; Yu, Shih-Hsiang; Chang, Kai-Kuo; Chiu, Wen-Ta

2018-05-18

Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model's pros and cons are also compared to those of other current models.

Comparative study of classification algorithms for immunosignaturing data

PubMed Central

2012-01-01

Background High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data. Results We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy. Conclusions ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties. PMID:22720696

Continuous robust sound event classification using time-frequency features and deep learning

PubMed Central

Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification. PMID:28892478

Continuous robust sound event classification using time-frequency features and deep learning.

PubMed

McLoughlin, Ian; Zhang, Haomin; Xie, Zhipeng; Song, Yan; Xiao, Wei; Phan, Huy

2017-01-01

The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification.

The Classification of Swanson for Congenital Anomalies of Upper Limb Modified by the Japanese Society for Surgery of the Hand (JSSH).

PubMed

Iba, Kousuke; Horii, Emiko; Ogino, Toshihiko; Kazuki, Kenichi; Kashiwa, Katsuhiko

2015-01-01

The aim of this study is to introduce the classification of Swanson for congenital anomalies of upper limb modified by the Japanese Society for Surgery of the Hand (the JSSH modification) in English. The Swanson classification has been widely accepted by most hand surgeons. However, several authors have suggested that complex cases, particularly those involving the complex spectrum of cleft hand and symbrachydactyly, are difficult to classify into the classification schemes. In the JSSH modification, brachysyndactyly, so-called atypical cleft hand and transverse deficiency are included under the same concept of transverse deficiency. Cleft hand, central polydactyly, and syndactyly are included in the same category of abnormal induction of digital rays. We believe that the JSSH modification system is effective in providing hand surgeons with the clinical features and conditions for congenital anomalies.

75 FR 9593 - Agency Information Collection Activities; Proposed Renewal of Several Currently Approved...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-03

... institutions participating in pesticide, fertilizer, and other agricultural chemical manufacturing [[Page 9595...: Entities potentially affected by this ICR include individuals or entities engaged in pesticide, fertilizer, and other agricultural chemical manufacturing (North American Industrial Classification System (NAICS...

The efficacy of the modified classification system of soft tissue injury in extension injury of the lower cervical spine.

PubMed

Song, Kyung-Jin; Kim, Gyu-Hyung; Lee, Kwang-Bok

2008-07-01

To classify comprehensively the severity of soft tissue injury for extension injuries of the lower cervical spine by magnetic resonance imaging (MRI). To investigate severity of extension injuries using a modified classification system for soft tissue injury by MRI, and to determine the possibility of predicting cord injury by determining the severity of soft tissue injury. It is difficult to diagnose extension injuries by plain radiography and computed tomography. MRI is considered to be the best method of diagnosing soft tissue injuries. The authors examined whether an MRI based diagnostic standard could be devised for extension injuries of the cervical spine. MRI was performed before surgery in 81 patients that had experienced a distractive-extension injury during the past 5 years. Severities of soft tissue injury were subdivided into 5 stages. The retropharyngeal space and the retrotracheal space were measured, and their correlations with the severity of soft tissue injury were examined, as was the relation between canal stenosis and cord injury. Cord injury developed in injuries greater than Grade III (according to our devised system) accompanied by posterior longitudinal ligament rupture (P < 0.01). As the severity of soft tissue injury increased, the cord signal change increased (P < 0.01), the retropharyngeal space and the retrotracheal space increased, and swelling severity in each stage were statistically significant (P < 0.01). In canal stenosis patients, soft tissue damage and cord injury were not found to be associated (P = 0.45). In cases of distractive-extension injury, levels of soft tissue injury were determined accurately by MRI. Moreover, the severity of soft tissue injury was found to be closely associated with the development of cord injury.

Ordering the discipline: classification in the history of science. Introduction.

PubMed

Weldon, Stephen P

2013-09-01

Classification of the history of science has a long history, and the essays in this Focus section explore that history and its consequences from several different angles. Two of the papers deal with how classifying schemes in bibliography have evolved. A third looks at the way archival organization has changed over the years. Finally, the last essay explores the intersection of human and machine classifying systems. All four contributions look closely at the ramifications of the digital revolution for the way we organize the knowledge of the discipline.

Large-scale gene function analysis with the PANTHER classification system.

PubMed

Mi, Huaiyu; Muruganujan, Anushya; Casagrande, John T; Thomas, Paul D

2013-08-01

The PANTHER (protein annotation through evolutionary relationship) classification system (http://www.pantherdb.org/) is a comprehensive system that combines gene function, ontology, pathways and statistical analysis tools that enable biologists to analyze large-scale, genome-wide data from sequencing, proteomics or gene expression experiments. The system is built with 82 complete genomes organized into gene families and subfamilies, and their evolutionary relationships are captured in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models or HMMs). Genes are classified according to their function in several different ways: families and subfamilies are annotated with ontology terms (Gene Ontology (GO) and PANTHER protein class), and sequences are assigned to PANTHER pathways. The PANTHER website includes a suite of tools that enable users to browse and query gene functions, and to analyze large-scale experimental data with a number of statistical tests. It is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. In the 2013 release of PANTHER (v.8.0), in addition to an update of the data content, we redesigned the website interface to improve both user experience and the system's analytical capability. This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system.

The role of Brazilian National Health Information Systems in assessing the impact of Zika virus outbreak.

PubMed

Pavão, Ana Luiza Braz; Barcellos, Christovam; Pedroso, Marcel; Boccolini, Cristiano; Romero, Dália

2017-01-01

The Zika virus (ZIKV) epidemic has become a public health emergency following its association with severe neurological complications. We aim to discuss how the Brazilian National Health Information Systems can help to assess the impact of the ZIKV epidemic on health outcomes potentially related to ZIKV. Health outcomes potentially related to ZIKV infection were described based on a literature review of published studies on ZIKV infection outcomes and on recent protocols developed and published by the Brazilian Ministry of Health for different stages of the life cycle. These outcomes were correlated with the International Classification of Diseases 10th Revision (ICD-10) classification system, as this is the diagnostic classification registered in the Health Information System. A suggested list of 50 clinical manifestations, dispersed into 4 ICD chapters, and their information sources was created to help monitor the ZIKV epidemics and trends. Correlation of these selected ICD-10 codes and the HIS, as well as, a review of the potentialities and limitations of health information systems were performed. The potential of the Health Information System and its underutilization by stakeholders and researchers have been a barrier in diagnosing and reporting ZIKV infection and its complications. The ZIKV outbreak is still a challenge for health practice and the Brazilian Health Information System.

Effects of truck traffic on crash injury severity on rural highways in Wyoming using Bayesian binary logit models.

PubMed

Ahmed, Mohamed M; Franke, Rebecca; Ksaibati, Khaled; Shinstine, Debbie S

2018-08-01

Roadway safety is an integral part of a functioning infrastructure. A major use of the highway system is the transport of goods. The United States has experienced constant growth in the amount of freight transported by truck in the last few years. Wyoming is experiencing a large increase in truck traffic on its local and county roads due to an increase in oil and gas production. This study explores the involvement of heavy trucks in crashes and their significance as a predictor of crash severity and addresses the effect that large truck traffic is having on the safety of roadways for various road classifications. Studies have been done on the factors involved in and the causation of heavy truck crashes, but none address the causation and effect of roadway classifications on truck crashes. Binary Logit Models (BLM) with Bayesian inferences were utilized to classify heavy truck involvement in severe and non-severe crashes using ten years (2002-2011) of historical crash data in the State of Wyoming. From the final main effects model, various interactions proved to be significant in predicting the severity of crashes and varied depending on the roadway classification. The results indicated the odds of a severe crash increase to 2.3 and 4.5 times when a heavy truck is involved on state and interstate highways respectively. The severity of crashes is significantly increased when road conditions were not clear, icy, and during snowy weather conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Classification of Newborn Ear Malformations and their Treatment with the EarWell Infant Ear Correction System.

PubMed

Daniali, Lily N; Rezzadeh, Kameron; Shell, Cheryl; Trovato, Matthew; Ha, Richard; Byrd, H Steve

2017-03-01

A single practice's treatment protocol and outcomes following molding therapy on newborn ear deformations and malformations with the EarWell Infant Ear Correction System were reviewed. A classification system for grading the severity of constricted ear malformations was created on the basis of anatomical findings. A retrospective chart/photograph review of a consecutive series of infants treated with the EarWell System from 2011 to 2014 was undertaken. The infants were placed in either deformation or malformation groups. Three classes of malformation were identified. Data regarding treatment induction, duration of treatment, and quality of outcome were collected for all study patients. One hundred seventy-five infant ear malformations and 303 infant ear deformities were treated with the EarWell System. The average age at initiation of treatment was 12 days; the mean duration of treatment was 37 days. An average of six office visits was required. Treated malformations included constricted ears [172 ears (98 percent)] and cryptotia [three ears (2 percent)]. Cup ear (34 ears) was considered a constricted malformation, in contrast to the prominent ear deformity. Constricted ears were assigned to one of three classes, with each subsequent class indicating increasing severity: class I, 77 ears (45 percent); class II, 81 ears (47 percent); and class III, 14 ears (8 percent). Molding therapy with the EarWell System reduced the severity by an average of 1.2 points (p < 0.01). Complications included minor superficial excoriations and abrasions. The EarWell System was shown to be effective in eliminating or reducing the need for surgery in all but the most severe malformations. Therapeutic, IV.

The Society for Vascular Surgery Lower Extremity Threatened Limb Classification System: risk stratification based on wound, ischemia, and foot infection (WIfI).

PubMed

Mills, Joseph L; Conte, Michael S; Armstrong, David G; Pomposelli, Frank B; Schanzer, Andres; Sidawy, Anton N; Andros, George

2014-01-01

Critical limb ischemia, first defined in 1982, was intended to delineate a subgroup of patients with a threatened lower extremity primarily because of chronic ischemia. It was the intent of the original authors that patients with diabetes be excluded or analyzed separately. The Fontaine and Rutherford Systems have been used to classify risk of amputation and likelihood of benefit from revascularization by subcategorizing patients into two groups: ischemic rest pain and tissue loss. Due to demographic shifts over the last 40 years, especially a dramatic rise in the incidence of diabetes mellitus and rapidly expanding techniques of revascularization, it has become increasingly difficult to perform meaningful outcomes analysis for patients with threatened limbs using these existing classification systems. Particularly in patients with diabetes, limb threat is part of a broad disease spectrum. Perfusion is only one determinant of outcome; wound extent and the presence and severity of infection also greatly impact the threat to a limb. Therefore, the Society for Vascular Surgery Lower Extremity Guidelines Committee undertook the task of creating a new classification of the threatened lower extremity that reflects these important considerations. We term this new framework, the Society for Vascular Surgery Lower Extremity Threatened Limb Classification System. Risk stratification is based on three major factors that impact amputation risk and clinical management: Wound, Ischemia, and foot Infection (WIfI). The implementation of this classification system is intended to permit more meaningful analysis of outcomes for various forms of therapy in this challenging, but heterogeneous population. Copyright © 2014 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Using a Discrete-Choice Experiment Involving Cost to Value a Classification System Measuring the Quality-of-Life Impact of Self-Management for Diabetes.

PubMed

Rowen, Donna; Stevens, Katherine; Labeit, Alexander; Elliott, Jackie; Mulhern, Brendan; Carlton, Jill; Basarir, Hasan; Ratcliffe, Julie; Brazier, John

2018-01-01

To describe the use of a novel approach in health valuation of a discrete-choice experiment (DCE) including a cost attribute to value a recently developed classification system for measuring the quality-of-life impact (both health and treatment experience) of self-management for diabetes. A large online survey was conducted using DCE with cost on UK respondents from the general population (n = 1497) and individuals with diabetes (n = 405). The data were modeled using a conditional logit model with robust standard errors. The marginal rate of substitution was used to generate willingness-to-pay (WTP) estimates for every state defined by the classification system. Robustness of results was assessed by including interaction effects for household income. There were some logical inconsistencies and insignificant coefficients for the milder levels of some attributes. There were some differences in the rank ordering of different attributes for the general population and diabetic patients. The WTP to avoid the most severe state was £1118.53 per month for the general population and £2356.02 per month for the diabetic patient population. The results were largely robust. Health and self-management can be valued in a single classification system using DCE with cost. The marginal rate of substitution for key attributes can be used to inform cost-benefit analysis of self-management interventions in diabetes using results from clinical studies in which this new classification system has been applied. The method shows promise, but found large WTP estimates exceeding the cost levels used in the survey. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

UAS Detection Classification and Neutralization: Market Survey 2015

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

Birch, Gabriel Carisle; Griffin, John Clark; Erdman, Matthew Kelly

The purpose of this document is to briefly frame the challenges of detecting low, slow, and small (LSS) unmanned aerial systems (UAS). The conclusion drawn from internal discussions and external reports is the following; detection of LSS UAS is a challenging problem that can- not be achieved with a single detection modality for all potential targets. Classification of LSS UAS, especially classification in the presence of background clutter (e.g., urban environment) or other non-threating targets (e.g., birds), is under-explored. Though information of avail- able technologies is sparse, many of the existing options for UAS detection appear to be in theirmore » infancy (when compared to more established ground-based air defense systems for larger and/or faster threats). Companies currently providing or developing technologies to combat the UAS safety and security problem are certainly worth investigating, however, no company has provided the statistical evidence necessary to support robust detection, identification, and/or neutralization of LSS UAS targets. The results of a market survey are included that highlights potential commercial entities that could contribute some technology that assists in the detection, classification, and neutral- ization of a LSS UAS. This survey found no clear and obvious commercial solution, though recommendations are given for further investigation of several potential systems.« less

A semi-automatic traffic sign detection, classification, and positioning system

NASA Astrophysics Data System (ADS)

Creusen, I. M.; Hazelhoff, L.; de With, P. H. N.

2012-01-01

The availability of large-scale databases containing street-level panoramic images offers the possibility to perform semi-automatic surveying of real-world objects such as traffic signs. These inventories can be performed significantly more efficiently than using conventional methods. Governmental agencies are interested in these inventories for maintenance and safety reasons. This paper introduces a complete semi-automatic traffic sign inventory system. The system consists of several components. First, a detection algorithm locates the 2D position of the traffic signs in the panoramic images. Second, a classification algorithm is used to identify the traffic sign. Third, the 3D position of the traffic sign is calculated using the GPS position of the photographs. Finally, the results are listed in a table for quick inspection and are also visualized in a web browser.

Toward an Attention-Based Diagnostic Tool for Patients With Locked-in Syndrome.

PubMed

Lesenfants, Damien; Habbal, Dina; Chatelle, Camille; Soddu, Andrea; Laureys, Steven; Noirhomme, Quentin

2018-03-01

Electroencephalography (EEG) has been proposed as a supplemental tool for reducing clinical misdiagnosis in severely brain-injured populations helping to distinguish conscious from unconscious patients. We studied the use of spectral entropy as a measure of focal attention in order to develop a motor-independent, portable, and objective diagnostic tool for patients with locked-in syndrome (LIS), answering the issues of accuracy and training requirement. Data from 20 healthy volunteers, 6 LIS patients, and 10 patients with a vegetative state/unresponsive wakefulness syndrome (VS/UWS) were included. Spectral entropy was computed during a gaze-independent 2-class (attention vs rest) paradigm, and compared with EEG rhythms (delta, theta, alpha, and beta) classification. Spectral entropy classification during the attention-rest paradigm showed 93% and 91% accuracy in healthy volunteers and LIS patients respectively. VS/UWS patients were at chance level. EEG rhythms classification reached a lower accuracy than spectral entropy. Resting-state EEG spectral entropy could not distinguish individual VS/UWS patients from LIS patients. The present study provides evidence that an EEG-based measure of attention could detect command-following in patients with severe motor disabilities. The entropy system could detect a response to command in all healthy subjects and LIS patients, while none of the VS/UWS patients showed a response to command using this system.

Conceptual-driven classification for coding advise in health insurance reimbursement.

PubMed

Li, Sheng-Tun; Chen, Chih-Chuan; Huang, Fernando

2011-01-01

With the non-stop increases in medical treatment fees, the economic survival of a hospital in Taiwan relies on the reimbursements received from the Bureau of National Health Insurance, which in turn depend on the accuracy and completeness of the content of the discharge summaries as well as the correctness of their International Classification of Diseases (ICD) codes. The purpose of this research is to enforce the entire disease classification framework by supporting disease classification specialists in the coding process. This study developed an ICD code advisory system (ICD-AS) that performed knowledge discovery from discharge summaries and suggested ICD codes. Natural language processing and information retrieval techniques based on Zipf's Law were applied to process the content of discharge summaries, and fuzzy formal concept analysis was used to analyze and represent the relationships between the medical terms identified by MeSH. In addition, a certainty factor used as reference during the coding process was calculated to account for uncertainty and strengthen the credibility of the outcome. Two sets of 360 and 2579 textual discharge summaries of patients suffering from cerebrovascular disease was processed to build up ICD-AS and to evaluate the prediction performance. A number of experiments were conducted to investigate the impact of system parameters on accuracy and compare the proposed model to traditional classification techniques including linear-kernel support vector machines. The comparison results showed that the proposed system achieves the better overall performance in terms of several measures. In addition, some useful implication rules were obtained, which improve comprehension of the field of cerebrovascular disease and give insights to the relationships between relevant medical terms. Our system contributes valuable guidance to disease classification specialists in the process of coding discharge summaries, which consequently brings benefits in aspects of patient, hospital, and healthcare system. Copyright © 2010 Elsevier B.V. All rights reserved.

Casemix reimbursement: a Singapore Children's Hospital perspective.

PubMed

Yoong, S L

2001-07-01

Casemix reimbursement was introduced to Singapore in October 1999 using the Australian National Diagnosis Related Groups Version 3.1 (AN-DRGs 3.1). The possible impact of this classification system on a Singapore Children's Hospital is discussed. Data on paediatric patients in KK Women's and Children's Hospital (KKH) were drawn from the inhouse Datamart warehouse system, and reviewed with regards to volume of patients, length of stay and charges. Several high cost categories were selected for a more in-depth review and discussed. The classification system and reimbursement method did not take into account the higher cost of treating children, thus penalising the Children's Hospital. The wide variety of cases treated also gave rise to difficulty in obtaining appropriate reimbursement. The lack of severity of illness measures was a drawback in the Diagnosis Related Group (DRG) for ventilated patients. The lack of outcome measures gave rise to potentially inequitable reimbursement in some high cost neonatal DRGs. While Casemix is an improvement over previous methods of providing Government funding in Singapore, particular aspects need to be reviewed, and reimbursement criteria refined to ensure equitable funding to Children's Hospital.

A new precipitation and drought climatology based on weather patterns.

PubMed

Richardson, Douglas; Fowler, Hayley J; Kilsby, Christopher G; Neal, Robert

2018-02-01

Weather-pattern, or weather-type, classifications are a valuable tool in many applications as they characterize the broad-scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather-pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI-based drought months. The new weather-pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation-based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra-pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification-based analyses in the UK.

Applying the WHO conceptual framework for the International Classification for Patient Safety to a surgical population

PubMed Central

McElroy, L. M.; Woods, D. M.; Yanes, A. F.; Skaro, A. I.; Daud, A.; Curtis, T.; Wymore, E.; Holl, J. L.; Abecassis, M. M.; Ladner, D. P.

2016-01-01

Objective Efforts to improve patient safety are challenged by the lack of universally agreed upon terms. The International Classification for Patient Safety (ICPS) was developed by the World Health Organization for this purpose. This study aimed to test the applicability of the ICPS to a surgical population. Design A web-based safety debriefing was sent to clinicians involved in surgical care of abdominal organ transplant patients. A multidisciplinary team of patient safety experts, surgeons and researchers used the data to develop a system of classification based on the ICPS. Disagreements were reconciled via consensus, and a codebook was developed for future use by researchers. Results A total of 320 debriefing responses were used for the initial review and codebook development. In total, the 320 debriefing responses contained 227 patient safety incidents (range: 0–7 per debriefing) and 156 contributing factors/hazards (0–5 per response). The most common severity classification was ‘reportable circumstance,’ followed by ‘near miss.’ The most common incident types were ‘resources/organizational management,’ followed by ‘medical device/equipment.’ Several aspects of surgical care were encompassed by more than one classification, including operating room scheduling, delays in care, trainee-related incidents, interruptions and handoffs. Conclusions This study demonstrates that a framework for patient safety can be applied to facilitate the organization and analysis of surgical safety data. Several unique aspects of surgical care require consideration, and by using a standardized framework for describing concepts, research findings can be compared and disseminated across surgical specialties. The codebook is intended for use as a framework for other specialties and institutions. PMID:26803539

2008 International Conference on Ectodermal Dysplasias Classification Conference Report

PubMed Central

Salinas, Carlos F.; Jorgenson, Ronald J.; Wright, J. Timothy; DiGiovanna, John J.; Fete, Mary D.

2009-01-01

There are many ways to classify ectodermal dysplasia syndromes. Clinicians in practice use a list of syndromes from which to choose a potential diagnosis, paging through a volume, such as Freire-Maia and Pinheiro's corpus, matching their patient's findings to listed syndromes. Medical researchers may want a list of syndromes that share one (monothetic system) or several (polythetic system) traits in order to focus research on a narrowly defined group. Special interest groups may want a list from which they can choose constituencies, and insurance companies and government agencies may want a list to determine for whom to provide (or deny) health care coverage. Furthermore, various molecular biologists are now promoting classification systems based on gene mutation (e.g. TP63 associated syndromes) or common molecular pathways. The challenge will be to balance comprehensiveness within the classification with usability and accessibility so that the benefits truly serve the needs of researchers, health care providers and ultimately the individuals and families directly affected by ectodermal dysplasias. It is also recognized that a new classification approach is an ongoing process and will require periodical reviews or updates. Whatever scheme is developed, however, will have far-reaching application for other groups of disorders for which classification is complicated by the number of interested parties and advances in diagnostic acumen. Consensus among interested parties is necessary for optimizing communication among the diverse groups whether it be for equitable distribution of funds, correctness of diagnosis and treatment, or focusing research efforts. PMID:19681152

Utility of CT classifications to predict unfavorable outcomes in children with acute pancreatitis.

PubMed

Izquierdo, Yojhan E; Fonseca, Eileen V; Moreno, Luz-Ángela; Montoya, Rubén D; Guerrero Lozano, Rafael

2018-02-21

Computed tomography (CT) is useful for the diagnosis of local complications in children with acute pancreatitis but its role as a prognostic tool remains controversial. To establish the correlation between the CT Severity Index and the Revised Atlanta Classification regarding unfavorable outcomes such as severe acute pancreatitis and need for Pediatric Special Care Unit attention in children with acute pancreatitis. We conducted a retrospective and concordance cohort study in which we obtained abdominal CT scans from 30 patients ages 0 to 18 years with acute pancreatitis. Two pediatric radiologists interpreted the results using the CT Severity Index and the Revised Atlanta Classification. The kappa coefficient was determined for each scale. The association among severe acute pancreatitis, need for admission to the Pediatric Special Care Unit and CT systems were established using chi-square or Mann-Whitney U tests. The best CT Severity Index value to predict the need for admission to the Pediatric Special Care Unit was estimated through a receiver operating characteristic (ROC) curve. Mean CT Severity Index was 5.1±2.8 (mean ± standard deviation on a scale of 0 to 10) for the severe acute pancreatitis group vs. 3.8±2.7 for the mild acute pancreatitis group (P=0.230). The CT Severity Index for the children who were not hospitalized at the Pediatric Special Care Unit was 2.2±2.2 vs. 5.6±2.4 for the group hospitalized at the Pediatric Special Care Unit (P=0.001). Only parenchymal necrosis >30% was associated with severe acute pancreatitis (P=0.021). A CT Severity Index ≥3 has a sensitivity of 89% and specificity of 72% to predict need for admission to the Pediatric Special Care Unit. None of the Revised Atlanta Classification categories was associated with severe acute pancreatitis or admission to the Pediatric Special Care Unit. A CT Severity Index ≥3 in children with acute pancreatitis who require CT assessment based on clinical criteria is associated with the need for admission to the Pediatric Special Care Unit. We found that pancreatic necrosis greater than 30% is the only tomographic parameter related to severe acute pancreatitis. New studies with a greater sample size are necessary to confirm this result.

Creating a Canonical Scientific and Technical Information Classification System for NCSTRL+

NASA Technical Reports Server (NTRS)

Tiffany, Melissa E.; Nelson, Michael L.

1998-01-01

The purpose of this paper is to describe the new subject classification system for the NCSTRL+ project. NCSTRL+ is a canonical digital library (DL) based on the Networked Computer Science Technical Report Library (NCSTRL). The current NCSTRL+ classification system uses the NASA Scientific and Technical (STI) subject classifications, which has a bias towards the aerospace, aeronautics, and engineering disciplines. Examination of other scientific and technical information classification systems showed similar discipline-centric weaknesses. Traditional, library-oriented classification systems represented all disciplines, but were too generalized to serve the needs of a scientific and technically oriented digital library. Lack of a suitable existing classification system led to the creation of a lightweight, balanced, general classification system that allows the mapping of more specialized classification schemes into the new framework. We have developed the following classification system to give equal weight to all STI disciplines, while being compact and lightweight.

Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

NASA Astrophysics Data System (ADS)

Kachach, Redouane; Cañas, José María

2016-05-01

Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

Classification of diabetic foot ulcers.

PubMed

Game, Frances

2016-01-01

It is known that the relative importance of factors involved in the development of diabetic foot problems can vary in both their presence and severity between patients and lesions. This may be one of the reasons why outcomes seem to vary centre to centre and why some treatments may seem more effective in some people than others. There is a need therefore to classify and describe lesions of the foot in patients with diabetes in a manner that is agreed across all communities but is simple to use in clinical practice. No single system is currently in widespread use, although a number have been published. Not all are well validated outside the system from which they were derived, and it has not always been made clear the clinical purposes to which such classifications should be put to use, whether that be for research, clinical description in routine clinical care or audit. Here the currently published classification systems, their validation in clinical practice, whether they were designed for research, audit or clinical care, and the strengths and weaknesses of each are explored. Copyright © 2016 John Wiley & Sons, Ltd.

Ozone-induced changes in natural organic matter (NOM) structure

USGS Publications Warehouse

Westerhoff, P.; Debroux, J.; Aiken, G.; Amy, G.

1999-01-01

Hydrophobic organic acids (combined humic and fulvic acids), obtained from an Antarctic Lake with predominantly microbially derived organic carbon sources and two US fiver systems with terrestrial organic carbon sources, were ozonated. Several analyses, including 13C-NMR, UV absorbance, fluorescence, hydrophobic/transphilic classification, and potentiometric titrations, were performed before and after ozonation. Ozonation reduced aromatic carbon content, selectively reducing phenolic carbon content. Ozonation of the samples resulted in increased aliphatic, carboxyl, plus acetal and ketal anomeric carbon content and shifted towards less hydrophobic compounds.Hydrophobic organic acids (combined humic and fulvic acids), obtained from an Antarctic Lake with predominantly microbially derived organic carbon sources and two US river systems with terrestrial organic carbon sources, were ozonated. Several analyses, including 13C-NMR, UV absorbance, fluorescence, hydrophobic/transphilic classification, and potentiometric titrations, were performed before and after ozonation. Ozonation reduced aromatic carbon content, selectively reducing phenolic carbon content. Ozonation of the samples resulted in increased aliphatic, carboxyl, plus acetal and ketal anomeric carbon content and shifted towards less hydrophobic compounds.

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Jong, Jen-Yi

1986-01-01

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Preliminary Study of Bioinformatics Patents and Their Classifications Registered in the KIPRIS Database.

PubMed

Park, Hyun-Seok

2012-12-01

Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

Fractures of the Tibial Plateau Involve Similar Energies as the Tibial Pilon but Greater Articular Surface Involvement

PubMed Central

Dibbern, Kevin; Kempton, Laurence B.; Higgins, Thomas F.; Morshed, Saam; McKinley, Todd O.; Marsh, J. Lawrence; Anderson, Donald D.

2016-01-01

Patients with tibial pilon fractures have a higher incidence of post-traumatic osteoarthritis than those with fractures of the tibial plateau. This may indicate that pilon fractures present a greater mechanical insult to the joint than do plateau fractures. We tested the hypothesis that fracture energy and articular fracture edge length, two independent indicators of severity, are higher in pilon than plateau fractures. We also evaluated if clinical fracture classification systems accurately reflect severity. Seventy-five tibial plateau fractures and fifty-two tibial pilon fractures from a multi-institutional study were selected to span the spectrum of severity. Fracture severity measures were calculated using objective CT-based image analysis methods. The ranges of fracture energies measured for tibial plateau and pilon fractures were 3.2 to 33.2 Joules (J) and 3.6 to 32.2 J, respectively, and articular fracture edge lengths were 68.0 to 493.0 mm and 56.1 to 288.6 mm, respectively. There were no differences in the fracture energies between the two fracture types, but plateau fractures had greater articular fracture edge lengths (p<0.001). The clinical fracture classifications generally reflected severity, but there was substantial overlap of fracture severity measures between different classes. Clinical Significance Similar fracture energies with different degrees of articular surface involvement suggest a possible explanation for dissimilar rates of post-traumatic osteoarthritis for fractures of the tibial plateau compared to the tibial pilon. The substantial overlap of severity measures between different fracture classes may well have confounded prior clinical studies relying on fracture classification as a surrogate for severity. PMID:27381653

Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization.

PubMed

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4.

Osteoarthritis Classification Using Self Organizing Map Based on Gabor Kernel and Contrast-Limited Adaptive Histogram Equalization

PubMed Central

Anifah, Lilik; Purnama, I Ketut Eddy; Hariadi, Mochamad; Purnomo, Mauridhi Hery

2013-01-01

Localization is the first step in osteoarthritis (OA) classification. Manual classification, however, is time-consuming, tedious, and expensive. The proposed system is designed as decision support system for medical doctors to classify the severity of knee OA. A method has been proposed here to localize a joint space area for OA and then classify it in 4 steps to classify OA into KL-Grade 0, KL-Grade 1, KL-Grade 2, KL-Grade 3 and KL-Grade 4, which are preprocessing, segmentation, feature extraction, and classification. In this proposed system, right and left knee detection was performed by employing the Contrast-Limited Adaptive Histogram Equalization (CLAHE) and the template matching. The Gabor kernel, row sum graph and moment methods were used to localize the junction space area of knee. CLAHE is used for preprocessing step, i.e.to normalize the varied intensities. The segmentation process was conducted using the Gabor kernel, template matching, row sum graph and gray level center of mass method. Here GLCM (contrast, correlation, energy, and homogeinity) features were employed as training data. Overall, 50 data were evaluated for training and 258 data for testing. Experimental results showed the best performance by using gabor kernel with parameters α=8, θ=0, Ψ=[0 π/2], γ=0,8, N=4 and with number of iterations being 5000, momentum value 0.5 and α0=0.6 for the classification process. The run gave classification accuracy rate of 93.8% for KL-Grade 0, 70% for KL-Grade 1, 4% for KL-Grade 2, 10% for KL-Grade 3 and 88.9% for KL-Grade 4. PMID:23525188

Perceptual-motor skill learning in Gilles de la Tourette syndrome. Evidence for multiple procedural learning and memory systems.

PubMed

Marsh, Rachel; Alexander, Gerianne M; Packard, Mark G; Zhu, Hongtu; Peterson, Bradley S

2005-01-01

Procedural learning and memory systems likely comprise several skills that are differentially affected by various illnesses of the central nervous system, suggesting their relative functional independence and reliance on differing neural circuits. Gilles de la Tourette syndrome (GTS) is a movement disorder that involves disturbances in the structure and function of the striatum and related circuitry. Recent studies suggest that patients with GTS are impaired in performance of a probabilistic classification task that putatively involves the acquisition of stimulus-response (S-R)-based habits. Assessing the learning of perceptual-motor skills and probabilistic classification in the same samples of GTS and healthy control subjects may help to determine whether these various forms of procedural (habit) learning rely on the same or differing neuroanatomical substrates and whether those substrates are differentially affected in persons with GTS. Therefore, we assessed perceptual-motor skill learning using the pursuit-rotor and mirror tracing tasks in 50 patients with GTS and 55 control subjects who had previously been compared at learning a task of probabilistic classifications. The GTS subjects did not differ from the control subjects in performance of either the pursuit rotor or mirror-tracing tasks, although they were significantly impaired in the acquisition of a probabilistic classification task. In addition, learning on the perceptual-motor tasks was not correlated with habit learning on the classification task in either the GTS or healthy control subjects. These findings suggest that the differing forms of procedural learning are dissociable both functionally and neuroanatomically. The specific deficits in the probabilistic classification form of habit learning in persons with GTS are likely to be a consequence of disturbances in specific corticostriatal circuits, but not the same circuits that subserve the perceptual-motor form of habit learning.

Integrating remote sensing and terrain data in forest fire modeling

NASA Astrophysics Data System (ADS)

Medler, Michael Johns

Forest fire policies are changing. Managers now face conflicting imperatives to re-establish pre-suppression fire regimes, while simultaneously preventing resource destruction. They must, therefore, understand the spatial patterns of fires. Geographers can facilitate this understanding by developing new techniques for mapping fire behavior. This dissertation develops such techniques for mapping recent fires and using these maps to calibrate models of potential fire hazards. In so doing, it features techniques that strive to address the inherent complexity of modeling the combinations of variables found in most ecological systems. Image processing techniques were used to stratify the elements of terrain, slope, elevation, and aspect. These stratification images were used to assure sample placement considered the role of terrain in fire behavior. Examination of multiple stratification images indicated samples were placed representatively across a controlled range of scales. The incorporation of terrain data also improved preliminary fire hazard classification accuracy by 40%, compared with remotely sensed data alone. A Kauth-Thomas transformation (KT) of pre-fire and post-fire Thematic Mapper (TM) remotely sensed data produced brightness, greenness, and wetness images. Image subtraction indicated fire induced change in brightness, greenness, and wetness. Field data guided a fuzzy classification of these change images. Because fuzzy classification can characterize a continuum of a phenomena where discrete classification may produce artificial borders, fuzzy classification was found to offer a range of fire severity information unavailable with discrete classification. These mapped fire patterns were used to calibrate a model of fire hazards for the entire mountain range. Pre-fire TM, and a digital elevation model produced a set of co-registered images. Training statistics were developed from 30 polygons associated with the previously mapped fire severity. Fuzzy classifications of potential burn patterns were produced from these images. Observed field data values were displayed over the hazard imagery to indicate the effectiveness of the model. Areas that burned without suppression during maximum fire severity are predicted best. Areas with widely spaced trees and grassy understory appear to be misrepresented, perhaps as a consequence of inaccuracies in the initial fire mapping.

A SVM framework for fault detection of the braking system in a high speed train

NASA Astrophysics Data System (ADS)

Liu, Jie; Li, Yan-Fu; Zio, Enrico

2017-03-01

In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

Tone classification of syllable-segmented Thai speech based on multilayer perception

NASA Astrophysics Data System (ADS)

Satravaha, Nuttavudh; Klinkhachorn, Powsiri; Lass, Norman

2002-05-01

Thai is a monosyllabic tonal language that uses tone to convey lexical information about the meaning of a syllable. Thus to completely recognize a spoken Thai syllable, a speech recognition system not only has to recognize a base syllable but also must correctly identify a tone. Hence, tone classification of Thai speech is an essential part of a Thai speech recognition system. Thai has five distinctive tones (``mid,'' ``low,'' ``falling,'' ``high,'' and ``rising'') and each tone is represented by a single fundamental frequency (F0) pattern. However, several factors, including tonal coarticulation, stress, intonation, and speaker variability, affect the F0 pattern of a syllable in continuous Thai speech. In this study, an efficient method for tone classification of syllable-segmented Thai speech, which incorporates the effects of tonal coarticulation, stress, and intonation, as well as a method to perform automatic syllable segmentation, were developed. Acoustic parameters were used as the main discriminating parameters. The F0 contour of a segmented syllable was normalized by using a z-score transformation before being presented to a tone classifier. The proposed system was evaluated on 920 test utterances spoken by 8 speakers. A recognition rate of 91.36% was achieved by the proposed system.

Computerized Classification of Pneumoconiosis on Digital Chest Radiography Artificial Neural Network with Three Stages.

PubMed

Okumura, Eiichiro; Kawashita, Ikuo; Ishida, Takayuki

2017-08-01

It is difficult for radiologists to classify pneumoconiosis from category 0 to category 3 on chest radiographs. Therefore, we have developed a computer-aided diagnosis (CAD) system based on a three-stage artificial neural network (ANN) method for classification based on four texture features. The image database consists of 36 chest radiographs classified as category 0 to category 3. Regions of interest (ROIs) with a matrix size of 32 × 32 were selected from chest radiographs. We obtained a gray-level histogram, histogram of gray-level difference, gray-level run-length matrix (GLRLM) feature image, and gray-level co-occurrence matrix (GLCOM) feature image in each ROI. For ROI-based classification, the first ANN was trained with each texture feature. Next, the second ANN was trained with output patterns obtained from the first ANN. Finally, we obtained a case-based classification for distinguishing among four categories with the third ANN method. We determined the performance of the third ANN by receiver operating characteristic (ROC) analysis. The areas under the ROC curve (AUC) of the highest category (severe pneumoconiosis) case and the lowest category (early pneumoconiosis) case were 0.89 ± 0.09 and 0.84 ± 0.12, respectively. The three-stage ANN with four texture features showed the highest performance for classification among the four categories. Our CAD system would be useful for assisting radiologists in classification of pneumoconiosis from category 0 to category 3.

Inter and intra-observer reliability in assessment of the position of the lateral sesamoid in determining the severity of hallux valgus.

PubMed

Panchani, Sunil; Reading, Jonathan; Mehta, Jaysheel

2016-06-01

The position of the lateral sesamoid on standard dorso-plantar weight bearing radiographs, with respect to the lateral cortex of the first metatarsal, has been shown to correlate well with the degree of the hallux valgus angle. This study aimed to assess the inter- and intra-observer error of this new classification system. Five orthopaedic consultants and five trainee orthopaedic surgeons were recruited to assess and document the degree of displacement of the lateral sesamoid on 144 weight-bearing dorso-plantar radiographs on two separate occasions. The severity of hallux valgus was defined as normal (0%), mild (≤50%), moderate (51-≤99%) or severe (≥100%) depending on the percentage displacement of the lateral sesamoid body from the lateral cortical border of the first metatarsal. Consultant intra-observer variability showed good agreement between repeated assessment of the radiographs (mean Kappa=0.75). Intra-observer variability for trainee orthopaedic surgeons also showed good agreement with a mean Kappa=0.73. Intraclass correlations for consultants and trainee surgeons was also high. The new classification system of assessing the severity of hallux valgus shows high inter- and intra-observer variability with good agreement and reproducibility between surgeons of consultant and trainee grades. Copyright © 2015 Elsevier Ltd. All rights reserved.

A methodology for space-time classification of groundwater quality.

PubMed

Passarella, G; Caputo, M C

2006-04-01

Safeguarding groundwater from civil, agricultural and industrial contamination is matter of great interest in water resource management. During recent years, much legislation has been produced stating the importance of groundwater as a source for drinking water supplies, underlining its vulnerability and defining the required quality standards. Thus, schematic tools, able to characterise the quality and quantity of groundwater systems, are of very great interest in any territorial planning and/or water resource management activity. This paper proposes a groundwater quality classification method which has been applied to a real aquifer, starting from several studies published by the Italian National Hydrogeologic Catastrophe Defence Group (GNDCI). The methodology is based on the concentration values of several parameters used as indexes of the natural hydro-chemical water condition and of potential man-induced modifications of groundwater quality. The resulting maps, although representative of the quality, do not include any information on its evolution in time. In this paper, this "stationary" classification method has been improved by crossing the quality classes with three indexes of temporal behaviour during recent years. It was then applied to data from monitoring campaigns, performed in spring and autumn, from 1990 to 1996, in the plain of Modena aquifer (central Italy). The results are reported in the form of space-time classification table and maps.

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

Pediatric severe sepsis: current trends and outcomes from the Pediatric Health Information Systems database.

PubMed

Ruth, Amanda; McCracken, Courtney E; Fortenberry, James D; Hall, Matthew; Simon, Harold K; Hebbar, Kiran B

2014-11-01

To 1) describe the characteristics and outcomes over time of PICU patients with severe sepsis within the dedicated U.S. children's hospitals, 2) identify patient subgroups at risk for mortality from pediatric severe sepsis, and 3) describe overall pediatric severe sepsis resource utilization. Retrospective review of a prospectively collected multi-institutional children's hospital database. PICUs in 43 U.S. children's hospitals. PICU patients from birth to younger than 19 years were identified with severe sepsis by modified Angus criteria and International Classification of Diseases, 9th Revision, codes for severe sepsis and septic shock. None. Data from the Pediatric Health Information System database collected by the Children's Hospital Association from 2004 to 2012. Pediatric severe sepsis was defined by 1) International Classification of Diseases, 9th Revision, codes reflecting severe sepsis and septic shock and 2) International Classification of Diseases, 9th Revision, codes of infection and organ dysfunction as defined by modified Angus criteria. From 2004 to 2012, 636,842 patients were identified from 43 hospitals. Pediatric severe sepsis prevalence was 7.7% (49,153) with an associated mortality rate of 14.4%. Age less than 1 year (vs age 10 to < 19) (odds ratio, 1.4), underlying cardiovascular condition (odds ratio, 1.4) and multiple organ dysfunction, conferred higher odds of mortality. Resource burden was significant with median hospital length of stay of 17 days (interquartile range, 8-36 d) and PICU length of stay of 7 days (interquartile range, 2-17 d), with median cost/day of $4,516 and median total hospitalization cost of $77,446. There was a significant increase in the severe sepsis prevalence rate from 6.2% to 7.7% from 2004 to 2012 (p < 0.001) and a significant decrease in mortality from 18.9% to 12.0% (p < 0.001). Center mortality was negatively correlated with prevalence (rs = -0.48) and volume (rs = -0.39) and positively correlated with cost (rs = 0.36). In this largest reported pediatric severe sepsis cohort to date, prevalence increased from 2004 to 2012 while associated mortality decreased. Age, cardiovascular comorbidity, and organ dysfunction were significant prognostic factors. Pediatric severe sepsis remains an important cause for PICU admission and mortality and leads to a substantial burden in healthcare costs. Individual center's prevalence and volume are associated with improved outcomes.

Evaluation of host and viral factors associated with severe dengue based on the 2009 WHO classification.

PubMed

Pozo-Aguilar, Jorge O; Monroy-Martínez, Verónica; Díaz, Daniel; Barrios-Palacios, Jacqueline; Ramos, Celso; Ulloa-García, Armando; García-Pillado, Janet; Ruiz-Ordaz, Blanca H

2014-12-11

Dengue fever (DF) is the most prevalent arthropod-borne viral disease affecting humans. The World Health Organization (WHO) proposed a revised classification in 2009 to enable the more effective identification of cases of severe dengue (SD). This was designed primarily as a clinical tool, but it also enables cases of SD to be differentiated into three specific subcategories (severe vascular leakage, severe bleeding, and severe organ dysfunction). However, no study has addressed whether this classification has advantage in estimating factors associated with the progression of disease severity or dengue pathogenesis. We evaluate in a dengue outbreak associated risk factors that could contribute to the development of SD according to the 2009 WHO classification. A prospective cross-sectional study was performed during an epidemic of dengue in 2009 in Chiapas, Mexico. Data were analyzed for host and viral factors associated with dengue cases, using the 1997 and 2009 WHO classifications. The cost-benefit ratio (CBR) was also estimated. The sensitivity in the 1997 WHO classification for determining SD was 75%, and the specificity was 97.7%. For the 2009 scheme, these were 100% and 81.1%, respectively. The 2009 classification showed a higher benefit (537%) with a lower cost (10.2%) than the 1997 WHO scheme. A secondary antibody response was strongly associated with SD. Early viral load was higher in cases of SD than in those with DF. Logistic regression analysis identified predictive SD factors (secondary infection, disease phase, viral load) within the 2009 classification. However, within the 1997 scheme it was not possible to differentiate risk factors between DF and dengue hemorrhagic fever or dengue shock syndrome. The critical clinical stage for determining SD progression was the transition from fever to defervescence in which plasma leakage can occur. The clinical phenotype of SD is influenced by the host (secondary response) and viral factors (viral load). The 2009 WHO classification showed greater sensitivity to identify SD in real time. Timely identification of SD enables accurate early decisions, allowing proper management of health resources for the benefit of patients at risk for SD. This is possible based on the 2009 WHO classification.

Job titles classified into socioeconomic and occupational groups identify subjects with increased risk for respiratory symptoms independent of occupational exposure to vapour, gas, dust, or fumes.

PubMed

Schyllert, Christian; Andersson, Martin; Hedman, Linnea; Ekström, Magnus; Backman, Helena; Lindberg, Anne; Rönmark, Eva

2018-01-01

Objectives : To evaluate the ability of three different job title classification systems to identify subjects at risk for respiratory symptoms and asthma by also taking the effect of exposure to vapours, gas, dust, and fumes (VGDF) into account. Background : Respiratory symptoms and asthma may be caused by occupational factors. There are different ways to classify occupational exposure. In this study, self-reported occupational exposure to vapours, gas, dust and fumes was used as well as job titles classifed into occupational and socioeconomic Groups according to three different systems. Design: This was a large population-based study of adults aged 30-69 years in Northern Sweden ( n  = 9,992, 50% women). Information on job titles, VGDF-exposure, smoking habits, asthma and respiratory symptoms was collected by a postal survey. Job titles were used for classification into socioeconomic and occupational groups based on three classification systems; Socioeconomic classification (SEI), the Nordic Occupations Classification 1983 (NYK), and the Swedish Standard Classification of Occupations 2012 (SSYK). Associations were analysed by multivariable logistic regression. Results : Occupational exposure to VGDF was a risk factor for all respiratory symptoms and asthma (odds ratios (ORs) 1.3-2.4). Productive cough was associated with the socioeconomic groups of manual workers (ORs 1.5-2.1) and non-manual employees (ORs 1.6-1.9). These groups include occupations such as construction and transportation workers, service workers, nurses, teachers and administration clerks which by the SSYK classification were associated with productive cough (ORs 2.4-3.7). Recurrent wheeze was significantly associated with the SEI group manual workers (ORs 1.5-1.7). After adjustment for also VGDF, productive cough remained significantly associated with the SEI groups manual workers in service and non-manual employees, and the SSYK-occupational groups administration, service, and elementary occupations. Conclusions : In this cross-sectional study, two of the three different classification systems, SSYK and SEI gave similar results and identified groups with increased risk for respiratory symptoms while NYK did not give conclusive results. Furthermore, several associations were independent of exposure to VGDF indicating that also other job-related factors than VGDF are of importance.

Standoff detection of bioaerosols over wide area using a newly developed sensor combining a cloud mapper and a spectrometric LIF lidar

NASA Astrophysics Data System (ADS)

Buteau, Sylvie; Simard, Jean-Robert; Roy, Gilles; Lahaie, Pierre; Nadeau, Denis; Mathieu, Pierre

2013-10-01

A standoff sensor called BioSense was developed to demonstrate the capacity to map, track and classify bioaerosol clouds from a distant range and over wide area. The concept of the system is based on a two steps dynamic surveillance: 1) cloud detection using an infrared (IR) scanning cloud mapper and 2) cloud classification based on a staring ultraviolet (UV) Laser Induced Fluorescence (LIF) interrogation. The system can be operated either in an automatic surveillance mode or using manual intervention. The automatic surveillance operation includes several steps: mission planning, sensor deployment, background monitoring, surveillance, cloud detection, classification and finally alarm generation based on the classification result. One of the main challenges is the classification step which relies on a spectrally resolved UV LIF signature library. The construction of this library relies currently on in-chamber releases of various materials that are simultaneously characterized with the standoff sensor and referenced with point sensors such as Aerodynamic Particle Sizer® (APS). The system was tested at three different locations in order to evaluate its capacity to operate in diverse types of surroundings and various environmental conditions. The system showed generally good performances even though the troubleshooting of the system was not completed before initiating the Test and Evaluation (T&E) process. The standoff system performances appeared to be highly dependent on the type of challenges, on the climatic conditions and on the period of day. The real-time results combined with the experience acquired during the 2012 T & E allowed to identify future ameliorations and investigation avenues.

Neuromuscular disease classification system

NASA Astrophysics Data System (ADS)

Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

2013-06-01

Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

Track classification within wireless sensor network

NASA Astrophysics Data System (ADS)

Doumerc, Robin; Pannetier, Benjamin; Moras, Julien; Dezert, Jean; Canevet, Loic

2017-05-01

In this paper, we present our study on track classification by taking into account environmental information and target estimated states. The tracker uses several motion model adapted to different target dynamics (pedestrian, ground vehicle and SUAV, i.e. small unmanned aerial vehicle) and works in centralized architecture. The main idea is to explore both: classification given by heterogeneous sensors and classification obtained with our fusion module. The fusion module, presented in his paper, provides a class on each track according to track location, velocity and associated uncertainty. To model the likelihood on each class, a fuzzy approach is used considering constraints on target capability to move in the environment. Then the evidential reasoning approach based on Dempster-Shafer Theory (DST) is used to perform a time integration of this classifier output. The fusion rules are tested and compared on real data obtained with our wireless sensor network.In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of this system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Decision Making in the Management of Extracapsular Fractures of the Proximal Femur - is the Dynamic Hip Screw the Prevailing Gold Standard?

PubMed

Jacob, Joshua; Desai, Ankit; Trompeter, Alex

2017-01-01

Currently, approximately half of all hip fractures are extracapsular, with an incidence as high as 50 in 100,000 in some countries. The common classification systems fail to explain the logistics of fracture classification and whether they all behave in the same manner. The Muller AO classification system is a useful platform to delineate stable and unstable fractures. The Dynamic hip screw (DHS) however, has remained the 'gold standard' implant of choice for application in all extracapsular fractures. The DHS relies on the integrity and strength of the lateral femoral wall as well as the postero-medial fragment. An analysis of several studies indicates significant improvements in design and techniques to ensure a better outcome with intramedullary nails. This article reviews the historical trends that helped to evolve the DHS implant as well as discussing if the surgeon should remain content with this implant. We suggest that the gold standard surgical management of extracapsular fractures can, and should, evolve.

Applying deep neural networks to HEP job classification

NASA Astrophysics Data System (ADS)

Wang, L.; Shi, J.; Yan, X.

2015-12-01

The cluster of IHEP computing center is a middle-sized computing system which provides 10 thousands CPU cores, 5 PB disk storage, and 40 GB/s IO throughput. Its 1000+ users come from a variety of HEP experiments. In such a system, job classification is an indispensable task. Although experienced administrator can classify a HEP job by its IO pattern, it is unpractical to classify millions of jobs manually. We present how to solve this problem with deep neural networks in a supervised learning way. Firstly, we built a training data set of 320K samples by an IO pattern collection agent and a semi-automatic process of sample labelling. Then we implemented and trained DNNs models with Torch. During the process of model training, several meta-parameters was tuned with cross-validations. Test results show that a 5- hidden-layer DNNs model achieves 96% precision on the classification task. By comparison, it outperforms a linear model by 8% precision.

Cutaneous Lupus Erythematosus: Diagnosis and treatment

PubMed Central

Okon, Lauren G.; Werth, Victoria P.

2013-01-01

Cutaneous lupus erythematosus encompasses a wide range of dermatologic manifestations, which may or may not be associated with the development of systemic disease. Cutaneous lupus is divided into several subtypes, including acute cutaneous lupus erythematosus, subacute cutaneous lupus erythematosus, and chronic cutaneous lupus erythematosus. Chronic cutaneous lupus erythematosus includes discoid lupus erythematosus, lupus erythematosus profundus, chilblain cutaneous lupus, and lupus tumidus. Diagnosis of these diseases requires proper classification of the subtype, through a combination of physical exam, laboratory studies, histology, antibody serology, and occasionally direct immunofluorescence, while ensuring to exclude systemic disease. Treatment of cutaneous lupus consists of patient education on proper sun protection along with appropriate topical and systemic agents. Systemic agents are indicated in cases of widespread, scarring, or treatment-refractory disease. In this review, we discuss issues in classification and diagnosis of the various subtypes of CLE, as well as provide an update on therapeutic management. PMID:24238695

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

42 CFR 412.620 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.620 Section 412... Inpatient Rehabilitation Hospitals and Rehabilitation Units § 412.620 Patient classification system. (a) Classification methodology. (1) A patient classification system is used to classify patients in inpatient...

Classification of fecal contamination on leafy greens by hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

A hyperspectral fluorescence imaging system was developed and used to obtain several two-waveband spectral ratios on leafy green vegetables, represented by romaine lettuce and baby spinach in this study. The ratios were analyzed to determine the proper one for detecting bovine fecal contamination on...

Classification of Fecal Contamination on Leafy Greens by Hyperspectral Imaging

USDA-ARS?s Scientific Manuscript database

A hyperspectral fluorescence imaging system was developed and used to obtain several two-waveband spectral ratios on leafy green vegetables, represented by romaine lettuce and baby spinach in this study. The ratios were analyzed to determine the proper one for detecting bovine fecal contamination on...

[Severity classification of chronic obstructive pulmonary disease based on deep learning].

PubMed

Ying, Jun; Yang, Ceyuan; Li, Quanzheng; Xue, Wanguo; Li, Tanshi; Cao, Wenzhe

2017-12-01

In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed

Rocha, José C; Passalia, Felipe; Matos, Felipe D; Maserati, Marc P; Alves, Mayra F; Almeida, Tamie G de; Cardoso, Bruna L; Basso, Andrea C; Nogueira, Marcelo F G

2016-08-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment.

Methods for assessing the quality of mammalian embryos: How far we are from the gold standard?

PubMed Central

Rocha, José C.; Passalia, Felipe; Matos, Felipe D.; Maserati Jr, Marc P.; Alves, Mayra F.; de Almeida, Tamie G.; Cardoso, Bruna L.; Basso, Andrea C.; Nogueira, Marcelo F. G.

2016-01-01

Morphological embryo classification is of great importance for many laboratory techniques, from basic research to the ones applied to assisted reproductive technology. However, the standard classification method for both human and cattle embryos, is based on quality parameters that reflect the overall morphological quality of the embryo in cattle, or the quality of the individual embryonic structures, more relevant in human embryo classification. This assessment method is biased by the subjectivity of the evaluator and even though several guidelines exist to standardize the classification, it is not a method capable of giving reliable and trustworthy results. Latest approaches for the improvement of quality assessment include the use of data from cellular metabolism, a new morphological grading system, development kinetics and cleavage symmetry, embryo cell biopsy followed by pre-implantation genetic diagnosis, zona pellucida birefringence, ion release by the embryo cells and so forth. Nowadays there exists a great need for evaluation methods that are practical and non-invasive while being accurate and objective. A method along these lines would be of great importance to embryo evaluation by embryologists, clinicians and other professionals who work with assisted reproductive technology. Several techniques shows promising results in this sense, one being the use of digital images of the embryo as basis for features extraction and classification by means of artificial intelligence techniques (as genetic algorithms and artificial neural networks). This process has the potential to become an accurate and objective standard for embryo quality assessment. PMID:27584609

Intra- and Interobserver Reliability of Three Classification Systems for Hallux Rigidus.

PubMed

Dillard, Sarita; Schilero, Christina; Chiang, Sharon; Pham, Peter

2018-04-18

There are over ten classification systems currently used in the staging of hallux rigidus. This results in confusion and inconsistency with radiographic interpretation and treatment. The reliability of hallux rigidus classification systems has not yet been tested. The purpose of this study was to evaluate intra- and interobserver reliability using three commonly used classifications for hallux rigidus. Twenty-one plain radiograph sets were presented to ten ACFAS board-certified foot and ankle surgeons. Each physician classified each radiograph based on clinical experience and knowledge according to the Regnauld, Roukis, and Hattrup and Johnson classification systems. The two-way mixed single-measure consistency intraclass correlation was used to calculate intra- and interrater reliability. The intrarater reliability of individual sets for the Roukis and Hattrup and Johnson classification systems was "fair to good" (Roukis, 0.62±0.19; Hattrup and Johnson, 0.62±0.28), whereas the intrarater reliability of individual sets for the Regnauld system bordered between "fair to good" and "poor" (0.43±0.24). The interrater reliability of the mean classification was "excellent" for all three classification systems. Conclusions Reliable and reproducible classification systems are essential for treatment and prognostic implications in hallux rigidus. In our study, Roukis classification system had the best intrarater reliability. Although there are various classification systems for hallux rigidus, our results indicate that all three of these classification systems show reliability and reproducibility.

Effects of gross motor function and manual function levels on performance-based ADL motor skills of children with spastic cerebral palsy.

PubMed

Park, Myoung-Ok

2017-02-01

[Purpose] The purpose of this study was to determine effects of Gross Motor Function Classification System and Manual Ability Classification System levels on performance-based motor skills of children with spastic cerebral palsy. [Subjects and Methods] Twenty-three children with cerebral palsy were included. The Assessment of Motor and Process Skills was used to evaluate performance-based motor skills in daily life. Gross motor function was assessed using Gross Motor Function Classification Systems, and manual function was measured using the Manual Ability Classification System. [Results] Motor skills in daily activities were significantly different on Gross Motor Function Classification System level and Manual Ability Classification System level. According to the results of multiple regression analysis, children categorized as Gross Motor Function Classification System level III scored lower in terms of performance based motor skills than Gross Motor Function Classification System level I children. Also, when analyzed with respect to Manual Ability Classification System level, level II was lower than level I, and level III was lower than level II in terms of performance based motor skills. [Conclusion] The results of this study indicate that performance-based motor skills differ among children categorized based on Gross Motor Function Classification System and Manual Ability Classification System levels of cerebral palsy.

78 FR 18252 - Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

...-AM78 Prevailing Rate Systems; North American Industry Classification System Based Federal Wage System... 2007 North American Industry Classification System (NAICS) codes currently used in Federal Wage System... (OPM) issued a final rule (73 FR 45853) to update the 2002 North American Industry Classification...

Comparison of six fire severity classification methods using Montana and Washington wildland fires

Treesearch

Pamela G. Sikkink

2015-01-01

Fire severity classifications are used in the post-fire environment to describe fire effects, such as soil alteration or fuel consumption, on the forest floor. Most of the developed classifications are limited because they address very specific fire effects or post-burn characteristics in the burned environment. However, because fire effects vary so much among soil,...

Application of the International Classification of Functioning, Disability and Health system to symptoms of the Duchenne and Becker muscular dystrophies.

PubMed

Conway, Kristin M; Ciafaloni, Emma; Matthews, Dennis; Westfield, Chris; James, Kathy; Paramsothy, Pangaja; Romitti, Paul A

2018-07-01

Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive diseases that affect dystrophin production resulting in compromised muscle function across multiple systems. The International Classification of Functioning, Disability and Health provides a systematic classification scheme from which body functions affected by a dystrophinopathy can be identified and used to examine functional health. The infrastructure of the Muscular Dystrophy Surveillance, Tracking, and Research Network was used to identify commonly affected body functions and link selected functions to clinical surveillance data collected through medical record abstraction. Seventy-one (24 second-, 41 third- and 7 fourth-level) body function categories were selected via clinician review and consensus. Of these, 15 of 24 retained second-level categories were linked to data elements from the Muscular Dystrophy Surveillance, Tracking, and Research Network surveillance database. Our findings support continued development of a core set of body functions from the International Classification of Functioning, Disability and Health system that are representative of disease progression in dystrophinopathies and the incorporation of these functions in standardized evaluations of functional health and implementation of individualized rehabilitation care plans. Implications for Rehabilitation Duchenne and Becker muscular dystrophies, collectively referred to as dystrophinopathies, are X-linked recessive disorders that affect the production of dystrophin resulting in compromised muscle function across multiple systems. The severity and progressive nature of dystrophinopathies can have considerable impact on a patient's participation in activities across multiple life domains. Our findings support continued development of an International Classification of Functioning, Disability and Health core set for childhood-onset dystrophinopathies. A standardized dystrophinopathy International Classification of Functioning, Disability and Health documentation form can be used as a screening tool by rehabilitation professionals and for patient goal setting when developing rehabilitation plans. Patient reports of perceived functional health should be incorporated into the rehabilitation plan and therapeutic progress monitored by a standardized form.

An open data mining framework for the analysis of medical images: application on obstructive nephropathy microscopy images.

PubMed

Doukas, Charalampos; Goudas, Theodosis; Fischer, Simon; Mierswa, Ingo; Chatziioannou, Aristotle; Maglogiannis, Ilias

2010-01-01

This paper presents an open image-mining framework that provides access to tools and methods for the characterization of medical images. Several image processing and feature extraction operators have been implemented and exposed through Web Services. Rapid-Miner, an open source data mining system has been utilized for applying classification operators and creating the essential processing workflows. The proposed framework has been applied for the detection of salient objects in Obstructive Nephropathy microscopy images. Initial classification results are quite promising demonstrating the feasibility of automated characterization of kidney biopsy images.

Comparing Features for Classification of MEG Responses to Motor Imagery.

PubMed

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio-spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system.

Toward the establishment of standardized in vitro tests for lipid-based formulations, part 4: proposing a new lipid formulation performance classification system.

PubMed

Williams, Hywel D; Sassene, Philip; Kleberg, Karen; Calderone, Marilyn; Igonin, Annabel; Jule, Eduardo; Vertommen, Jan; Blundell, Ross; Benameur, Hassan; Müllertz, Anette; Porter, Christopher J H; Pouton, Colin W

2014-08-01

The Lipid Formulation Classification System Consortium looks to develop standardized in vitro tests and to generate much-needed performance criteria for lipid-based formulations (LBFs). This article highlights the value of performing a second, more stressful digestion test to identify LBFs near a performance threshold and to facilitate lead formulation selection in instances where several LBF prototypes perform adequately under standard digestion conditions (but where further discrimination is necessary). Stressed digestion tests can be designed based on an understanding of the factors that affect LBF performance, including the degree of supersaturation generated on dispersion/digestion. Stresses evaluated included decreasing LBF concentration (↓LBF), increasing bile salt, and decreasing pH. Their capacity to stress LBFs was dependent on LBF composition and drug type: ↓LBF was a stressor to medium-chain glyceride-rich LBFs, but not more hydrophilic surfactant-rich LBFs, whereas decreasing pH stressed tolfenamic acid LBFs, but not fenofibrate LBFs. Lastly, a new Performance Classification System, that is, LBF composition independent, is proposed to promote standardized LBF comparisons, encourage robust LBF development, and facilitate dialogue with the regulatory authorities. This classification system is based on the concept that performance evaluations across three in vitro tests, designed to subject a LBF to progressively more challenging conditions, will enable effective LBF discrimination and performance grading. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

42 CFR 412.503 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... through September 30. LTC-DRG stands for the diagnosis-related group used to classify patient discharges... on or after October 1, 2007, are classified by a severity-adjusted patient classification system, the MS-LTC-DRGs. Any reference to the term “LTC-DRG” shall be considered a reference to the term “MS-LTC...

75 FR 23105 - Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System Payment-Update for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-30

... Disorders Fourth Edition--Text Revision. DRGs Diagnosis-related groups. FY Federal fiscal year. ICD-9-CM...) coding and diagnosis-related groups (DRGs) classification changes discussed in the annual update to the... for the following patient-level characteristics: Medicare Severity diagnosis related groups (MS-DRGs...

Classifying Partner Femicide

ERIC Educational Resources Information Center

Dixon, Louise; Hamilton-Giachritsis, Catherine; Browne, Kevin

2008-01-01

The heterogeneity of domestic violent men has long been established. However, research has failed to examine this phenomenon among men committing the most severe form of domestic violence. This study aims to use a multi-dimensional approach to empirically construct a classification system of men who are incarcerated for the murder of their female…

The Frequency and Severity of Magnetic Resonance Imaging Abnormalities in Infants with Mild Neonatal Encephalopathy.

PubMed

Walsh, Brian H; Neil, Jeffrey; Morey, JoAnn; Yang, Edward; Silvera, Michelle V; Inder, Terrie E; Ortinau, Cynthia

2017-08-01

To assess and contrast the incidence and severity of abnormalities on cerebral magnetic resonance imaging (MRI) between infants with mild, moderate, and severe neonatal encephalopathy who received therapeutic hypothermia. This retrospective cohort studied infants with mild, moderate, and severe neonatal encephalopathy who received therapeutic hypothermia at a single tertiary neonatal intensive care unit between 2013 and 2015. Two neuroradiologists masked to the clinical condition evaluated brain MRIs for cerebral injury after therapeutic hypothermia using the Barkovich classification system. Additional abnormalities not included in this classification system were also noted. The rate, pattern, and severity of abnormalities/injury were compared across the grades of neonatal encephalopathy. Eighty-nine infants received therapeutic hypothermia and met study criteria, 48 with mild neonatal encephalopathy, 35 with moderate neonatal encephalopathy, and 6 with severe neonatal encephalopathy. Forty-eight infants (54%) had an abnormality on MRI. There was no difference in the rate of overall MRI abnormalities by grade of neonatal encephalopathy (mild neonatal encephalopathy 54%, moderate neonatal encephalopathy 54%, and severe neonatal encephalopathy 50%; P= .89). Basal ganglia/thalamic injury was more common in those with severe neonatal encephalopathy (mild neonatal encephalopathy 4%, moderate neonatal encephalopathy 9%, severe neonatal encephalopathy 34%; P = .03). In contrast, watershed injury did not differ between neonatal encephalopathy grades (mild neonatal encephalopathy 36%, moderate neonatal encephalopathy 32%, severe neonatal encephalopathy 50%; P = .3). Mild neonatal encephalopathy is commonly associated with MRI abnormalities after therapeutic hypothermia. The grade of neonatal encephalopathy during the first hours of life may not discriminate adequately between infants with and without cerebral injury noted on MRI after therapeutic hypothermia. Copyright © 2017 Elsevier Inc. All rights reserved.

Developing an automatic classification system of vegetation anomalies for early warning with the ASAP (Anomaly hot Spots of Agricultural Production) system

NASA Astrophysics Data System (ADS)

Meroni, M.; Rembold, F.; Urbano, F.; Lemoine, G.

2016-12-01

Anomaly maps and time profiles of remote sensing derived indicators relevant to monitor crop and vegetation stress can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for SDG 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide monthly warning of production deficits in water-limited agriculture worldwide. The first step is fully automated and aims at classifying each administrative unit (1st sub-national level) into a number of possible warning levels, ranging from "none" to "watch" and up to "extended alarm". The second step involves the verification of the automatic warnings and integration into a short national level analysis by agricultural analysts. In this paper we describe the methodological development of the automatic vegetation anomaly classification system. Warnings are triggered only during the crop growing season, defined by a remote sensing based phenology. The classification takes into consideration the fraction of the agricultural and rangelands area for each administrative unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index (SPI), computed at 1 and 3-month scale) and one biophysical indicator (the cumulative NDVI from the start of the growing season). The severity of the warning thus depends on the timing, the nature and the number of indicators for which an anomaly is detected. The prototype system is using global NDVI images of the METOP sensor, while a second version is being developed based on 1km Modis NDVI with temporal smoothing and near real time filtering. Also a specific water balance model is under development to include agriculture water stress information in addition to the SPI. The monthly warning classification and crop condition assessment will be made available on a website and will strengthen the JRC support to information products based on consensus assessment such as the GEOGLAM Crop Monitor for Early Warning.

Construction of an Yucatec Maya soil classification and comparison with the WRB framework

PubMed Central

2010-01-01

Background Mayas living in southeast Mexico have used soils for millennia and provide thus a good example for understanding soil-culture relationships and for exploring the ways indigenous people name and classify the soils of their territory. This paper shows an attempt to organize the Maya soil knowledge into a soil classification scheme and compares the latter with the World Reference Base for Soil Resources (WRB). Methods Several participative soil surveys were carried out in the period 2000-2009 with the help of bilingual Maya-Spanish-speaking farmers. A multilingual soil database was built with 315 soil profile descriptions. Results On the basis of the diagnostic soil properties and the soil nomenclature used by Maya farmers, a soil classification scheme with a hierarchic, dichotomous and open structure was constructed, organized in groups and qualifiers in a fashion similar to that of the WRB system. Maya soil properties were used at the same categorical levels as similar diagnostic properties are used in the WRB system. Conclusions The Maya soil classification (MSC) is a natural system based on key properties, such as relief position, rock types, size and quantity of stones, color of topsoil and subsoil, depth, water dynamics, and plant-supporting processes. The MSC addresses the soil properties of surficial and subsurficial horizons, and uses plant communities as qualifier in some cases. The MSC is more accurate than the WRB for classifying Leptosols. PMID:20152047

Construction of an Yucatec Maya soil classification and comparison with the WRB framework.

PubMed

Bautista, Francisco; Zinck, J Alfred

2010-02-13

Mayas living in southeast Mexico have used soils for millennia and provide thus a good example for understanding soil-culture relationships and for exploring the ways indigenous people name and classify the soils of their territory. This paper shows an attempt to organize the Maya soil knowledge into a soil classification scheme and compares the latter with the World Reference Base for Soil Resources (WRB). Several participative soil surveys were carried out in the period 2000-2009 with the help of bilingual Maya-Spanish-speaking farmers. A multilingual soil database was built with 315 soil profile descriptions. On the basis of the diagnostic soil properties and the soil nomenclature used by Maya farmers, a soil classification scheme with a hierarchic, dichotomous and open structure was constructed, organized in groups and qualifiers in a fashion similar to that of the WRB system. Maya soil properties were used at the same categorical levels as similar diagnostic properties are used in the WRB system. The Maya soil classification (MSC) is a natural system based on key properties, such as relief position, rock types, size and quantity of stones, color of topsoil and subsoil, depth, water dynamics, and plant-supporting processes. The MSC addresses the soil properties of surficial and subsurficial horizons, and uses plant communities as qualifier in some cases. The MSC is more accurate than the WRB for classifying Leptosols.

Assessment and classification of cancer breakthrough pain: a systematic literature review.

PubMed

Haugen, Dagny Faksvåg; Hjermstad, Marianne Jensen; Hagen, Neil; Caraceni, Augusto; Kaasa, Stein

2010-06-01

Temporal variations in cancer pain intensity are highly prevalent, and are often difficult to manage. However, the phenomenon is not well understood: several definitions and approaches to classification and bedside assessment of cancer breakthrough pain (BTP) have been described. The present study is a systematic review of published literature on cancer BTP to answer the following questions: which terms and definitions have been used; are there validated assessment tools; which domains of BTP do the tools delineate, and which items do they contain; how have assessment tools been applied within clinical studies; and are there validated classification systems for BTP. A systematic search of the peer-reviewed literature was performed using five major databases. Of 375 titles and abstracts initially identified, 51 articles were examined in detail. Analysis of these publications indicates a range of overlapping but distinct definitions have been used to characterize BTP; 42 of the included papers presented one or more ways of classifying BTP; and while 10 tools to assess patients' experience of BTP were identified, only 2 have been partially validated. We conclude that there is no widely accepted definition, classification system or well-validated assessment tool for cancer-related breakthrough pain, but there is strong concurrence on most of its key attributes. With further work in this area, an internationally agreed upon definition and classification system for cancer-related breakthrough pain, and a standard approach on how to measure it, hold the promise to improve patient care and support research in this poor-prognosis cancer pain syndrome.

Knee replacement and Diagnosis-Related Groups (DRGs): patient classification and hospital reimbursement in 11 European countries.

PubMed

Tan, Siok Swan; Chiarello, Pietro; Quentin, Wilm

2013-11-01

Researchers from 11 countries (Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their Diagnosis-Related Group (DRG) systems deal with knee replacement cases. The study aims to assist knee surgeons and national authorities to optimize the grouping algorithm of their DRG systems. National or regional databases were used to identify hospital cases treated with a procedure of knee replacement. DRG classification algorithms and indicators of resource consumption were compared for those DRGs that together comprised at least 97 % of cases. Five standardized case scenarios were defined and quasi-prices according to national DRG-based hospital payment systems ascertained. Grouping algorithms for knee replacement vary widely across countries: they classify cases according to different variables (between one and five classification variables) into diverging numbers of DRGs (between one and five DRGs). Even the most expensive DRGs generally have a cost index below 2.00, implying that grouping algorithms do not adequately account for cases that are more than twice as costly as the index DRG. Quasi-prices for the most complex case vary between euro 4,920 in Estonia and euro 14,081 in Spain. Most European DRG systems were observed to insufficiently consider the most important determinants of resource consumption. Several countries' DRG system might be improved through the introduction of classification variables for revision of knee replacement or for the presence of complications or comorbidities. Ultimately, this would contribute to assuring adequate performance comparisons and fair hospital reimbursement on the basis of DRGs.

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

NASA Technical Reports Server (NTRS)

Penaloza, Mauel A.; Welch, Ronald M.

1996-01-01

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Caracterization of adults with cerebral palsy.

PubMed

Margre, Anna L M; Reis, Maria G L; Morais, Rosane L S

2010-01-01

cerebral Palsy (CP) is a group of permanent disorders of the development of movement and posture that cause functional limitation and are attributed to non-progressive disorders which occur in the fetal or infant brain. In recent years, with the increase in life expectancy of individuals with CP, several studies have described the impact of musculoskeletal disabilities and functional limitations over the life cycle. to characterize adults with CP through sociodemographic information, classifications, general health, associated conditions, physical complications and locomotion. twenty-two adults with CP recruited from local rehabilitation centers in an inner town of Brazil participated in this study. A questionnaire was used to collect data on sociodemographic characteristics, comorbities, and physical complications. A brief physical therapy evaluation was carried out, and the Gross Motor Function Classification System (GMFCS) and the Manual Ability Classification System (MACS) were applied. Data were analyzed through descriptive statistics. the mean age was 28.7 (SD 10.6) years, 86.4% of participants lived with parents, and 4.5% were employed. Most of the sample consisted of spastic quadriplegic subjects, corresponding to levels IV and V of the GMFCS and MACS. Different comorbidities and important physical complications such as scoliosis and muscle contractures were present. More than half of the participants were unable to walk. Most participants demonstrated important restrictions in social participation and lower educational level. Adults with CP can be affected by several physical complications and progressive limitations in gait.

A comparison of spectral decorrelation techniques and performance evaluation metrics for a wavelet-based, multispectral data compression algorithm

NASA Technical Reports Server (NTRS)

Matic, Roy M.; Mosley, Judith I.

1994-01-01

Future space-based, remote sensing systems will have data transmission requirements that exceed available downlinks necessitating the use of lossy compression techniques for multispectral data. In this paper, we describe several algorithms for lossy compression of multispectral data which combine spectral decorrelation techniques with an adaptive, wavelet-based, image compression algorithm to exploit both spectral and spatial correlation. We compare the performance of several different spectral decorrelation techniques including wavelet transformation in the spectral dimension. The performance of each technique is evaluated at compression ratios ranging from 4:1 to 16:1. Performance measures used are visual examination, conventional distortion measures, and multispectral classification results. We also introduce a family of distortion metrics that are designed to quantify and predict the effect of compression artifacts on multi spectral classification of the reconstructed data.

Differentiation of several interstitial lung disease patterns in HRCT images using support vector machine: role of databases on performance

NASA Astrophysics Data System (ADS)

Kale, Mandar; Mukhopadhyay, Sudipta; Dash, Jatindra K.; Garg, Mandeep; Khandelwal, Niranjan

2016-03-01

Interstitial lung disease (ILD) is complicated group of pulmonary disorders. High Resolution Computed Tomography (HRCT) considered to be best imaging technique for analysis of different pulmonary disorders. HRCT findings can be categorised in several patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Nodular, Normal etc. based on their texture like appearance. Clinician often find it difficult to diagnosis these pattern because of their complex nature. In such scenario computer-aided diagnosis system could help clinician to identify patterns. Several approaches had been proposed for classification of ILD patterns. This includes computation of textural feature and training /testing of classifier such as artificial neural network (ANN), support vector machine (SVM) etc. In this paper, wavelet features are calculated from two different ILD database, publically available MedGIFT ILD database and private ILD database, followed by performance evaluation of ANN and SVM classifiers in terms of average accuracy. It is found that average classification accuracy by SVM is greater than ANN where trained and tested on same database. Investigation continued further to test variation in accuracy of classifier when training and testing is performed with alternate database and training and testing of classifier with database formed by merging samples from same class from two individual databases. The average classification accuracy drops when two independent databases used for training and testing respectively. There is significant improvement in average accuracy when classifiers are trained and tested with merged database. It infers dependency of classification accuracy on training data. It is observed that SVM outperforms ANN when same database is used for training and testing.

Hierarchical Modelling Of Mobile, Seeing Robots

NASA Astrophysics Data System (ADS)

Luh, Cheng-Jye; Zeigler, Bernard P.

1990-03-01

This paper describes the implementation of a hierarchical robot simulation which supports the design of robots with vision and mobility. A seeing robot applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.

Hierarchical modelling of mobile, seeing robots

NASA Technical Reports Server (NTRS)

Luh, Cheng-Jye; Zeigler, Bernard P.

1990-01-01

This paper describes the implementation of a hierarchical robot simulation which supports the design of robots with vision and mobility. A seeing robot applies a classification expert system for visual identification of laboratory objects. The visual data acquisition algorithm used by the robot vision system has been developed to exploit multiple viewing distances and perspectives. Several different simulations have been run testing the visual logic in a laboratory environment. Much work remains to integrate the vision system with the rest of the robot system.

Annual Symposium on Machine Processing of Remotely Sensed Data, 4th, Purdue University, West Lafayette, Ind., June 21-23, 1977, Proceedings

NASA Technical Reports Server (NTRS)

Morrison, D. B. (Editor); Scherer, D. J.

1977-01-01

Papers are presented on a variety of techniques for the machine processing of remotely sensed data. Consideration is given to preprocessing methods such as the correction of Landsat data for the effects of haze, sun angle, and reflectance and to the maximum likelihood estimation of signature transformation algorithm. Several applications of machine processing to agriculture are identified. Various types of processing systems are discussed such as ground-data processing/support systems for sensor systems and the transfer of remotely sensed data to operational systems. The application of machine processing to hydrology, geology, and land-use mapping is outlined. Data analysis is considered with reference to several types of classification methods and systems.

Ecological Land Classification: Applications to Identify the Productive Potential of Southern Forests

Treesearch

Dennis L. Mengel; D. Thompson Tew; [Editors

1991-01-01

Eighteen papers representing four categories-Regional Overviews; Classification System Development; Classification System Interpretation; Mapping/GIS Applications in Classification Systems-present the state of the art in forest-land classification and evaluation in the South. In addition, nine poster papers are presented.

Classifier fusion for VoIP attacks classification

NASA Astrophysics Data System (ADS)

Safarik, Jakub; Rezac, Filip

2017-05-01

SIP is one of the most successful protocols in the field of IP telephony communication. It establishes and manages VoIP calls. As the number of SIP implementation rises, we can expect a higher number of attacks on the communication system in the near future. This work aims at malicious SIP traffic classification. A number of various machine learning algorithms have been developed for attack classification. The paper presents a comparison of current research and the use of classifier fusion method leading to a potential decrease in classification error rate. Use of classifier combination makes a more robust solution without difficulties that may affect single algorithms. Different voting schemes, combination rules, and classifiers are discussed to improve the overall performance. All classifiers have been trained on real malicious traffic. The concept of traffic monitoring depends on the network of honeypot nodes. These honeypots run in several networks spread in different locations. Separation of honeypots allows us to gain an independent and trustworthy attack information.

Joint Concept Correlation and Feature-Concept Relevance Learning for Multilabel Classification.

PubMed

Zhao, Xiaowei; Ma, Zhigang; Li, Zhi; Li, Zhihui

2018-02-01

In recent years, multilabel classification has attracted significant attention in multimedia annotation. However, most of the multilabel classification methods focus only on the inherent correlations existing among multiple labels and concepts and ignore the relevance between features and the target concepts. To obtain more robust multilabel classification results, we propose a new multilabel classification method aiming to capture the correlations among multiple concepts by leveraging hypergraph that is proved to be beneficial for relational learning. Moreover, we consider mining feature-concept relevance, which is often overlooked by many multilabel learning algorithms. To better show the feature-concept relevance, we impose a sparsity constraint on the proposed method. We compare the proposed method with several other multilabel classification methods and evaluate the classification performance by mean average precision on several data sets. The experimental results show that the proposed method outperforms the state-of-the-art methods.

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

42 CFR 412.513 - Patient classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS...-DRGs. (1) The classification of a particular discharge is based, as appropriate, on the patient's age...

Levels of Evidence in Cosmetic Surgery: Analysis and Recommendations Using a New CLEAR Classification

PubMed Central

2013-01-01

Background: The Level of Evidence rating was introduced in 2011 to grade the quality of publications. This system evaluates study design but does not assess several other quality indicators. This study introduces a new “Cosmetic Level of Evidence And Recommendation” (CLEAR) classification that includes additional methodological criteria and compares this new classification with the existing system. Methods: All rated publications in the Cosmetic Section of Plastic and Reconstructive Surgery, July 2011 through June 2013, were evaluated. The published Level of Evidence rating (1–5) and criteria relevant to study design and methodology for each study were tabulated. A new CLEAR rating was assigned to each article, including a recommendation grade (A–D). The published Level of Evidence rating (1–5) was compared with the recommendation grade determined using the CLEAR classification. Results: Among the 87 cosmetic articles, 48 studies (55%) were designated as level 4. Three articles were assigned a level 1, but they contained deficiencies sufficient to undermine the conclusions. The correlation between the published Level of Evidence classification (1–5) and CLEAR Grade (A–D) was weak (ρ = 0.11, not significant). Only 41 studies (48%) evaluated consecutive patients or consecutive patients meeting inclusion criteria. Conclusions: The CLEAR classification considers methodological factors in evaluating study reliability. A prospective study among consecutive patients meeting eligibility criteria, with a reported inclusion rate, the use of contemporaneous controls when indicated, and consideration of confounders is a realistic goal. Such measures are likely to improve study quality. PMID:25289261

Return to play after thigh muscle injury in elite football players: implementation and validation of the Munich muscle injury classification

PubMed Central

Ekstrand, Jan; Askling, Carl; Magnusson, Henrik; Mithoefer, Kai

2013-01-01

Background Owing to the complexity and heterogeneity of muscle injuries, a generally accepted classification system is still lacking. Aims To prospectively implement and validate a novel muscle injury classification and to evaluate its predictive value for return to professional football. Methods The recently described Munich muscle injury classification was prospectively evaluated in 31 European professional male football teams during the 2011/2012 season. Thigh muscle injury types were recorded by team medical staff and correlated to individual player exposure and resultant time-loss. Results In total, 393 thigh muscle injuries occurred. The muscle classification system was well received with a 100% response rate. Two-thirds of thigh muscle injuries were classified as structural and were associated with longer lay-off times compared to functional muscle disorders (p<0.001). Significant differences were observed between structural injury subgroups (minor partial, moderate partial and complete injuries) with increasing lay-off time associated with more severe structural injury. Median lay-off time of functional disorders was 5–8 days without significant differences between subgroups. There was no significant difference in the absence time between anterior and posterior thigh injuries. Conclusions The Munich muscle classification demonstrates a positive prognostic validity for return to play after thigh muscle injury in professional male football players. Structural injuries are associated with longer average lay-off times than functional muscle disorders. Subclassification of structural injuries correlates with return to play, while subgrouping of functional disorders shows less prognostic relevance. Functional disorders are often underestimated clinically and require further systematic study. PMID:23645834

Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

NASA Astrophysics Data System (ADS)

Santiago Girola Schneider, Rafael

2015-08-01

The fuzzy logic is a branch of the artificial intelligence founded on the concept that 'everything is a matter of degree.' It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others.The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters.Fuzzy logic enables the researcher to work with “imprecise” information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic’s techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

Challenges And Results of the Applications of Fuzzy Logic in the Classification of Rich Galaxy Clusters

NASA Astrophysics Data System (ADS)

Girola Schneider, R.

2017-07-01

The fuzzy logic is a branch of the artificial intelligence founded on the concept that everything is a matter of degree. It intends to create mathematical approximations on the resolution of certain types of problems. In addition, it aims to produce exact results obtained from imprecise data, for which it is particularly useful for electronic and computer applications. This enables it to handle vague or unspecific information when certain parts of a system are unknown or ambiguous and, therefore, they cannot be measured in a reliable manner. Also, when the variation of a variable can produce an alteration on the others The main focus of this paper is to prove the importance of these techniques formulated from a theoretical analysis on its application on ambiguous situations in the field of the rich clusters of galaxies. The purpose is to show its applicability in the several classification systems proposed for the rich clusters, which are based on criteria such as the level of richness of the cluster, the distribution of the brightest galaxies, whether there are signs of type-cD galaxies or not or the existence of sub-clusters. Fuzzy logic enables the researcher to work with "imprecise" information implementing fuzzy sets and combining rules to define actions. The control systems based on fuzzy logic join input variables that are defined in terms of fuzzy sets through rule groups that produce one or several output values of the system under study. From this context, the application of the fuzzy logic's techniques approximates the solution of the mathematical models in abstractions about the rich galaxy cluster classification of physical properties in order to solve the obscurities that must be confronted by an investigation group in order to make a decision.

Use of signal analysis of heart sounds and murmurs to assess severity of mitral valve regurgitation attributable to myxomatous mitral valve disease in dogs.

PubMed

Ljungvall, Ingrid; Ahlstrom, Christer; Höglund, Katja; Hult, Peter; Kvart, Clarence; Borgarelli, Michele; Ask, Per; Häggström, Jens

2009-05-01

To investigate use of signal analysis of heart sounds and murmurs in assessing severity of mitral valve regurgitation (mitral regurgitation [MR]) in dogs with myxomatous mitral valve disease (MMVD). 77 client-owned dogs. Cardiac sounds were recorded from dogs evaluated by use of auscultatory and echocardiographic classification systems. Signal analysis techniques were developed to extract 7 sound variables (first frequency peak, murmur energy ratio, murmur duration > 200 Hz, sample entropy and first minimum of the auto mutual information function of the murmurs, and energy ratios of the first heart sound [S1] and second heart sound [S2]). Significant associations were detected between severity of MR and all sound variables, except the energy ratio of S1. An increase in severity of MR resulted in greater contribution of higher frequencies, increased signal irregularity, and decreased energy ratio of S2. The optimal combination of variables for distinguishing dogs with high-intensity murmurs from other dogs was energy ratio of S2 and murmur duration > 200 Hz (sensitivity, 79%; specificity, 71%) by use of the auscultatory classification. By use of the echocardiographic classification, corresponding variables were auto mutual information, first frequency peak, and energy ratio of S2 (sensitivity, 88%; specificity, 82%). Most of the investigated sound variables were significantly associated with severity of MR, which indicated a powerful diagnostic potential for monitoring MMVD. Signal analysis techniques could be valuable for clinicians when performing risk assessment or determining whether special care and more extensive examinations are required.

False alarm reduction by the And-ing of multiple multivariate Gaussian classifiers

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2003-09-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. This paper describes a method for training several multivariate Gaussian classifiers such that their And-ing dramatically reduces false alarms while maintaining a high probability of classification. This training approach is referred to as the Focused- Training method. This work extends our 2001-2002 work where the Focused-Training method was used with three other types of classifiers: the Attractor-based K-Nearest Neighbor Neural Network (a type of radial-basis, probabilistic neural network), the Optimal Discrimination Filter Classifier (based linear discrimination theory), and the Quadratic Penalty Function Support Vector Machine (QPFSVM). Although our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to a wide range of pattern recognition and automatic target recognition (ATR) problems.

Use of routinely available clinical, nutritional, and functional criteria to classify cachexia in advanced cancer patients.

PubMed

Vigano, Antonio A L; Morais, José A; Ciutto, Lorella; Rosenthall, Leonard; di Tomasso, Jonathan; Khan, Sarah; Olders, Henry; Borod, Manuel; Kilgour, Robert D

2017-10-01

Cachexia is a highly prevalent syndrome in cancer and chronic diseases. However, due to the heterogeneous features of cancer cachexia, its identification and classification challenge clinical practitioners. To determine the clinical relevance of a cancer cachexia classification system in advanced cancer patients. Beginning with the four-stage classification system proposed for cachexia [non-cachexia (NCa), pre-cachexia (PCa), cachexia (Ca) and refractory cachexia (RCa)], we assigned patients to these cachexia stages according to five classification criteria available in clinical practice: 1) biochemistry (high C-reactive protein or leukocytes, or hypoalbuminemia, or anemia), 2) food intake (normal/decreased), weight loss: 3) moderate (≤5%) or 4) significant (>5%/past six months) and 5) performance status (Eastern Cooperative Oncology Group Performance Status ≥ 3). We then determined if symptom severity, body composition changes, functional levels, hospitalizations and survival rates varied significantly across cachexia stages. Two-hundred and ninety-seven advanced cancer patients with primary gastrointestinal and lung tumors were included. Patients were classified into Ca (36%), PCa and RCa (21%, respectively) and NCa (15%). Significant (p < 0.05) differences were observed among cachexia stages for most of the outcome measures (symptoms, body composition, handgrip strength, emergency room visits and length of hospital stays) according to cachexia severity. Survival also differed between cachexia stages (except between PCa and Ca). Five clinical criteria can be used to stage cancer cachexia patients and predict important clinical, nutritional and functional outcomes. The lack of statistical difference between PCa and Ca in almost all clinical outcomes examined suggests either that the PCa group includes patients already affected by early cachexia or that more precise criteria are needed to differentiate PCa from Ca patients. More studies are required to validate these findings. Copyright © 2016. Published by Elsevier Ltd.

Analysis of the comprehensibility of chemical hazard communication tools at the industrial workplace.

PubMed

Ta, Goh Choo; Mokhtar, Mazlin Bin; Mohd Mokhtar, Hj Anuar Bin; Ismail, Azmir Bin; Abu Yazid, Mohd Fadhil Bin Hj

2010-01-01

Chemical classification and labelling systems may be roughly similar from one country to another but there are significant differences too. In order to harmonize various chemical classification systems and ultimately provide consistent chemical hazard communication tools worldwide, the Globally Harmonized System of Classification and Labelling of Chemicals (GHS) was endorsed by the United Nations Economic and Social Council (ECOSOC). Several countries, including Japan, Taiwan, Korea and Malaysia, are now in the process of implementing GHS. It is essential to ascertain the comprehensibility of chemical hazard communication tools that are described in the GHS documents, namely the chemical labels and Safety Data Sheets (SDS). Comprehensibility Testing (CT) was carried out with a mixed group of industrial workers in Malaysia (n=150) and factors that influence the comprehensibility were analysed using one-way ANOVA. The ability of the respondents to retrieve information from the SDS was also tested in this study. The findings show that almost all the GHS pictograms meet the ISO comprehension criteria and it is concluded that the underlying core elements that enhance comprehension of GHS pictograms and which are also essential in developing competent persons in the use of SDS are training and education.

Predicting fire severity using surface fuels and moisture

Treesearch

Pamela G. Sikkink; Robert E. Keane

2012-01-01

Fire severity classifications have been used extensively in fire management over the last 30 years to describe specific environmental or ecological impacts of fire on fuels, vegetation, wildlife, and soils in recently burned areas. New fire severity classifications need to be more objective, predictive, and ultimately more useful to fire management and planning. Our...

Harmonizing the Classification of Age-related Macular Degeneration in the Three Continent AMD Consortium

PubMed Central

Klein, Ronald; Meuer, Stacy M.; Myers, Chelsea E.; Buitendijk, Gabriëlle H. S.; Rochtchina, Elena; Choudhury, Farzana; de Jong, Paulus T. V. M.; McKean-Cowdin, Roberta; Iyengar, Sudha K.; Gao, Xiaoyi; Lee, Kristine E.; Vingerling, Johannes R.; Mitchell, Paul; Klaver, Caroline C. W.; Wang, Jie Jin; Klein, Barbara E. K.

2014-01-01

Purpose To describe methods to harmonize the classification of age-related macular degeneration (AMD) phenotypes across four population-based cohort studies: the Beaver Dam Eye Study (BDES), Blue Mountains Eye Study (BMES), Los Angeles Latino Eye Study (LALES), and Rotterdam Study (RS). Methods AMD grading protocols, definitions of categories, and grading forms from each study were compared to determine whether there were systematic differences in AMD severity definitions and lesion categorization among the three grading centers. Each center graded the same set of 60 images using their respective systems to determine presence and severity of AMD lesions. A common five-step AMD severity scale and definitions of lesion measurement cutpoints and early and late AMD were developed from this exercise. Results Applying this severity scale changed the age-sex adjusted prevalence of early AMD from 18.7% to 20.3% in BDES, from 4.7% to 14.4% in BMES, from 14.1% to 15.8% in LALES, and from 7.5% to 17.1% in RS. Age-sex adjusted prevalences of late AMD remained unchanged. Comparison of each center’s grades of the 60 images converted to the consortium scale showed that exact agreement of AMD severity among centers varied from 61.0% to 81.4%, and one-step agreement varied from 84.7% to 98.3%. Conclusion Harmonization of AMD classification reduced categorical differences in phenotypic definitions across the studies, resulted in a new 5-step AMD severity scale, and enhanced similarity of AMD prevalence among four cohorts. Despite harmonization it may still be difficult to remove systematic differences in grading, if present. PMID:24467558

Prediction of Disease Case Severity Level To Determine INA CBGs Rate

NASA Astrophysics Data System (ADS)

Puspitorini, Sukma; Kusumadewi, Sri; Rosita, Linda

2017-03-01

Indonesian Case-Based Groups (INA CBGs) is case-mix payment system using software grouper application. INA CBGs consisting of four digits code where the last digits indicating the severity level of disease cases. Severity level influence by secondary diagnosis (complications and co-morbidity) related to resource intensity level. It is medical resources used to treat a hospitalized patient. Objectives of this research is developing decision support system to predict severity level of disease cases and illustrate INA CBGs rate by using data mining decision tree classification model. Primary diagnosis (DU), first secondary diagnosis (DS 1), and second secondary diagnosis (DS 2) are attributes that used as input of severity level. The training process using C4.5 algorithm and the rules will represent in the IF-THEN form. Credibility of the system analyzed through testing process and confusion matrix present the results. Outcome of this research shows that first secondary diagnosis influence significant to form severity level predicting rules from new disease cases and INA CBGs rate illustration.

Definitions for warning signs and signs of severe dengue according to the WHO 2009 classification: Systematic review of literature.

PubMed

Morra, Mostafa Ebraheem; Altibi, Ahmed M A; Iqtadar, Somia; Minh, Le Huu Nhat; Elawady, Sameh Samir; Hallab, Asma; Elshafay, Abdelrahman; Omer, Omer Abedlbagi; Iraqi, Ahmed; Adhikari, Purushottam; Labib, Jonair Hussein; Elhusseiny, Khaled Mosaad; Elgebaly, Ahmed; Yacoub, Sophie; Huong, Le Thi Minh; Hirayama, Kenji; Huy, Nguyen Tien

2018-04-24

Since warning signs and signs of severe dengue are defined differently between studies, we conducted a systematic review on how researchers defined these signs. We conducted an electronic search in Scopus to identify relevant articles, using key words including dengue, "warning signs," "severe dengue," and "classification." A total of 491 articles were identified through this search strategy and were subsequently screened by 2 independent reviewers for definitions of any of the warning or severe signs in the 2009 WHO dengue classification. We included all original articles published in English after 2009, classifying dengue by the 2009 WHO classification or providing the additional definition or criterion of warning signs and severity (besides the information of 2009 WHO). Analysis of the extracted data from 44 articles showed wide variations among definitions and cutoff values used by physicians to classify patients diagnosed with dengue infection. The establishment of clear definitions for warning signs and severity is essential to prevent unnecessary hospitalization and harmonizing the interpretation and comparability of epidemiological studies dedicated to dengue infection. Copyright © 2018 John Wiley & Sons, Ltd.

Toward noncooperative iris recognition: a classification approach using multiple signatures.

PubMed

Proença, Hugo; Alexandre, Luís A

2007-04-01

This paper focuses on noncooperative iris recognition, i.e., the capture of iris images at large distances, under less controlled lighting conditions, and without active participation of the subjects. This increases the probability of capturing very heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstructions and reflections). Current iris recognition systems are unable to deal with noisy data and substantially increase their error rates, especially the false rejections, in these conditions. We propose an iris classification method that divides the segmented and normalized iris image into six regions, makes an independent feature extraction and comparison for each region, and combines each of the dissimilarity values through a classification rule. Experiments show a substantial decrease, higher than 40 percent, of the false rejection rates in the recognition of noisy iris images.

Identifying the optimal segmentors for mass classification in mammograms

NASA Astrophysics Data System (ADS)

Zhang, Yu; Tomuro, Noriko; Furst, Jacob; Raicu, Daniela S.

2015-03-01

In this paper, we present the results of our investigation on identifying the optimal segmentor(s) from an ensemble of weak segmentors, used in a Computer-Aided Diagnosis (CADx) system which classifies suspicious masses in mammograms as benign or malignant. This is an extension of our previous work, where we used various parameter settings of image enhancement techniques to each suspicious mass (region of interest (ROI)) to obtain several enhanced images, then applied segmentation to each image to obtain several contours of a given mass. Each segmentation in this ensemble is essentially a "weak segmentor" because no single segmentation can produce the optimal result for all images. Then after shape features are computed from the segmented contours, the final classification model was built using logistic regression. The work in this paper focuses on identifying the optimal segmentor(s) from an ensemble mix of weak segmentors. For our purpose, optimal segmentors are those in the ensemble mix which contribute the most to the overall classification rather than the ones that produced high precision segmentation. To measure the segmentors' contribution, we examined weights on the features in the derived logistic regression model and computed the average feature weight for each segmentor. The result showed that, while in general the segmentors with higher segmentation success rates had higher feature weights, some segmentors with lower segmentation rates had high classification feature weights as well.

Evaluation of a wetland classification system devised for ...

EPA Pesticide Factsheets

The manuscript is part of an FY14 RAP product: "Functional Assessment of Alaska Peatlands in Cook Inlet Basin: A report to Region 10". This report included this technical information product which is a manuscript that has now been fully revised, reviewed and published in a scientific peer-reviewed publication with open access (doi:10.1007/s11273-016-9504-0). The journal article scientific abstract is as follows: "Several wetland classification schemes are now commonly used to describe wetlands in the contiguous United States to meet local, regional, and national regulatory requirements. However, these established systems have proven to be insufficient to meet the needs of land managers in Alaska. The wetlands of this northern region are predominantly peatlands, which are not adequately treated by the nationally-used systems, which have few, if any, peatland classes. A new system was therefore devised to classify wetlands in the rapidly urbanizing Cook Inlet Basin of southcentral Alaska, USA. The Cook Inlet Classification (CIC) is based on seven geomorphic and six hydrologic components that incorporate the environmental gradients responsible for the primary sources of variation in peatland ecosystems. The geomorphic and hydrologic components have the added advantage of being detectable on remote sensing imagery, which facilitates regional mapping across large tracts of inaccessible terrain. Three different quantitative measures were used to evaluate the robu

Overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three body mass index classification systems.

PubMed

St-Jean, Audray; Meziou, Salma; Ayotte, Pierre; Lucas, Michel

2017-11-22

Little is known about the suitability of three commonly used body mass index (BMI) classification systems for Indigenous youth. We estimated overweight and obesity prevalence among Cree youth of Eeyou Istchee according to three BMI classification systems, assessed the level of agreement between them, and evaluated their accuracy through body fat and cardiometabolic risk factors. Data on 288 youth (aged 8-17 years) were collected. Overweight and obesity prevalence were estimated with Centers for Disease Control and Prevention (CDC), International Obesity Task Force (IOTF) and World Health Organization (WHO) criteria. Agreement was measured with weighted kappa (κw). Associations with body fat and cardiometabolic risk factors were evaluated by analysis of variance. Obesity prevalence was 42.7% with IOTF, 47.2% with CDC, and 49.3% with WHO criteria. Agreement was almost perfect between IOTF and CDC (κw = 0.93), IOTF and WHO (κw = 0.91), and WHO and CDC (κw = 0.94). Means of body fat and cardiometabolic risk factors were significantly higher (P trend  < 0.001) from normal weight to obesity, regardless of the system used. Youth considered overweight by IOTF but obese by CDC or WHO exhibited less severe clinical obesity. IOTF seems to be more accurate in identifying obesity in Cree youth.

[State of the art diagnostic criteria of severe periodontitis].

PubMed

Ouyang, X Y

2017-02-09

Periodontitis could be categorized as mild, moderate, and severe according to the severity of the disease. This categorizing system could also be used together with other classification systems. The present article introduced the status about the case definition of severe periodontitis, including the standard of case definitions for surveillance of periodontitis reported by the Centers for Disease Control and Prevention (CDC) in partnership with the American Academy of Periodontology (AAP) and the consensus report on the definition of periodontitis case for use in risk factor research by Europe workshop. A consensus on the state of the art definition of severe periodontitis for use in clinical work was gained base on the expertise of Chinese Society of Periodontology, Chinese Association of Stomatology. The background of this consensus and the significance of the criteria for the case definition were discussed.

Modelling for Understanding AND for Prediction/Classification--The Power of Neural Networks in Research

ERIC Educational Resources Information Center

Cascallar, Eduardo; Musso, Mariel; Kyndt, Eva; Dochy, Filip

2014-01-01

Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Musso, Kyndt, Cascallar, and Dochy (2013). Several relevant issues are raised and some important clarifications are made in response to both commentaries. Predictive systems based on artificial neural networks continue to be the focus of current…

THE USE OF GEOMORPHOLOGY AND STREAM STABILITY IN THE ASSESSMENT OF THE RISK OF STREAM IMPAIRMENT FROM SEDIMENT

EPA Science Inventory

The evaluation of the current condition is critical to the management of streams impaired by sediment and other non-point source stressors, which adversely affect both physical habitat and water quality. Several rating and classification systems based on geomorphic data exist for...

Ensemble Classifier Strategy Based on Transient Feature Fusion in Electronic Nose

NASA Astrophysics Data System (ADS)

Bagheri, Mohammad Ali; Montazer, Gholam Ali

2011-09-01

In this paper, we test the performance of several ensembles of classifiers and each base learner has been trained on different types of extracted features. Experimental results show the potential benefits introduced by the usage of simple ensemble classification systems for the integration of different types of transient features.

Entanglement in General Multipartite Quantum Systems and Its Role in Quantum Information Processing Tasks

NASA Astrophysics Data System (ADS)

Gielerak, Roman

A major role playing by entanglement of quantum states in several, present day applications of genuine quantum technologies is briefly reviewed. Additionally, the notion and classification of multipartite entanglement has been presented. A new, monotone under (S)LOCC-operations measures of many-partite entanglement are defined and discussed briefly.

What Attributes Determine Severity of Function in Autism? A Web-Based Survey of Stakeholders

ERIC Educational Resources Information Center

Di Rezze, Briano; Rosenbaum, Peter; Zwaigenbaum, Lonnie

2012-01-01

Service providers and researchers in autism spectrum disorders (ASD) are challenged to categorize clinical variation in function. Classification systems for children with cerebral palsy have enabled clinicians and families to describe levels of function. A web-based survey engaged international ASD stakeholders to advise on considerations of…

Spiraea L.: spirea

Treesearch

John C. Zasada; Peter F. Stickney

2008-01-01

There are about 80 species of the genus Spiraea throughout the world. The genus is subdivided into subgenera and sections in several ways depending upon the author - all classifications are based primarily on the structure of the inflorescence. In the system followed here (Batta 1977), the genus has 3 sections: Chamaedryon, Calospira, and Spiraria. In the United States...

Special Education and Severe Disabilities in Costa Rica: Developing Inclusion in a Developing Country.

ERIC Educational Resources Information Center

Stough, Laura M.

2003-01-01

An overview of special education in Costa Rica is provided. Costa Rica has promulgated four educational service models that extend special education expertise: consulting teachers, educational assistance teams, itinerant teams, and resource centers. Their educational classification system describes the level of modifications required by students.…

Pediatric aquatic therapy on motor function and enjoyment in children diagnosed with cerebral palsy of various motor severities.

PubMed

Lai, Chih-Jou; Liu, Wen-Yu; Yang, Tsui-Fen; Chen, Chia-Ling; Wu, Ching-Yi; Chan, Rai-Chi

2015-02-01

This study investigates the effects of pediatric aquatic therapy on motor function, enjoyment, activities of daily living, and health-related quality of life for children with spastic cerebral palsy of various motor severities. Children with spastic cerebral palsy were assigned to a pediatric aquatic therapy group (n = 11; mean age = 85.0 ± 33.1 months; male : female = 4 : 7) or a control group (n = 13; mean age = 87.6 ± 34.0 months; male : female = 9 : 4). The statistic results indicate that the pediatric aquatic therapy group had greater average 66-item Gross Motor Function Measure following intervention than the control group (η(2) = 0.308, P = .007), even for children with Gross Motor Function Classification System level IV (5.0 vs 1.3). The pediatric aquatic therapy group had higher Physical Activity Enjoyment Scale scores than the control group at post-treatment (P = .015). These findings demonstrate that pediatric aquatic therapy can be an effective and alternative therapy for children with cerebral palsy even with poor Gross Motor Function Classification System level. © The Author(s) 2014.

Physiological sensor signals classification for healthcare using sensor data fusion and case-based reasoning.

PubMed

Begum, Shahina; Barua, Shaibal; Ahmed, Mobyen Uddin

2014-07-03

Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify Stressed or Relaxed individuals using sensor data fusion. Physiological sensor signals i.e., Heart Rate (HR), Finger Temperature (FT), Respiration Rate (RR), Carbon dioxide (CO2) and Oxygen Saturation (SpO2) are collected during the data collection phase. Here, sensor fusion has been done in two different ways: (i) decision-level fusion using features extracted through traditional approaches; and (ii) data-level fusion using features extracted by means of Multivariate Multiscale Entropy (MMSE). Case-Based Reasoning (CBR) is applied for the classification of the signals. The experimental result shows that the proposed system could classify Stressed or Relaxed individual 87.5% accurately compare to an expert in the domain. So, it shows promising result in the psychophysiological domain and could be possible to adapt this approach to other relevant healthcare systems.

Classification of Unmanned Aircraft Systems. UAS Classification/Categorization for Certification

NASA Technical Reports Server (NTRS)

2004-01-01

Category, class, and type designations are primary means to identify appropriate aircraft certification basis, operating rules/limitations, and pilot qualifications to operate in the National Airspace System (NAS). The question is whether UAS fit into existing aircraft categories or classes, or are unique enough to justify the creation of a new category/class. In addition, the characteristics or capabilities, which define when an UAS becomes a regulated aircraft, must also be decided. This issue focuses on UAS classification for certification purposes. Several approaches have been considered for classifying UAS. They basically group into either using a weight/mass basis, or a safety risk basis, factoring in the performance of the UAS, including where the UAS would operate. Under existing standards, aircraft must have a Type Certificate and Certificate of Airworthiness, in order to be used for "compensation or hire", a major difference from model aircraft. Newer technologies may make it possible for very small UAS to conduct commercial services, but that is left for a future discussion to extend the regulated aircraft to a lower level. The Access 5 position is that UAS are aircraft and should be regulated above the weight threshold differentiating them from model airplanes. The recommended classification grouping is summarized in a chart.

Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

NASA Astrophysics Data System (ADS)

Schultz, Gregory M.; Keranen, Joe; Miller, Jonathan S.; Shubitidze, Fridon

2014-06-01

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

A subject-independent pattern-based Brain-Computer Interface

PubMed Central

Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos, Cristián; Zamorano, Francisco; Aboitiz, Francisco; Birbaumer, Niels; Ruiz, Sergio

2015-01-01

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofeedback of brain states from electroencephalographic (EEG) signals. It involves the creation of a fused classification model based on the method of Common Spatial Patterns (CSPs) from data of several healthy individuals. The subject-independent model is then used to classify EEG data in real-time and provide feedback to new individuals. In a series of offline experiments involving training and testing of the classifier with individual data from 27 healthy subjects, a mean classification accuracy of 75.30% was achieved, demonstrating that the classification system at hand can reliably decode two types of imagery used in our experiments, i.e., happy emotional imagery and motor imagery. In a subsequent experiment it is shown that the classifier can be used to provide neurofeedback to new subjects, and that these subjects learn to “match” their brain pattern to that of the fused classification model in a few days of neurofeedback training. This finding can have important implications for future studies on neurofeedback and its clinical applications on neuropsychiatric disorders. PMID:26539089

Enhancing navigation in biomedical databases by community voting and database-driven text classification

PubMed Central

Duchrow, Timo; Shtatland, Timur; Guettler, Daniel; Pivovarov, Misha; Kramer, Stefan; Weissleder, Ralph

2009-01-01

Background The breadth of biological databases and their information content continues to increase exponentially. Unfortunately, our ability to query such sources is still often suboptimal. Here, we introduce and apply community voting, database-driven text classification, and visual aids as a means to incorporate distributed expert knowledge, to automatically classify database entries and to efficiently retrieve them. Results Using a previously developed peptide database as an example, we compared several machine learning algorithms in their ability to classify abstracts of published literature results into categories relevant to peptide research, such as related or not related to cancer, angiogenesis, molecular imaging, etc. Ensembles of bagged decision trees met the requirements of our application best. No other algorithm consistently performed better in comparative testing. Moreover, we show that the algorithm produces meaningful class probability estimates, which can be used to visualize the confidence of automatic classification during the retrieval process. To allow viewing long lists of search results enriched by automatic classifications, we added a dynamic heat map to the web interface. We take advantage of community knowledge by enabling users to cast votes in Web 2.0 style in order to correct automated classification errors, which triggers reclassification of all entries. We used a novel framework in which the database "drives" the entire vote aggregation and reclassification process to increase speed while conserving computational resources and keeping the method scalable. In our experiments, we simulate community voting by adding various levels of noise to nearly perfectly labelled instances, and show that, under such conditions, classification can be improved significantly. Conclusion Using PepBank as a model database, we show how to build a classification-aided retrieval system that gathers training data from the community, is completely controlled by the database, scales well with concurrent change events, and can be adapted to add text classification capability to other biomedical databases. The system can be accessed at . PMID:19799796

Upper Gastrointestinal Hemorrhage: Development of the Severity Score.

PubMed

Chaikitamnuaychok, Rangson; Patumanond, Jayanton

2012-12-01

Emergency endoscopy for every patient with upper gastrointestinal hemorrhage is not possible in many medical centers. Simple guidelines to select patients for emergency endoscopy are lacking. The aim of the present report is to develop a simple scoring system to classify upper gastrointestinal hemorrhage (UGIH) severity based on patient clinical profiles at the emergency departments. Retrospective data of patients with UGIH in a university affiliated hospital were analyzed. Patients were criterion-classified into 3 severity levels: mild, moderate and severe. Clinical and laboratory information were compared among the 3 groups. Significant parameters were selected as indicators of severity. Coefficients of significant multivariable parameters were transformed into item scores, which added up as individual severity scores. The scores were used to classify patients into 3 urgency levels: non-urgent, urgent and emergent groups. Score-classification and criterion-classification were compared. Significant parameters in the model were age ≥ 60 years, pulse rate ≥ 100/min, systolic blood pressure < 100 mmHg, hemoglobin < 10 g/dL, blood urea nitrogen ≥ 35 mg/dL, presence of cirrhosis and hepatic failure. The score ranged from 0 to 27, and classifying patients into 3 urgency groups: non-urgent (score < 4, n = 215, 21.2%), urgent (score 4 - 16, n = 677, 66.9%) and emergent (score > 16, n = 121, 11.9%). The score correctly classified 81.4% of the patients into their original (criterion-classified) severity groups. Under-estimation (7.5%) and over-estimation (11.1%) were clinically acceptable. Our UGIH severity scoring system classified patients into 3 urgency groups: non-urgent, urgent and emergent, with clinically acceptable small number of under- and over-estimations. Its discriminative ability and precision should be validated before adopting into clinical practice.

5 CFR 9701.231 - Conversion of positions and employees to the DHS classification system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the DHS classification system. 9701.231 Section 9701.231 Administrative Personnel DEPARTMENT OF... MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Transitional Provisions § 9701.231 Conversion of positions and employees to the DHS classification system. (a) This...

A proposal for a CT driven classification of left colon acute diverticulitis.

PubMed

Sartelli, Massimo; Moore, Frederick A; Ansaloni, Luca; Di Saverio, Salomone; Coccolini, Federico; Griffiths, Ewen A; Coimbra, Raul; Agresta, Ferdinando; Sakakushev, Boris; Ordoñez, Carlos A; Abu-Zidan, Fikri M; Karamarkovic, Aleksandar; Augustin, Goran; Costa Navarro, David; Ulrych, Jan; Demetrashvili, Zaza; Melo, Renato B; Marwah, Sanjay; Zachariah, Sanoop K; Wani, Imtiaz; Shelat, Vishal G; Kim, Jae Il; McFarlane, Michael; Pintar, Tadaja; Rems, Miran; Bala, Miklosh; Ben-Ishay, Offir; Gomes, Carlos Augusto; Faro, Mario Paulo; Pereira, Gerson Alves; Catani, Marco; Baiocchi, Gianluca; Bini, Roberto; Anania, Gabriele; Negoi, Ionut; Kecbaja, Zurabs; Omari, Abdelkarim H; Cui, Yunfeng; Kenig, Jakub; Sato, Norio; Vereczkei, Andras; Skrovina, Matej; Das, Koray; Bellanova, Giovanni; Di Carlo, Isidoro; Segovia Lohse, Helmut A; Kong, Victor; Kok, Kenneth Y; Massalou, Damien; Smirnov, Dmitry; Gachabayov, Mahir; Gkiokas, Georgios; Marinis, Athanasios; Spyropoulos, Charalampos; Nikolopoulos, Ioannis; Bouliaris, Konstantinos; Tepp, Jaan; Lohsiriwat, Varut; Çolak, Elif; Isik, Arda; Rios-Cruz, Daniel; Soto, Rodolfo; Abbas, Ashraf; Tranà, Cristian; Caproli, Emanuele; Soldatenkova, Darija; Corcione, Francesco; Piazza, Diego; Catena, Fausto

2015-01-01

Computed tomography (CT) imaging is the most appropriate diagnostic tool to confirm suspected left colonic diverticulitis. However, the utility of CT imaging goes beyond accurate diagnosis of diverticulitis; the grade of severity on CT imaging may drive treatment planning of patients presenting with acute diverticulitis. The appropriate management of left colon acute diverticulitis remains still debated because of the vast spectrum of clinical presentations and different approaches to treatment proposed. The authors present a new simple classification system based on both CT scan results driving decisions making management of acute diverticulitis that may be universally accepted for day to day practice.

Injury severity in ice skating: an epidemiologic analysis using a standardised injury classification system.

PubMed

Ostermann, Roman C; Hofbauer, Marcus; Tiefenböck, Thomas M; Pumberger, Matthias; Tiefenböck, Michael; Platzer, Patrick; Aldrian, Silke

2015-01-01

Although injuries sustained during ice skating have been reported to be more serious than other forms of skating, the potential injury risks are often underestimated by skating participants. The purpose of this study was to give a descriptive overview of injury patterns occurring during ice skating. Special emphasis was put on injury severity by using a standardised injury classification system. Over a six month period, all patients treated with ice-skating-related injuries at Europe's largest hospital were included. Patient demographics were collected and all injuries categorised according to the Abbreviated Injury Scale (AIS) 2005. A descriptive statistic and logistic regression analysis was performed. Three hundred and forty-one patients (134 M, 207 F) were included in this study. Statistical analysis revealed that age had a significant influence on injury severity. People > 50 years had a higher risk of sustaining a more severe injury according to the AIS compared with younger skaters. Furthermore, the risk of head injury was significantly lower for people aged between 18 and 50 years than for people < 18 years (p = 0.0007) and significantly higher for people > 50 years than for people aged between 18 and 50 years (p = 0.04). The severity of ice-skating injuries is associated with the patient's age, showing more severe injuries in older patients. Awareness should be raised among the public and physicians about the risks associated with this activity in order to promote further educational interventions and the use of protective gear.

Dimensional approaches to psychiatric classification: refining the research agenda for DSM-V: an introduction.

PubMed

Regier, Darrel A

2007-01-01

The American Psychiatric Association (APA) will publish the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V), in 2012. This paper reviews the extended, multi-faceted research planning preparations that APA has undertaken, several in collaboration with the World Health Organization and the U.S. National Institutes of Health, to assess the current state of diagnosis-relevant research and to generate short- and long-term recommendations for research needed to enrich DSM-V and future psychiatric classifications. This research review and planning process has underscored widespread interest among nosologists in the US and globally regarding the potential benefits for research and clinical practice of incorporating a dimensional component into the existing categorical, or binary, classification system in the DSM. Toward this end, the APA and its partners convened an international conference in July 2006 to critically appraise the use of dimensional constructs in psychiatric diagnostic systems. Resultant papers appear in this issue of International Journal of Methods in Psychiatric Research and in a forthcoming monograph to be published by APA. Copyright (c) 2007 John Wiley & Sons, Ltd.

Decision Making in the Management of Extracapsular Fractures of the Proximal Femur – is the Dynamic Hip Screw the Prevailing Gold Standard?

PubMed Central

Jacob, Joshua; Desai, Ankit; Trompeter, Alex

2017-01-01

Currently, approximately half of all hip fractures are extracapsular, with an incidence as high as 50 in 100,000 in some countries. The common classification systems fail to explain the logistics of fracture classification and whether they all behave in the same manner. The Muller AO classification system is a useful platform to delineate stable and unstable fractures. The Dynamic hip screw (DHS) however, has remained the ‘gold standard’ implant of choice for application in all extracapsular fractures. The DHS relies on the integrity and strength of the lateral femoral wall as well as the postero-medial fragment. An analysis of several studies indicates significant improvements in design and techniques to ensure a better outcome with intramedullary nails. This article reviews the historical trends that helped to evolve the DHS implant as well as discussing if the surgeon should remain content with this implant. We suggest that the gold standard surgical management of extracapsular fractures can, and should, evolve. PMID:29290858

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed.

PubMed

Eisinger, Daniel; Tsatsaronis, George; Bundschus, Markus; Wieneke, Ulrich; Schroeder, Michael

2013-04-15

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms.Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources.

A two-step automatic sleep stage classification method with dubious range detection.

PubMed

Sousa, Teresa; Cruz, Aniana; Khalighi, Sirvan; Pires, Gabriel; Nunes, Urbano

2015-04-01

The limitations of the current systems of automatic sleep stage classification (ASSC) are essentially related to the similarities between epochs from different sleep stages and the subjects' variability. Several studies have already identified the situations with the highest likelihood of misclassification in sleep scoring. Here, we took advantage of such information to develop an ASSC system based on knowledge of subjects' variability of some indicators that characterize sleep stages and on the American Academy of Sleep Medicine (AASM) rules. An ASSC system consisting of a two-step classifier is proposed. In the first step, epochs are classified using support vector machines (SVMs) spread into different nodes of a decision tree. In the post-processing step, the epochs suspected of misclassification (dubious classification) are tagged, and a new classification is suggested. Identification and correction are based on the AASM rules, and on misclassifications most commonly found/reported in automatic sleep staging. Six electroencephalographic and two electrooculographic channels were used to classify wake, non-rapid eye movement (NREM) sleep--N1, N2 and N3, and rapid eye movement (REM) sleep. The proposed system was tested in a dataset of 14 clinical polysomnographic records of subjects suspected of apnea disorders. Wake and REM epochs not falling in the dubious range, are classified with accuracy levels compatible with the requirements for clinical applications. The suggested correction assigned to the epochs that are tagged as dubious enhances the global results of all sleep stages. This approach provides reliable sleep staging results for non-dubious epochs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automated Patent Categorization and Guided Patent Search using IPC as Inspired by MeSH and PubMed

PubMed Central

2013-01-01

Document search on PubMed, the pre-eminent database for biomedical literature, relies on the annotation of its documents with relevant terms from the Medical Subject Headings ontology (MeSH) for improving recall through query expansion. Patent documents are another important information source, though they are considerably less accessible. One option to expand patent search beyond pure keywords is the inclusion of classification information: Since every patent is assigned at least one class code, it should be possible for these assignments to be automatically used in a similar way as the MeSH annotations in PubMed. In order to develop a system for this task, it is necessary to have a good understanding of the properties of both classification systems. This report describes our comparative analysis of MeSH and the main patent classification system, the International Patent Classification (IPC). We investigate the hierarchical structures as well as the properties of the terms/classes respectively, and we compare the assignment of IPC codes to patents with the annotation of PubMed documents with MeSH terms. Our analysis shows a strong structural similarity of the hierarchies, but significant differences of terms and annotations. The low number of IPC class assignments and the lack of occurrences of class labels in patent texts imply that current patent search is severely limited. To overcome these limits, we evaluate a method for the automated assignment of additional classes to patent documents, and we propose a system for guided patent search based on the use of class co-occurrence information and external resources. PMID:23734562

Joint action on monitoring injuries in Europe (JAMIE).

PubMed

Rogmans, W H J

2012-08-28

The hospital sector provides the best setting for collecting information as this information relates to the most severe cases (while less severe cases are treated by family doctors of school nurses for instance) and information can be obtained easily on a large number of cases at low cost (while surveys are expensive and suffering serious deficiencies as regards the specificity of data obtained). The WHO-International Classification of Diseases and its derivative classification on external causes of injuries provide the proper tools for standardised data collection on injuries treated within the health sector.In order to make injury data collection affordable for countries to collect and to have a greater number of countries joining the data exchange efforts, JAMIE envisages to have a relatively limited set data elements being collected in a representative sample of emergency departments in countries, while collecting in a few departments deeper information on the circumstances of the injury event. Injuries due to accidents or violence constitute a major public health problem globally and also within the 27 member states of the European Union (EU-MSs). In spite of the magnitude and the severity of the problem, injury surveillance systems are not yet sufficiently well developed to accurately quantify the burden of injuries on individuals, health services and society in the EU-region. Much of the injury information generated up until now is not comparable between countries, and not between registers, due to the lack of harmonised methodology and classification. JAMIE project aims at having by 2015 a common emergency departmental-based surveillance system for injury prevention in operation in all MS. Such a system should report on external causes of injuries due to accidents and violence as part of the Community Statistics on Public Health. The project will build on previous work on injury data exchange initiated by the European Commission (EC) and a number of EU-member states, which resulted to the so called Injury Data Base hosted by the EC.

Idiopathic inflammatory myopathies overlapping with systemic diseases

PubMed Central

Lepreux, Sébastien; Hainfellner, Johannes A.; Vital, Anne

2018-01-01

A muscle biopsy is currently requested to assess the diagnosis of an idiopathic inflammatory myopathy overlapping with a systemic disease. During the past few years, the classification of inflammatory myopathy subtypes has been revisited progressively on the basis of correlations between clinical phenotypes, autoantibodies and histological data. Several syndromic entities are now more clearly defined, and the aim of the present review is to clarify the contribution of muscle biopsy in a setting of idiopathic inflammatory myopathies overlapping with systemic diseases. PMID:29154752

Scoliosis in Patients with Severe Cerebral Palsy: Three Different Courses in Adolescents.

PubMed

Oda, Yoshiaki; Takigawa, Tomoyuki; Sugimoto, Yoshihisa; Tanaka, Masato; Akazawa, Hirofumi; Ozaki, Toshifumi

2017-04-01

Patients with cerebral palsy (CP) frequently present with scoliosis; however, the pattern of curve progression is difficult to predict. We aimed to clarify the natural course of the progression of scoliosis and to identify scoliosis predictors. This was a retrospective, single-center, observational study. Total of 92 CP patients from Asahikawasou Ryouiku Iryou Center in Okayama, Japan were retrospectively analyzed. Cobb angle, presence of hip dislocation and pelvic obliquity, and Gross Motor Function Classification System (GMFCS) were investigated. Severe CP was defined as GMFCS level IV or V. The mean observation period was 10.7 years. Thirtyfour severe CP patients presented with scoliosis and were divided into 3 groups based on their clinical courses: severe, moderate and mild. The mean Cobb angles at the final follow-up were 129°, 53°, and 13° in the severe, moderate, and mild groups, respectively. The average progressions from 18 to 25 years were 2.7°/year, 0.7°/year, and 0.1°/year in the severe, moderate, and mild curve groups, respectively. We observed the natural course of scoliosis and identified 3 courses based on the Cobb angle at 15 and 18 years of age. This method of classification may help clinicians predict the patients' disease progression.

Hazard Classification of Household Chemical Products in Korea according to the Globally Harmonized System of Classification and labeling of Chemicals.

PubMed

Kim, Kyung-Hee; Song, Dae-Jong; Yu, Myeong-Hyun; Park, Yuon-Shin; Noh, Hye-Ran; Kim, Hae-Joon; Choi, Jae-Wook

2013-07-16

This study was conducted to review the validity of the need for the application of the Globally Harmonized System of Classification and Labeling of Chemicals (GHS) to household chemical products in Korea. The study also aimed to assess the severity of health and environmental hazards of household chemical products using the GHS. 135 products were classified as 'cleaning agents and polishing agents' and 98 products were classified as 'bleaches, disinfectants, and germicides.' The current status of carcinogenic classification of GHS and carcinogenicity was examined for 272 chemical substances contained in household chemical products by selecting the top 11 products for each of the product categories. In addition, the degree of toxicity was assessed through analysis of whether the standard of the Republic of Korea's regulations on household chemical products had been exceeded or not. According to GHS health and environmental hazards, "acute toxicity (oral)" was found to be the highest for two product groups, 'cleaning agents and polishing agents', and 'bleaches, disinfectants, and germicides' (result of classification of 233 household chemical products) at 37.8% and 52.0% respectively. In an analysis of carcinogenicity assuming a threshold of IARC 2B for the substances in household chemical products, we found 'cleaning agents and polishing agents' to contain 12 chemical substances and 'bleaches, disinfectants, and germicides' 11 chemical substances. Some of the household chemical products were found to have a high hazard level including acute toxicity and germ cell mutagenicity, carcinogenicity, and reproductive toxicity. Establishing a hazard information delivery system including the application of GHS to household chemical products in Korea is urgent as well.

Hazard Classification of Household Chemical Products in Korea according to the Globally Harmonized System of Classification and labeling of Chemicals

PubMed Central

2013-01-01

Objectives This study was conducted to review the validity of the need for the application of the Globally Harmonized System of Classification and Labeling of Chemicals (GHS) to household chemical products in Korea. The study also aimed to assess the severity of health and environmental hazards of household chemical products using the GHS. Methods 135 products were classified as ‘cleaning agents and polishing agents’ and 98 products were classified as ‘bleaches, disinfectants, and germicides.’ The current status of carcinogenic classification of GHS and carcinogenicity was examined for 272 chemical substances contained in household chemical products by selecting the top 11 products for each of the product categories. In addition, the degree of toxicity was assessed through analysis of whether the standard of the Republic of Korea’s regulations on household chemical products had been exceeded or not. Results According to GHS health and environmental hazards, “acute toxicity (oral)” was found to be the highest for two product groups, ‘cleaning agents and polishing agents’, and ‘bleaches, disinfectants, and germicides’ (result of classification of 233 household chemical products) at 37.8% and 52.0% respectively. In an analysis of carcinogenicity assuming a threshold of IARC 2B for the substances in household chemical products, we found ‘cleaning agents and polishing agents’ to contain 12 chemical substances and ‘bleaches, disinfectants, and germicides’ 11 chemical substances. Conclusion Some of the household chemical products were found to have a high hazard level including acute toxicity and germ cell mutagenicity, carcinogenicity, and reproductive toxicity. Establishing a hazard information delivery system including the application of GHS to household chemical products in Korea is urgent as well. PMID:24472347

Extraction of texture features with a multiresolution neural network

NASA Astrophysics Data System (ADS)

Lepage, Richard; Laurendeau, Denis; Gagnon, Roger A.

1992-09-01

Texture is an important surface characteristic. Many industrial materials such as wood, textile, or paper are best characterized by their texture. Detection of defaults occurring on such materials or classification for quality control anD matching can be carried out through careful texture analysis. A system for the classification of pieces of wood used in the furniture industry is proposed. This paper is concerned with a neural network implementation of the features extraction and classification components of the proposed system. Texture appears differently depending at which spatial scale it is observed. A complete description of a texture thus implies an analysis at several spatial scales. We propose a compact pyramidal representation of the input image for multiresolution analysis. The feature extraction system is implemented on a multilayer artificial neural network. Each level of the pyramid, which is a representation of the input image at a given spatial resolution scale, is mapped into a layer of the neural network. A full resolution texture image is input at the base of the pyramid and a representation of the texture image at multiple resolutions is generated by the feedforward pyramid structure of the neural network. The receptive field of each neuron at a given pyramid level is preprogrammed as a discrete Gaussian low-pass filter. Meaningful characteristics of the textured image must be extracted if a good resolving power of the classifier must be achieved. Local dominant orientation is the principal feature which is extracted from the textured image. Local edge orientation is computed with a Sobel mask at four orientation angles (multiple of (pi) /4). The resulting intrinsic image, that is, the local dominant orientation image, is fed to the texture classification neural network. The classification network is a three-layer feedforward back-propagation neural network.

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

Comparison of using single- or multi-polarimetric TerraSAR-X images for segmentation and classification of man-made maritime objects

NASA Astrophysics Data System (ADS)

Teutsch, Michael; Saur, Günter

2011-11-01

Spaceborne SAR imagery offers high capability for wide-ranging maritime surveillance especially in situations, where AIS (Automatic Identification System) data is not available. Therefore, maritime objects have to be detected and optional information such as size, orientation, or object/ship class is desired. In recent research work, we proposed a SAR processing chain consisting of pre-processing, detection, segmentation, and classification for single-polarimetric (HH) TerraSAR-X StripMap images to finally assign detection hypotheses to class "clutter", "non-ship", "unstructured ship", or "ship structure 1" (bulk carrier appearance) respectively "ship structure 2" (oil tanker appearance). In this work, we extend the existing processing chain and are now able to handle full-polarimetric (HH, HV, VH, VV) TerraSAR-X data. With the possibility of better noise suppression using the different polarizations, we slightly improve both the segmentation and the classification process. In several experiments we demonstrate the potential benefit for segmentation and classification. Precision of size and orientation estimation as well as correct classification rates are calculated individually for single- and quad-polarization and compared to each other.

A comparison of outcomes according to different diagnostic systems for delirium (DSM-5, DSM-IV, CAM, and DRS-R98).

PubMed

Adamis, Dimitrios; Meagher, David; Rooney, Siobhan; Mulligan, Owen; McCarthy, Geraldine

2018-04-01

ABSTRACTStudies indicate that DSM-5 criteria for delirium are relatively restrictive, and identify different cases of delirium compared with previous systems. We evaluate four outcomes of delirium (mortality, length of hospital stay, institutionalization, and cognitive improvement) in relation to delirium defined by different DSM classification systems.Prospective, longitudinal study of patients aged 70+ admitted to medical wards of a general hospital. Participants were assessed up to a maximum of four times during two weeks, using DSM-5 and DSM-IV criteria, DRS-R98 and CAM scales as proxies for DSM III-R and DSM III.Of the 200 assessed patients (mean age 81.1, SD = 6.5; and 50% female) during hospitalization, delirium was identified in 41 (20.5%) using DSM-5, 45 (22.5%) according to DSM-IV, 46 (23%) with CAM positive, and 37 (18.5%) with DRS-R98 severity score >15. Mortality was significantly associated with delirium according to any classification system, but those identified with DSM-5 were at greater risk. Length of stay was significantly longer for those with DSM-IV delirium. Discharge to a care home was associated only with DRS-R98 defined delirium. Cognitive improvement was only associated with CAM and DSM-IV. Different classification systems for delirium identify populations with different outcomes.

Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification.

PubMed

Ramírez, J; Górriz, J M; Segovia, F; Chaves, R; Salas-Gonzalez, D; López, M; Alvarez, I; Padilla, P

2010-03-19

This letter shows a computer aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The proposed method is based on partial least squares (PLS) regression model and a random forest (RF) predictor. The challenge of the curse of dimensionality is addressed by reducing the large dimensionality of the input data by downscaling the SPECT images and extracting score features using PLS. A RF predictor then forms an ensemble of classification and regression tree (CART)-like classifiers being its output determined by a majority vote of the trees in the forest. A baseline principal component analysis (PCA) system is also developed for reference. The experimental results show that the combined PLS-RF system yields a generalization error that converges to a limit when increasing the number of trees in the forest. Thus, the generalization error is reduced when using PLS and depends on the strength of the individual trees in the forest and the correlation between them. Moreover, PLS feature extraction is found to be more effective for extracting discriminative information from the data than PCA yielding peak sensitivity, specificity and accuracy values of 100%, 92.7%, and 96.9%, respectively. Moreover, the proposed CAD system outperformed several other recently developed AD CAD systems. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

A Hilbert transform-based smart sensor for detection, classification, and quantification of power quality disturbances.

PubMed

Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A; Romero-Troncoso, Rene J; Osornio-Rios, Roque A

2013-04-25

Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System.

PubMed

Lesko, Mehdi M; Woodford, Maralyn; White, Laura; O'Brien, Sarah J; Childs, Charmaine; Lecky, Fiona E

2010-08-06

The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data.

Using Abbreviated Injury Scale (AIS) codes to classify Computed Tomography (CT) features in the Marshall System

PubMed Central

2010-01-01

Background The purpose of Abbreviated Injury Scale (AIS) is to code various types of Traumatic Brain Injuries (TBI) based on their anatomical location and severity. The Marshall CT Classification is used to identify those subgroups of brain injured patients at higher risk of deterioration or mortality. The purpose of this study is to determine whether and how AIS coding can be translated to the Marshall Classification Methods Initially, a Marshall Class was allocated to each AIS code through cross-tabulation. This was agreed upon through several discussion meetings with experts from both fields (clinicians and AIS coders). Furthermore, in order to make this translation possible, some necessary assumptions with regards to coding and classification of mass lesions and brain swelling were essential which were all approved and made explicit. Results The proposed method involves two stages: firstly to determine all possible Marshall Classes which a given patient can attract based on allocated AIS codes; via cross-tabulation and secondly to assign one Marshall Class to each patient through an algorithm. Conclusion This method can be easily programmed in computer softwares and it would enable future important TBI research programs using trauma registry data. PMID:20691038

Review of medication errors that are new or likely to occur more frequently with electronic medication management systems.

PubMed

Van de Vreede, Melita; McGrath, Anne; de Clifford, Jan

2018-05-14

Objective. The aim of the present study was to identify and quantify medication errors reportedly related to electronic medication management systems (eMMS) and those considered likely to occur more frequently with eMMS. This included developing a new classification system relevant to eMMS errors. Methods. Eight Victorian hospitals with eMMS participated in a retrospective audit of reported medication incidents from their incident reporting databases between May and July 2014. Site-appointed project officers submitted deidentified incidents they deemed new or likely to occur more frequently due to eMMS, together with the Incident Severity Rating (ISR). The authors reviewed and classified incidents. Results. There were 5826 medication-related incidents reported. In total, 93 (47 prescribing errors, 46 administration errors) were identified as new or potentially related to eMMS. Only one ISR2 (moderate) and no ISR1 (severe or death) errors were reported, so harm to patients in this 3-month period was minimal. The most commonly reported error types were 'human factors' and 'unfamiliarity or training' (70%) and 'cross-encounter or hybrid system errors' (22%). Conclusions. Although the results suggest that the errors reported were of low severity, organisations must remain vigilant to the risk of new errors and avoid the assumption that eMMS is the panacea to all medication error issues. What is known about the topic? eMMS have been shown to reduce some types of medication errors, but it has been reported that some new medication errors have been identified and some are likely to occur more frequently with eMMS. There are few published Australian studies that have reported on medication error types that are likely to occur more frequently with eMMS in more than one organisation and that include administration and prescribing errors. What does this paper add? This paper includes a new simple classification system for eMMS that is useful and outlines the most commonly reported incident types and can inform organisations and vendors on possible eMMS improvements. The paper suggests a new classification system for eMMS medication errors. What are the implications for practitioners? The results of the present study will highlight to organisations the need for ongoing review of system design, refinement of workflow issues, staff education and training and reporting and monitoring of errors.

[Evaluation of the course of chronic obstructive lung diseases according to the classifications of the European Respiratory Society and the Global Initiative on Chronic Obstructive Lung Disease].

PubMed

Nefedov, V B; Shergina, E A; Popova, L A

2006-01-01

In 91 patients with chronic obstructive lung disease (COLD), the severity of this disease according to the Classifications of the European Respiratory Society (ERS) and the Global Initiative on Chronic Obstructive Lung Disease (GOLD) was compared with that of pulmonary dysfunction according to the data of a comprehensive study, involving the determination of bronchial patency, lung volumes, capacities, and gas-exchange function. This follows that the ERS and GOLD classifications are to be positively appraised as they provide an eligible group of patients for clinical practice in terms of the severity of pulmonary dysfunction and that of COLD. However, the concomitant clinical use of both classifications cannot be regarded as justifiable due to that there are differences in the number of detectable grades (stages) of COLD and borderline (COLD differentiating grades (stages) values of EFV1). In this connection, both classifications have approximately equally significant merits and shortcomings and it is practically impossible to give preference to one of them as the best one. The optimal way out of the established situation is to develop a new (improved) classification of the severity of COLD on the bases of these two existing classifications.

Lava Morphology Classification of a Fast-Spreading Ridge Using Deep-Towed Sonar Data: East Pacific Rise

NASA Astrophysics Data System (ADS)

Meyer, J.; White, S.

2005-05-01

Classification of lava morphology on a regional scale contributes to the understanding of the distribution and extent of lava flows at a mid-ocean ridge. Seafloor classification is essential to understand the regional undersea environment at midocean ridges. In this study, the development of a classification scheme is found to identify and extract textural patterns of different lava morphologies along the East Pacific Rise using DSL-120 side-scan and ARGO camera imagery. Application of an accurate image classification technique to side-scan sonar allows us to expand upon the locally available visual ground reference data to make the first comprehensive regional maps of small-scale lava morphology present at a mid-ocean ridge. The submarine lava morphologies focused upon in this study; sheet flows, lobate flows, and pillow flows; have unique textures. Several algorithms were applied to the sonar backscatter intensity images to produce multiple textural image layers useful in distinguishing the different lava morphologies. The intensity and spatially enhanced images were then combined and applied to a hybrid classification technique. The hybrid classification involves two integrated classifiers, a rule-based expert system classifier and a machine learning classifier. The complementary capabilities of the two integrated classifiers provided a higher accuracy of regional seafloor classification compared to using either classifier alone. Once trained, the hybrid classifier can then be applied to classify neighboring images with relative ease. This classification technique has been used to map the lava morphology distribution and infer spatial variability of lava effusion rates along two segments of the East Pacific Rise, 17 deg S and 9 deg N. Future use of this technique may also be useful for attaining temporal information. Repeated documentation of morphology classification in this dynamic environment can be compared to detect regional seafloor change.

A new precipitation and drought climatology based on weather patterns

PubMed Central

Fowler, Hayley J.; Kilsby, Christopher G.; Neal, Robert

2017-01-01

ABSTRACT Weather‐pattern, or weather‐type, classifications are a valuable tool in many applications as they characterize the broad‐scale atmospheric circulation over a given region. This study analyses the aspects of regional UK precipitation and meteorological drought climatology with respect to a new set of objectively defined weather patterns. These new patterns are currently being used by the Met Office in several probabilistic forecasting applications driven by ensemble forecasting systems. Weather pattern definitions and daily occurrences are mapped to Lamb weather types (LWTs), and parallels between the two classifications are drawn. Daily precipitation distributions are associated with each weather pattern and LWT. Standardized precipitation index (SPI) and drought severity index (DSI) series are calculated for a range of aggregation periods and seasons. Monthly weather‐pattern frequency anomalies are calculated for SPI wet and dry periods and for the 5% most intense DSI‐based drought months. The new weather‐pattern definitions and daily occurrences largely agree with their respective LWTs, allowing comparison between the two classifications. There is also broad agreement between weather pattern and LWT changes in frequencies. The new data set is shown to be adequate for precipitation‐based analyses in the UK, although a smaller set of clustered weather patterns is not. Furthermore, intra‐pattern precipitation variability is lower in the new classification compared to the LWTs, which is an advantage in this context. Six of the new weather patterns are associated with drought over the entire UK, with several other patterns linked to regional drought. It is demonstrated that the new data set of weather patterns offers a new opportunity for classification‐based analyses in the UK. PMID:29456290

A hazard and risk classification system for catastrophic rock slope failures in Norway

NASA Astrophysics Data System (ADS)

Hermanns, R.; Oppikofer, T.; Anda, E.; Blikra, L. H.; Böhme, M.; Bunkholt, H.; Dahle, H.; Devoli, G.; Eikenæs, O.; Fischer, L.; Harbitz, C. B.; Jaboyedoff, M.; Loew, S.; Yugsi Molina, F. X.

2012-04-01

The Geological Survey of Norway carries out systematic geologic mapping of potentially unstable rock slopes in Norway that can cause a catastrophic failure. As catastrophic failure we describe failures that involve substantial fragmentation of the rock mass during run-out and that impact an area larger than that of a rock fall (shadow angle of ca. 28-32° for rock falls). This includes therefore rock slope failures that lead to secondary effects, such as a displacement wave when impacting a water body or damming of a narrow valley. Our systematic mapping revealed more than 280 rock slopes with significant postglacial deformation, which might represent localities of large future rock slope failures. This large number necessitates prioritization of follow-up activities, such as more detailed investigations, periodic monitoring and permanent monitoring and early-warning. In the past hazard and risk were assessed qualitatively for some sites, however, in order to compare sites so that political and financial decisions can be taken, it was necessary to develop a quantitative hazard and risk classification system. A preliminary classification system was presented and discussed with an expert group of Norwegian and international experts and afterwards adapted following their recommendations. This contribution presents the concept of this final hazard and risk classification that should be used in Norway in the upcoming years. Historical experience and possible future rockslide scenarios in Norway indicate that hazard assessment of large rock slope failures must be scenario-based, because intensity of deformation and present displacement rates, as well as the geological structures activated by the sliding rock mass can vary significantly on a given slope. In addition, for each scenario the run-out of the rock mass has to be evaluated. This includes the secondary effects such as generation of displacement waves or landslide damming of valleys with the potential of later outburst floods. It became obvious that large rock slope failures cannot be evaluated on a slope scale with frequency analyses of historical and prehistorical events only, as multiple rockslides have occurred within one century on a single slope that prior to the recent failures had been inactive for several thousand years. In addition, a systematic analysis on temporal distribution indicates that rockslide activity following deglaciation after the Last Glacial Maximum has been much higher than throughout the Holocene. Therefore the classification system has to be based primarily on the geological conditions on the deforming slope and on the deformation rates and only to a lesser weight on a frequency analyses. Our hazard classification therefore is primarily based on several criteria: 1) Development of the back-scarp, 2) development of the lateral release surfaces, 3) development of the potential basal sliding surface, 4) morphologic expression of the basal sliding surface, 5) kinematic feasibility tests for different displacement mechanisms, 6) landslide displacement rates, 7) change of displacement rates (acceleration), 8) increase of rockfall activity on the unstable rock slope, 9) Presence post-glacial events of similar size along the affected slope and its vicinity. For each of these criteria several conditions are possible to choose from (e.g. different velocity classes for the displacement rate criterion). A score is assigned to each condition and the sum of all scores gives the total susceptibility score. Since many of these observations are somewhat uncertain, the classification system is organized in a decision tree where probabilities can be assigned to each condition. All possibilities in the decision tree are computed and the individual probabilities giving the same total score are summed. Basic statistics show the minimum and maximum total scores of a scenario, as well as the mean and modal value. The final output is a cumulative frequency distribution of the susceptibility scores that can be divided into several classes, which are interpreted as susceptibility classes (very high, high, medium, low, and very low). Today the Norwegian Planning and Building Act uses hazard classes with annual probabilities of impact on buildings producing damages (<1/100, <1/1000, <1/5000 and zero for critical buildings). However, up to now there is not enough scientific knowledge to predict large rock slope failures in these strict classes. Therefore, the susceptibility classes will be matched with the hazard classes from the Norwegian Building Act (e.g. very high susceptibility represents the hazard class with annual probability >1/100). The risk analysis focuses on the potential fatalities of a worst case rock slide scenario and its secondary effects only and is done in consequence classes with a decimal logarithmic scale. However we recommend for all high risk objects that municipalities carry out detailed risk analyses. Finally, the hazard and risk classification system will give recommendations where surveillance in form of continuous 24/7 monitoring systems coupled with early-warning systems (high risk class) or periodic monitoring (medium risk class) should be carried out. These measures are understood as to reduce the risk of life loss due to a rock slope failure close to 0 as population can be evacuated on time if a change of stability situation occurs. The final hazard and risk classification for all potentially unstable rock slopes in Norway, including all data used for its classification will be published within the national landslide database (available on www.skrednett.no).

The groningen laryngomalacia classification system--based on systematic review and dynamic airway changes.

PubMed

van der Heijden, Martijn; Dikkers, Frederik G; Halmos, Gyorgy B

2015-12-01

Laryngomalacia is the most common cause of dyspnea and stridor in newborn infants. Laryngomalacia is a dynamic change of the upper airway based on abnormally pliable supraglottic structures, which causes upper airway obstruction. In the past, different classification systems have been introduced. Until now no classification system is widely accepted and applied. Our goal is to provide a simple and complete classification system based on systematic literature search and our experiences. Retrospective cohort study with literature review. All patients with laryngomalacia under the age of 5 at time of diagnosis were included. Photo and video documentation was used to confirm diagnosis and characteristics of dynamic airway change. Outcome was compared with available classification systems in literature. Eighty-five patients were included. In contrast to other classification systems, only three typical different dynamic changes have been identified in our series. Two existing classification systems covered 100% of our findings, but there was an unnecessary overlap between different types in most of the systems. Based on our finding, we propose a new a classification system for laryngomalacia, which is purely based on dynamic airway changes. The groningen laryngomalacia classification is a new, simplified classification system with three types, based on purely dynamic laryngeal changes, tested in a tertiary referral center: Type 1: inward collapse of arytenoids cartilages, Type 2: medial displacement of aryepiglottic folds, and Type 3: posterocaudal displacement of epiglottis against the posterior pharyngeal wall. © 2015 Wiley Periodicals, Inc.

Handling Imbalanced Data Sets in Multistage Classification

NASA Astrophysics Data System (ADS)

López, M.

Multistage classification is a logical approach, based on a divide-and-conquer solution, for dealing with problems with a high number of classes. The classification problem is divided into several sequential steps, each one associated to a single classifier that works with subgroups of the original classes. In each level, the current set of classes is split into smaller subgroups of classes until they (the subgroups) are composed of only one class. The resulting chain of classifiers can be represented as a tree, which (1) simplifies the classification process by using fewer categories in each classifier and (2) makes it possible to combine several algorithms or use different attributes in each stage. Most of the classification algorithms can be biased in the sense of selecting the most populated class in overlapping areas of the input space. This can degrade a multistage classifier performance if the training set sample frequencies do not reflect the real prevalence in the population. Several techniques such as applying prior probabilities, assigning weights to the classes, or replicating instances have been developed to overcome this handicap. Most of them are designed for two-class (accept-reject) problems. In this article, we evaluate several of these techniques as applied to multistage classification and analyze how they can be useful for astronomy. We compare the results obtained by classifying a data set based on Hipparcos with and without these methods.

Severity and duration of diabetic foot ulcer (DFU) before seeking care as predictors of healing time: A retrospective cohort study

PubMed Central

Iversen, Marjolein M.; Igland, Jannicke; Østbye, Truls; Graue, Marit; Skeie, Svein; Wu, Bei; Rokne, Berit

2017-01-01

Objectives To investigate whether A) duration of ulcer before start of treatment in specialist health care, and B) severity of ulcer according to University of Texas classification system (UT) at start of treatment (baseline), are independent predictors of healing time. Methods This retrospective cohort study, based on electronic medical record data, included 105 patients from two outpatient clinics in Western Norway with a new diabetic foot ulcer during 2009–2011. The associations of duration of ulcer and ulcer severity with healing time were assessed using cumulative incidence curves and subdistribution hazard ratio estimated using competing risk regression with adjustment for potential confounders. Results Of the 105 participants, 45.7% achieved ulcer healing, 36.2% underwent amputations, 9.5% died before ulcer healing and 8.5% were lost to follow-up. Patients who were referred to specialist health care by a general practitioner ≥ 52 days after ulcer onset had a 58% (SHR 0.42, CI 0.18–0.98) decreased healing rate compared to patients who were referred earlier, in the adjusted model. High severity (grade 2/3, stage C/D) according to the UT classification system was associated with a decreased healing rate compared to low severity (grade1, stage A/B or grade 2, stage A) with SHR (95% CI) equal to 0.14 (0.05–0.43) after adjustment for referral time and other potential confounders. Conclusion Early detection and referral by both the patient and general practitioner are crucial for optimal foot ulcer healing. Ulcer grade and severity are also important predictors for healing time, and early screening to assess the severity and initiation of prompt treatment is important. PMID:28498862

Should Age at Diagnosis Be Included as an Additional Variable in the Risk of Recurrence Classification System in Patients with Differentiated Thyroid Cancer.

PubMed

Pitoia, Fabián; Jerkovich, Fernando; Smulever, Anabella; Brenta, Gabriela; Bueno, Fernanda; Cross, Graciela

2017-07-01

To evaluate the influence of age at diagnosis on the frequency of structural incomplete response (SIR) according to the modified risk of recurrence (RR) staging system from the American Thyroid Association guidelines. We performed a retrospective analysis of 268 patients with differentiated thyroid cancer (DTC) followed up for at least 3 years after initial treatment (total thyroidectomy and remnant ablation). The median follow-up in the whole cohort was 74.3 months (range: 36.1-317.9) and the median age at diagnosis was 45.9 years (range: 18-87). The association between age at diagnosis and the initial and final response to treatment was assessed with analysis of variance (ANOVA). Patients were also divided into several groups considering age younger and older than 40, 50, and 60 years. Age at diagnosis was not associated with either an initial or final statistically significant different SIR to treatment ( p = 0.14 and p = 0.58, respectively). Additionally, we did not find any statistically significant differences when the percentages of SIR considering the classification of RR were compared between different groups of patients by using several age cutoffs. When patients are correctly risk stratified, it seems that age at diagnosis is not involved in the frequency of having a SIR at the initial evaluation or at the final follow-up, so it should not be included as an additional variable to be considered in the RR classifications.

Fusion of multiple quadratic penalty function support vector machines (QPFSVM) for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-08-01

The high-resolution sonar is one of the principal sensors used by the Navy to detect and classify sea mines in minehunting operations. For such sonar systems, substantial effort has been devoted to the development of automated detection and classification (D/C) algorithms. These have been spurred by several factors including (1) aids for operators to reduce work overload, (2) more optimal use of all available data, and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and man-made clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while still maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms have been studied. We refer to this as Algorithm Fusion. The results have been remarkable, including reliable robustness to new environments. The Quadratic Penalty Function Support Vector Machine (QPFSVM) algorithm to aid in the automated detection and classification of sea mines is introduced in this paper. The QPFSVM algorithm is easy to train, simple to implement, and robust to feature space dimension. Outputs of successive SVM algorithms are cascaded in stages (fused) to improve the Probability of Classification (Pc) and reduce the number of false alarms. Even though our experience has been gained in the area of sea mine detection and classification, the principles described herein are general and can be applied to fusion of any D/C problem (e.g., automated medical diagnosis or automatic target recognition for ballistic missile defense).

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

Radiographic readings for asbestosis: misuse of science--validation of the ILO classification.

PubMed

Miller, Albert

2007-01-01

Radiographic readings for pneumoconiosis (both asbestosis and silicosis), even those using the International Labour Office (ILO) Classification, have received widespread negative coverage in the media and strong judicial rebuke. The medical literature over the past 90 years was reviewed for the relationships between radiographic severity (standardized as the ILO profusion score) and indices of exposure to silica or asbestos, tissue burden of silica particles or asbestos fibers, histologic fibrosis, various measurements of pulmonary function and mortality. Evidence from many different disciplines has demonstrated that the ILO profusion score correlates with occupational exposure, dust burden in the lung, histologic fibrosis and, more recently, with physiologic impairment and mortality. The ILO Classification has therefore been validated as a scientific tool. Its fraudulent misuse by "hired-gun" physicians, attorneys and elements of the compensation system to falsify claims of asbestosis and/or silicosis (often in the same claimant) must be condemned. (c) 2006 Wiley-Liss, Inc.

Classification of passive auditory event-related potentials using discriminant analysis and self-organizing feature maps.

PubMed

Schönweiler, R; Wübbelt, P; Tolloczko, R; Rose, C; Ptok, M

2000-01-01

Discriminant analysis (DA) and self-organizing feature maps (SOFM) were used to classify passively evoked auditory event-related potentials (ERP) P(1), N(1), P(2) and N(2). Responses from 16 children with severe behavioral auditory perception deficits, 16 children with marked behavioral auditory perception deficits, and 14 controls were examined. Eighteen ERP amplitude parameters were selected for examination of statistical differences between the groups. Different DA methods and SOFM configurations were trained to the values. SOFM had better classification results than DA methods. Subsequently, measures on another 37 subjects that were unknown for the trained SOFM were used to test the reliability of the system. With 10-dimensional vectors, reliable classifications were obtained that matched behavioral auditory perception deficits in 96%, implying central auditory processing disorder (CAPD). The results also support the assumption that CAPD includes a 'non-peripheral' auditory processing deficit. Copyright 2000 S. Karger AG, Basel.

Systemic characterization and evaluation of particle packings as initial sets for discrete element simulations

NASA Astrophysics Data System (ADS)

Morfa, Carlos Recarey; Cortés, Lucía Argüelles; Farias, Márcio Muniz de; Morales, Irvin Pablo Pérez; Valera, Roberto Roselló; Oñate, Eugenio

2018-07-01

A methodology that comprises several characterization properties for particle packings is proposed in this paper. The methodology takes into account factors such as dimension and shape of particles, space occupation, homogeneity, connectivity and isotropy, among others. This classification and integration of several properties allows to carry out a characterization process to systemically evaluate the particle packings in order to guarantee the quality of the initial meshes in discrete element simulations, in both the micro- and the macroscales. Several new properties were created, and improvements in existing ones are presented. Properties from other disciplines were adapted to be used in the evaluation of particle systems. The methodology allows to easily characterize media at the level of the microscale (continuous geometries—steels, rocks microstructures, etc., and discrete geometries) and the macroscale. A global, systemic and integral system for characterizing and evaluating particle sets, based on fuzzy logic, is presented. Such system allows researchers to have a unique evaluation criterion based on the aim of their research. Examples of applications are shown.

Systemic characterization and evaluation of particle packings as initial sets for discrete element simulations

NASA Astrophysics Data System (ADS)

Morfa, Carlos Recarey; Cortés, Lucía Argüelles; Farias, Márcio Muniz de; Morales, Irvin Pablo Pérez; Valera, Roberto Roselló; Oñate, Eugenio

2017-10-01

A methodology that comprises several characterization properties for particle packings is proposed in this paper. The methodology takes into account factors such as dimension and shape of particles, space occupation, homogeneity, connectivity and isotropy, among others. This classification and integration of several properties allows to carry out a characterization process to systemically evaluate the particle packings in order to guarantee the quality of the initial meshes in discrete element simulations, in both the micro- and the macroscales. Several new properties were created, and improvements in existing ones are presented. Properties from other disciplines were adapted to be used in the evaluation of particle systems. The methodology allows to easily characterize media at the level of the microscale (continuous geometries—steels, rocks microstructures, etc., and discrete geometries) and the macroscale. A global, systemic and integral system for characterizing and evaluating particle sets, based on fuzzy logic, is presented. Such system allows researchers to have a unique evaluation criterion based on the aim of their research. Examples of applications are shown.

Physiotherapy movement based classification approaches to low back pain: comparison of subgroups through review and developer/expert survey.

PubMed

Karayannis, Nicholas V; Jull, Gwendolen A; Hodges, Paul W

2012-02-20

Several classification schemes, each with its own philosophy and categorizing method, subgroup low back pain (LBP) patients with the intent to guide treatment. Physiotherapy derived schemes usually have a movement impairment focus, but the extent to which other biological, psychological, and social factors of pain are encompassed requires exploration. Furthermore, within the prevailing 'biological' domain, the overlap of subgrouping strategies within the orthopaedic examination remains unexplored. The aim of this study was "to review and clarify through developer/expert survey, the theoretical basis and content of physical movement classification schemes, determine their relative reliability and similarities/differences, and to consider the extent of incorporation of the bio-psycho-social framework within the schemes". A database search for relevant articles related to LBP and subgrouping or classification was conducted. Five dominant movement-based schemes were identified: Mechanical Diagnosis and Treatment (MDT), Treatment Based Classification (TBC), Pathoanatomic Based Classification (PBC), Movement System Impairment Classification (MSI), and O'Sullivan Classification System (OCS) schemes. Data were extracted and a survey sent to the classification scheme developers/experts to clarify operational criteria, reliability, decision-making, and converging/diverging elements between schemes. Survey results were integrated into the review and approval obtained for accuracy. Considerable diversity exists between schemes in how movement informs subgrouping and in the consideration of broader neurosensory, cognitive, emotional, and behavioural dimensions of LBP. Despite differences in assessment philosophy, a common element lies in their objective to identify a movement pattern related to a pain reduction strategy. Two dominant movement paradigms emerge: (i) loading strategies (MDT, TBC, PBC) aimed at eliciting a phenomenon of centralisation of symptoms; and (ii) modified movement strategies (MSI, OCS) targeted towards documenting the movement impairments associated with the pain state. Schemes vary on: the extent to which loading strategies are pursued; the assessment of movement dysfunction; and advocated treatment approaches. A biomechanical assessment predominates in the majority of schemes (MDT, PBC, MSI), certain psychosocial aspects (fear-avoidance) are considered in the TBC scheme, certain neurophysiologic (central versus peripherally mediated pain states) and psychosocial (cognitive and behavioural) aspects are considered in the OCS scheme.

Comparing Features for Classification of MEG Responses to Motor Imagery

PubMed Central

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Background Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. Methods MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio—spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. Results The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. Conclusions We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system. PMID:27992574

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

42 CFR 412.10 - Changes in the DRG classification system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Changes in the DRG classification system. 412.10... § 412.10 Changes in the DRG classification system. (a) General rule. CMS issues changes in the DRG classification system in a Federal Register notice at least annually. Except as specified in paragraphs (c) and...

Inter-Relationships of Functional Status in Cerebral Palsy: Analyzing Gross Motor Function, Manual Ability, and Communication Function Classification Systems in Children

ERIC Educational Resources Information Center

Hidecker, Mary Jo Cooley; Ho, Nhan Thi; Dodge, Nancy; Hurvitz, Edward A.; Slaughter, Jaime; Workinger, Marilyn Seif; Kent, Ray D.; Rosenbaum, Peter; Lenski, Madeleine; Messaros, Bridget M.; Vanderbeek, Suzette B.; Deroos, Steven; Paneth, Nigel

2012-01-01

Aim: To investigate the relationships among the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) in children with cerebral palsy (CP). Method: Using questionnaires describing each scale, mothers reported GMFCS, MACS, and CFCS levels in 222…

Emerging insights into the molecular and cellular basis of glioblastoma

PubMed Central

Dunn, Gavin P.; Rinne, Mikael L.; Wykosky, Jill; Genovese, Giannicola; Quayle, Steven N.; Dunn, Ian F.; Agarwalla, Pankaj K.; Chheda, Milan G.; Campos, Benito; Wang, Alan; Brennan, Cameron; Ligon, Keith L.; Furnari, Frank; Cavenee, Webster K.; Depinho, Ronald A.; Chin, Lynda; Hahn, William C.

2012-01-01

Glioblastoma is both the most common and lethal primary malignant brain tumor. Extensive multiplatform genomic characterization has provided a higher-resolution picture of the molecular alterations underlying this disease. These studies provide the emerging view that “glioblastoma” represents several histologically similar yet molecularly heterogeneous diseases, which influences taxonomic classification systems, prognosis, and therapeutic decisions. PMID:22508724

New Metaphors for Organizing Data Could Change the Nature of Computers.

ERIC Educational Resources Information Center

Young, Jeffrey R.

1997-01-01

Based on the idea that the current framework for organizing electronic data does not take advantage of the mind's ability to make connections among disparate pieces of information, several projects at universities around the country are taking new approaches to classification and storage of vast amounts of computerized data. The new systems take…

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

PubMed

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

Correlation of the Rock Mass Rating (RMR) System with the Unified Soil Classification System (USCS): Introduction of the Weak Rock Mass Rating System (W-RMR)

NASA Astrophysics Data System (ADS)

Warren, Sean N.; Kallu, Raj R.; Barnard, Chase K.

2016-11-01

Underground gold mines in Nevada are exploiting increasingly deeper ore bodies comprised of weak to very weak rock masses. The Rock Mass Rating (RMR) classification system is widely used at underground gold mines in Nevada and is applicable in fair to good-quality rock masses, but is difficult to apply and loses reliability in very weak rock mass to soil-like material. Because very weak rock masses are transition materials that border engineering rock mass and soil classification systems, soil classification may sometimes be easier and more appropriate to provide insight into material behavior and properties. The Unified Soil Classification System (USCS) is the most likely choice for the classification of very weak rock mass to soil-like material because of its accepted use in tunnel engineering projects and its ability to predict soil-like material behavior underground. A correlation between the RMR and USCS systems was developed by comparing underground geotechnical RMR mapping to laboratory testing of bulk samples from the same locations, thereby assigning a numeric RMR value to the USCS classification that can be used in spreadsheet calculations and geostatistical analyses. The geotechnical classification system presented in this paper including a USCS-RMR correlation, RMR rating equations, and the Geo-Pick Strike Index is collectively introduced as the Weak Rock Mass Rating System (W-RMR). It is the authors' hope that this system will aid in the classification of weak rock masses and more usable design tools based on the RMR system. More broadly, the RMR-USCS correlation and the W-RMR system help define the transition between engineering soil and rock mass classification systems and may provide insight for geotechnical design in very weak rock masses.

Overweight and Obesity Prevalence Among School-Aged Nunavik Inuit Children According to Three Body Mass Index Classification Systems.

PubMed

Medehouenou, Thierry Comlan Marc; Ayotte, Pierre; St-Jean, Audray; Meziou, Salma; Roy, Cynthia; Muckle, Gina; Lucas, Michel

2015-07-01

Little is known about the suitability of three commonly used body mass index (BMI) classification system for Indigenous children. This study aims to estimate overweight and obesity prevalence among school-aged Nunavik Inuit children according to International Obesity Task Force (IOTF), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO) BMI classification systems, to measure agreement between those classification systems, and to investigate whether BMI status as defined by these classification systems is associated with levels of metabolic and inflammatory biomarkers. Data were collected on 290 school-aged children (aged 8-14 years; 50.7% girls) from the Nunavik Child Development Study with data collected in 2005-2010. Anthropometric parameters were measured and blood sampled. Participants were classified as normal weight, overweight, and obese according to BMI classification systems. Weighted kappa (κw) statistics assessed agreement between different BMI classification systems, and multivariate analysis of variance ascertained their relationship with metabolic and inflammatory biomarkers. The combined prevalence rate of overweight/obesity was 26.9% (with 6.6% obesity) with IOTF, 24.1% (11.0%) with CDC, and 40.4% (12.8%) with WHO classification systems. Agreement was the highest between IOTF and CDC (κw = .87) classifications, and substantial for IOTF and WHO (κw = .69) and for CDC and WHO (κw = .73). Insulin and high-sensitivity C-reactive protein plasma levels were significantly higher from normal weight to obesity, regardless of classification system. Among obese subjects, higher insulin level was observed with IOTF. Compared with other systems, IOTF classification appears to be more specific to identify overweight and obesity in Inuit children. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Stroke subtyping for genetic association studies? A comparison of the CCS and TOAST classifications.

PubMed

Lanfranconi, Silvia; Markus, Hugh S

2013-12-01

A reliable and reproducible classification system of stroke subtype is essential for epidemiological and genetic studies. The Causative Classification of Stroke system is an evidence-based computerized algorithm with excellent inter-rater reliability. It has been suggested that, compared to the Trial of ORG 10172 in Acute Stroke Treatment classification, it increases the proportion of cases with defined subtype that may increase power in genetic association studies. We compared Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications in a large cohort of well-phenotyped stroke patients. Six hundred ninety consecutively recruited patients with first-ever ischemic stroke were classified, using review of clinical data and original imaging, according to the Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system classifications. There was excellent agreement subtype assigned by between Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke system (kappa = 0·85). The agreement was excellent for the major individual subtypes: large artery atherosclerosis kappa = 0·888, small-artery occlusion kappa = 0·869, cardiac embolism kappa = 0·89, and undetermined category kappa = 0·884. There was only moderate agreement (kappa = 0·41) for the subjects with at least two competing underlying mechanism. Thirty-five (5·8%) patients classified as undetermined by Trial of ORG 10172 in Acute Stroke Treatment were assigned to a definite subtype by Causative Classification of Stroke system. Thirty-two subjects assigned to a definite subtype by Trial of ORG 10172 in Acute Stroke Treatment were classified as undetermined by Causative Classification of Stroke system. There is excellent agreement between classification using Trial of ORG 10172 in Acute Stroke Treatment and Causative Classification of Stroke systems but no evidence that Causative Classification of Stroke system reduced the proportion of patients classified to undetermined subtypes. The excellent inter-rater reproducibility and web-based semiautomated nature make Causative Classification of Stroke system suitable for multicenter studies, but the benefit of reclassifying cases already classified using the Trial of ORG 10172 in Acute Stroke Treatment system on existing databases is likely to be small. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

PubMed

Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

2017-08-11

The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

The revised dengue fever classification in German travelers: clinical manifestations and indicators for severe disease.

PubMed

Hoffmeister, B; Suttorp, N; Zoller, T

2015-02-01

The number of dengue cases imported to Germany has increased significantly in recent years. Among returning travelers, dengue is now a frequent cause of hospitalization. The aim of this study was to determine the proportion of patients with severe disease hospitalized in a European, non-endemic country applying the revised 2009 WHO classification system and to determine predictors of severe disease. A retrospective single-center analysis of clinical data from 56 patients, 31 (55 %) women and 25 (45 %) men, between 14 and 70 years of age treated in a tertiary care hospital between 1996 and 2010 was conducted. Thirty-nine patients (69.6 %) presented with dengue fever without warning signs, 11 (19.6 %) with warning signs and 6 (10.7 %) with signs for severe dengue fever. Two patients (4 %) developed dengue shock syndrome. Non-European descent (p = 0.001), plasma protein level <6.5 mg/dl (p = 0.001), platelets <30/nl (p = 0.017) and activated partial thromboplastin time (aPTT) >44 s (p = 0.003) were associated with severe disease. A significant proportion of patients hospitalized with symptomatic imported dengue fever in Germany have evidence of severe disease. Simple routine laboratory parameters such as complete blood count, plasma protein level and aPTT are helpful tools for identifying adult patients at risk for severe disease.

A new hierarchical method for inter-patient heartbeat classification using random projections and RR intervals

PubMed Central

2014-01-01

Background The inter-patient classification schema and the Association for the Advancement of Medical Instrumentation (AAMI) standards are important to the construction and evaluation of automated heartbeat classification systems. The majority of previously proposed methods that take the above two aspects into consideration use the same features and classification method to classify different classes of heartbeats. The performance of the classification system is often unsatisfactory with respect to the ventricular ectopic beat (VEB) and supraventricular ectopic beat (SVEB). Methods Based on the different characteristics of VEB and SVEB, a novel hierarchical heartbeat classification system was constructed. This was done in order to improve the classification performance of these two classes of heartbeats by using different features and classification methods. First, random projection and support vector machine (SVM) ensemble were used to detect VEB. Then, the ratio of the RR interval was compared to a predetermined threshold to detect SVEB. The optimal parameters for the classification models were selected on the training set and used in the independent testing set to assess the final performance of the classification system. Meanwhile, the effect of different lead configurations on the classification results was evaluated. Results Results showed that the performance of this classification system was notably superior to that of other methods. The VEB detection sensitivity was 93.9% with a positive predictive value of 90.9%, and the SVEB detection sensitivity was 91.1% with a positive predictive value of 42.2%. In addition, this classification process was relatively fast. Conclusions A hierarchical heartbeat classification system was proposed based on the inter-patient data division to detect VEB and SVEB. It demonstrated better classification performance than existing methods. It can be regarded as a promising system for detecting VEB and SVEB of unknown patients in clinical practice. PMID:24981916

Extensions to the Speech Disorders Classification System (SDCS)

ERIC Educational Resources Information Center

Shriberg, Lawrence D.; Fourakis, Marios; Hall, Sheryl D.; Karlsson, Heather B.; Lohmeier, Heather L.; McSweeny, Jane L.; Potter, Nancy L.; Scheer-Cohen, Alison R.; Strand, Edythe A.; Tilkens, Christie M.; Wilson, David L.

2010-01-01

This report describes three extensions to a classification system for paediatric speech sound disorders termed the Speech Disorders Classification System (SDCS). Part I describes a classification extension to the SDCS to differentiate motor speech disorders from speech delay and to differentiate among three sub-types of motor speech disorders.…

Phenomenology and classification of dystonia: a consensus update

PubMed Central

Albanese, Alberto; Bhatia, Kailash; Bressman, Susan B.; DeLong, Mahlon R.; Fahn, Stanley; Fung, Victor S.C.; Hallett, Mark; Jankovic, Joseph; Jinnah, H.A.; Klein, Christine; Lang, Anthony E.; Mink, Jonathan W.; Teller, Jan K.

2013-01-01

This report describes the consensus outcome of an international panel consisting of investigators with years of experience in this field that reviewed the definition and classification of dystonia. Agreement was obtained based on a consensus development methodology during three in-person meetings and manuscript review by mail. Dystonia is defined as a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements, postures, or both. Dystonic movements are typically patterned and twisting, and may be tremulous. Dystonia is often initiated or worsened by voluntary action and associated with overflow muscle activation. Dystonia is classified along two axes: clinical characteristics, including age at onset, body distribution, temporal pattern and associated features (additional movement disorders or neurological features), and etiology, which includes nervous system pathology and inheritance. The clinical characteristics fall into several specific dystonia syndromes that help to guide diagnosis and treatment. We provide here a new general definition of dystonia and propose a new classification. We encourage clinicians and researchers to use these innovative definition and classification and test them in the clinical setting on a variety of patients with dystonia. PMID:23649720

Classification and grading of muscle injuries: a narrative review

PubMed Central

Hamilton, Bruce; Valle, Xavier; Rodas, Gil; Til, Luis; Grive, Ricard Pruna; Rincon, Josep Antoni Gutierrez; Tol, Johannes L

2015-01-01

A limitation to the accurate study of muscle injuries and their management has been the lack of a uniform approach to the categorisation and grading of muscle injuries. The goal of this narrative review was to provide a framework from which to understand the historical progression of the classification and grading of muscle injuries. We reviewed the classification and grading of muscle injuries in the literature to critically illustrate the strengths, weaknesses, contradictions or controversies. A retrospective, citation-based methodology was applied to search for English language literature which evaluated or utilised a novel muscle classification or grading system. While there is an abundance of literature classifying and grading muscle injuries, it is predominantly expert opinion, and there remains little evidence relating any of the clinical or radiological features to an established pathology or clinical outcome. While the categorical grading of injury severity may have been a reasonable solution to a clinical challenge identified in the middle of the 20th century, it is time to recognise the complexity of the injury, cease trying to oversimplify it and to develop appropriately powered research projects to answer important questions. PMID:25394420

Neural network and wavelet average framing percentage energy for atrial fibrillation classification.

PubMed

Daqrouq, K; Alkhateeb, A; Ajour, M N; Morfeq, A

2014-03-01

ECG signals are an important source of information in the diagnosis of atrial conduction pathology. Nevertheless, diagnosis by visual inspection is a difficult task. This work introduces a novel wavelet feature extraction method for atrial fibrillation derived from the average framing percentage energy (AFE) of terminal wavelet packet transform (WPT) sub signals. Probabilistic neural network (PNN) is used for classification. The presented method is shown to be a potentially effective discriminator in an automated diagnostic process. The ECG signals taken from the MIT-BIH database are used to classify different arrhythmias together with normal ECG. Several published methods were investigated for comparison. The best recognition rate selection was obtained for AFE. The classification performance achieved accuracy 97.92%. It was also suggested to analyze the presented system in an additive white Gaussian noise (AWGN) environment; 55.14% for 0dB and 92.53% for 5dB. It was concluded that the proposed approach of automating classification is worth pursuing with larger samples to validate and extend the present study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Diagnostic Concordance between DSM-5 and ICD-10 Cannabis Use Disorders.

PubMed

Proctor, Steven L; Williams, Daniel C; Kopak, Albert M; Voluse, Andrew C; Connolly, Kevin M; Hoffmann, Norman G

2016-07-01

With the recent federal mandate that all U.S. health care settings transition to ICD-10 billing codes, empirical evidence is necessary to determine if the DSM-5 designations map to their respective ICD-10 diagnostic categories/billing codes. The present study examined the concordance between DSM-5 and ICD-10 cannabis use disorder diagnoses. Data were derived from routine clinical assessments of 6871 male and 801 female inmates recently admitted to a state prison system from 2000 to 2003. DSM-5 and ICD-10 diagnostic determinations were made from algorithms corresponding to the respective diagnostic formulations. Past 12-month prevalence rates of cannabis use disorders were comparable across classification systems. The vast majority of inmates with no DSM-5 diagnosis continued to have no diagnosis per the ICD-10, and a similar proportion with a DSM-5 severe diagnosis received an ICD-10 dependence diagnosis. Most of the variation in diagnostic classifications was accounted for by those with a DSM-5 moderate diagnosis in that approximately half of these cases received an ICD-10 dependence diagnosis while the remaining cases received a harmful use diagnosis. Although there appears to be a generally high level of agreement between diagnostic classification systems for those with no diagnosis or those evincing symptoms of a more severe condition, concordance between DSM-5 moderate and ICD-10 dependence diagnoses was poor. Additional research is warranted to determine the appropriateness and implications of the current DSM-5 coding guidelines regarding the assignment of an ICD-10 dependence code for those with a DSM-5 moderate diagnosis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of Danish dichotomous and BI-RADS classifications of mammographic density.

PubMed

Hodge, Rebecca; Hellmann, Sophie Sell; von Euler-Chelpin, My; Vejborg, Ilse; Andersen, Zorana Jovanovic

2014-06-01

In the Copenhagen mammography screening program from 1991 to 2001, mammographic density was classified either as fatty or mixed/dense. This dichotomous mammographic density classification system is unique internationally, and has not been validated before. To compare the Danish dichotomous mammographic density classification system from 1991 to 2001 with the density BI-RADS classifications, in an attempt to validate the Danish classification system. The study sample consisted of 120 mammograms taken in Copenhagen in 1991-2001, which tested false positive, and which were in 2012 re-assessed and classified according to the BI-RADS classification system. We calculated inter-rater agreement between the Danish dichotomous mammographic classification as fatty or mixed/dense and the four-level BI-RADS classification by the linear weighted Kappa statistic. Of the 120 women, 32 (26.7%) were classified as having fatty and 88 (73.3%) as mixed/dense mammographic density, according to Danish dichotomous classification. According to BI-RADS density classification, 12 (10.0%) women were classified as having predominantly fatty (BI-RADS code 1), 46 (38.3%) as having scattered fibroglandular (BI-RADS code 2), 57 (47.5%) as having heterogeneously dense (BI-RADS 3), and five (4.2%) as having extremely dense (BI-RADS code 4) mammographic density. The inter-rater variability assessed by weighted kappa statistic showed a substantial agreement (0.75). The dichotomous mammographic density classification system utilized in early years of Copenhagen's mammographic screening program (1991-2001) agreed well with the BI-RADS density classification system.

CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.

PubMed

Kumar, Shiu; Mamun, Kabir; Sharma, Alok

2017-12-01

Classification of electroencephalography (EEG) signals for motor imagery based brain computer interface (MI-BCI) is an exigent task and common spatial pattern (CSP) has been extensively explored for this purpose. In this work, we focused on developing a new framework for classification of EEG signals for MI-BCI. We propose a single band CSP framework for MI-BCI that utilizes the concept of tangent space mapping (TSM) in the manifold of covariance matrices. The proposed method is named CSP-TSM. Spatial filtering is performed on the bandpass filtered MI EEG signal. Riemannian tangent space is utilized for extracting features from the spatial filtered signal. The TSM features are then fused with the CSP variance based features and feature selection is performed using Lasso. Linear discriminant analysis (LDA) is then applied to the selected features and finally classification is done using support vector machine (SVM) classifier. The proposed framework gives improved performance for MI EEG signal classification in comparison with several competing methods. Experiments conducted shows that the proposed framework reduces the overall classification error rate for MI-BCI by 3.16%, 5.10% and 1.70% (for BCI Competition III dataset IVa, BCI Competition IV Dataset I and BCI Competition IV Dataset IIb, respectively) compared to the conventional CSP method under the same experimental settings. The proposed CSP-TSM method produces promising results when compared with several competing methods in this paper. In addition, the computational complexity is less compared to that of TSM method. Our proposed CSP-TSM framework can be potentially used for developing improved MI-BCI systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

The history of female genital tract malformation classifications and proposal of an updated system.

PubMed

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

Towards an International Classification for Patient Safety: the conceptual framework.

PubMed

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-02-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose.

Towards an International Classification for Patient Safety: the conceptual framework

PubMed Central

Sherman, Heather; Castro, Gerard; Fletcher, Martin; Hatlie, Martin; Hibbert, Peter; Jakob, Robert; Koss, Richard; Lewalle, Pierre; Loeb, Jerod; Perneger, Thomas; Runciman, William; Thomson, Richard; Van Der Schaaf, Tjerk; Virtanen, Martti

2009-01-01

Global advances in patient safety have been hampered by the lack of a uniform classification of patient safety concepts. This is a significant barrier to developing strategies to reduce risk, performing evidence-based research and evaluating existing healthcare policies relevant to patient safety. Since 2005, the World Health Organization's World Alliance for Patient Safety has undertaken the Project to Develop an International Classification for Patient Safety (ICPS) to devise a classification which transforms patient safety information collected from disparate systems into a common format to facilitate aggregation, analysis and learning across disciplines, borders and time. A drafting group, comprised of experts from the fields of patient safety, classification theory, health informatics, consumer/patient advocacy, law and medicine, identified and defined key patient safety concepts and developed an internationally agreed conceptual framework for the ICPS based upon existing patient safety classifications. The conceptual framework was iteratively improved through technical expert meetings and a two-stage web-based modified Delphi survey of over 250 international experts. This work culminated in a conceptual framework consisting of ten high level classes: incident type, patient outcomes, patient characteristics, incident characteristics, contributing factors/hazards, organizational outcomes, detection, mitigating factors, ameliorating actions and actions taken to reduce risk. While the framework for the ICPS is in place, several challenges remain. Concepts need to be defined, guidance for using the classification needs to be provided, and further real-world testing needs to occur to progressively refine the ICPS to ensure it is fit for purpose. PMID:19147595

Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

NASA Astrophysics Data System (ADS)

Ceballos, G. A.; Hernández, L. F.

2015-04-01

Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

Impact of using the new GOLD classification on the distribution of COPD severity in clinical practice.

PubMed

Hernández, Marcos; García, Gabriel; Falco, Jimena; García, Agustín R; Martín, Vanina; Ibarrola, Manuel; Quadrelli, Silvia

2018-01-01

The objective of this study was to examine how COPD patients were classified by the Global Initiative for Chronic Obstructive Lung Disease (GOLD) spirometry-based severity system and the distribution of COPD severity using the new GOLD 2011 assessment framework. This was an observational, retrospective cohort study conducted in a single tertiary center on a prospective database, which aimed to evaluate the prevalence, incidence, severity, and comorbidities of COPD. Inclusion criteria were age ≥40 years and COPD diagnosis according to GOLD 2007 classification. Clinical factors were compared between the categories in GOLD 2007 and 2011 groups by using the χ 2 test for categorical data and the analysis of variance for continuous data. In total, 420 COPD patients were included in the analysis. The distribution of patients into GOLD 2007 categories was as follows: 6.4% (n=27) of them were classified into subgroup I, 42.1% (n=177) into subgroup II, 37.9% (n=159) into subgroup III, and 13.6% (n=57) into subgroup IV. The distribution of patients into GOLD 2011 categories was as follows: 16.4% (n=69) of them were classified into subgroup A (low risk and fewer symptoms), 32.1% (n=135) into subgroup B (low risk and more symptoms), 21.6% (n=91) into subgroup C (high risk and fewer symptoms), and 29.7% (n=125) into subgroup D (high risk and more symptoms). After the application of the new GOLD 2011 (modified Medical Research Council [mMRC] system), 22% (n=94) of patients were upgraded to a higher level than their spirometry level, and 16.2% (n=68) of them were downgraded in their severity category, meaning that almost 40% of patients changed their severity assessment category. In total, 22% of patients in stage I were allocated to group B, and 35% of patients in stage IV were allocated to group C. Patients in stage III were the most frequently upgraded to a higher risk group (D), taking into account mMRC and exacerbation history. Classifying patients using the new GOLD 2011 criteria reallocated a relevant proportion of patients to a different risk category and identified larger proportions of patients in the mildest and more severe groups compared with GOLD 2007 classification.

Tree mortality based fire severity classification for forest inventories: A Pacific Northwest national forests example

Treesearch

Thomas R. Whittier; Andrew N. Gray

2016-01-01

Determining how the frequency, severity, and extent of forest fires are changing in response to changes in management and climate is a key concern in many regions where fire is an important natural disturbance. In the USA the only national-scale fire severity classification uses satellite image changedetection to produce maps for large (>400 ha) fires, and is...

Classification of trivial spin-1 tensor network states on a square lattice

NASA Astrophysics Data System (ADS)

Lee, Hyunyong; Han, Jung Hoon

2016-09-01

Classification of possible quantum spin liquid (QSL) states of interacting spin-1/2's in two dimensions has been a fascinating topic of condensed matter for decades, resulting in enormous progress in our understanding of low-dimensional quantum matter. By contrast, relatively little work exists on the identification, let alone classification, of QSL phases for spin-1 systems in dimensions higher than one. Employing the powerful ideas of tensor network theory and its classification, we develop general methods for writing QSL wave functions of spin-1 respecting all the lattice symmetries, spin rotation, and time reversal with trivial gauge structure on the square lattice. We find 25 distinct classes characterized by five binary quantum numbers. Several explicit constructions of such wave functions are given for bond dimensions D ranging from two to four, along with thorough numerical analyses to identify their physical characters. Both gapless and gapped states are found. The topological entanglement entropy of the gapped states is close to zero, indicative of topologically trivial states. In D =4 , several different tensors can be linearly combined to produce a family of states within the same symmetry class. A rich "phase diagram" can be worked out among the phases of these tensors, as well as the phase transitions among them. Among the states we identified in this putative phase diagram is the plaquette-ordered phase, gapped resonating valence bond phase, and a critical phase. A continuous transition separates the plaquette-ordered phase from the resonating valence bond phase.

Prototype Expert System for Climate Classification.

ERIC Educational Resources Information Center

Harris, Clay

Many students find climate classification laborious and time-consuming, and through their lack of repetition fail to grasp the details of classification. This paper describes an expert system for climate classification that is being developed at Middle Tennessee State University. Topics include: (1) an introduction to the nature of classification,…

Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin.

PubMed

Bokulich, Nicholas A; Kaehler, Benjamin D; Rideout, Jai Ram; Dillon, Matthew; Bolyen, Evan; Knight, Rob; Huttley, Gavin A; Gregory Caporaso, J

2018-05-17

Taxonomic classification of marker-gene sequences is an important step in microbiome analysis. We present q2-feature-classifier ( https://github.com/qiime2/q2-feature-classifier ), a QIIME 2 plugin containing several novel machine-learning and alignment-based methods for taxonomy classification. We evaluated and optimized several commonly used classification methods implemented in QIIME 1 (RDP, BLAST, UCLUST, and SortMeRNA) and several new methods implemented in QIIME 2 (a scikit-learn naive Bayes machine-learning classifier, and alignment-based taxonomy consensus methods based on VSEARCH, and BLAST+) for classification of bacterial 16S rRNA and fungal ITS marker-gene amplicon sequence data. The naive-Bayes, BLAST+-based, and VSEARCH-based classifiers implemented in QIIME 2 meet or exceed the species-level accuracy of other commonly used methods designed for classification of marker gene sequences that were evaluated in this work. These evaluations, based on 19 mock communities and error-free sequence simulations, including classification of simulated "novel" marker-gene sequences, are available in our extensible benchmarking framework, tax-credit ( https://github.com/caporaso-lab/tax-credit-data ). Our results illustrate the importance of parameter tuning for optimizing classifier performance, and we make recommendations regarding parameter choices for these classifiers under a range of standard operating conditions. q2-feature-classifier and tax-credit are both free, open-source, BSD-licensed packages available on GitHub.

Guidelines on severity assessment and classification of genetically altered mouse and rat lines.

PubMed

Zintzsch, Anne; Noe, Elena; Reißmann, Monika; Ullmann, Kristina; Krämer, Stephanie; Jerchow, Boris; Kluge, Reinhart; Gösele, Claudia; Nickles, Hannah; Puppe, Astrid; Rülicke, Thomas

2017-12-01

Genetic alterations can unpredictably compromise the wellbeing of animals. Thus, more or less harmful phenotypes might appear in the animals used in research projects even when they are not subjected to experimental treatments. The severity classification of suffering has become an important issue since the implementation of Directive 2010/63/EU on the protection of animals used for scientific purposes. Accordingly, the breeding and maintenance of genetically altered (GA) animals which are likely to develop a harmful phenotype has to be authorized. However, a determination of the degree of severity is rather challenging due to the large variety of phenotypes. Here, the Working Group of Berlin Animal Welfare Officers (WG Berlin AWO) provides field-tested guidelines on severity assessment and classification of GA rodents. With a focus on basic welfare assessment and severity classification we provide a list of symptoms that have been classified as non-harmful, mild, moderate or severe burdens. Corresponding monitoring and refinement strategies as well as specific housing requirements have been compiled and are strongly recommended to improve hitherto applied breeding procedures and conditions. The document serves as a guide to determine the degree of severity for an observed phenotype. The aim is to support scientists, animal care takers, animal welfare bodies and competent authorities with this task, and thereby make an important contribution to a European harmonization of severity assessments for the continually increasing number of GA rodents.

Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis.

PubMed

Myburgh, Hermanus C; van Zijl, Willemien H; Swanepoel, DeWet; Hellström, Sten; Laurent, Claude

2016-03-01

Otitis media is one of the most common childhood diseases worldwide, but because of lack of doctors and health personnel in developing countries it is often misdiagnosed or not diagnosed at all. This may lead to serious, and life-threatening complications. There is, thus a need for an automated computer based image-analyzing system that could assist in making accurate otitis media diagnoses anywhere. A method for automated diagnosis of otitis media is proposed. The method uses image-processing techniques to classify otitis media. The system is trained using high quality pre-assessed images of tympanic membranes, captured by digital video-otoscopes, and classifies undiagnosed images into five otitis media categories based on predefined signs. Several verification tests analyzed the classification capability of the method. An accuracy of 80.6% was achieved for images taken with commercial video-otoscopes, while an accuracy of 78.7% was achieved for images captured on-site with a low cost custom-made video-otoscope. The high accuracy of the proposed otitis media classification system compares well with the classification accuracy of general practitioners and pediatricians (~64% to 80%) using traditional otoscopes, and therefore holds promise for the future in making automated diagnosis of otitis media in medically underserved populations.

Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis

PubMed Central

Myburgh, Hermanus C.; van Zijl, Willemien H.; Swanepoel, DeWet; Hellström, Sten; Laurent, Claude

2016-01-01

Background Otitis media is one of the most common childhood diseases worldwide, but because of lack of doctors and health personnel in developing countries it is often misdiagnosed or not diagnosed at all. This may lead to serious, and life-threatening complications. There is, thus a need for an automated computer based image-analyzing system that could assist in making accurate otitis media diagnoses anywhere. Methods A method for automated diagnosis of otitis media is proposed. The method uses image-processing techniques to classify otitis media. The system is trained using high quality pre-assessed images of tympanic membranes, captured by digital video-otoscopes, and classifies undiagnosed images into five otitis media categories based on predefined signs. Several verification tests analyzed the classification capability of the method. Findings An accuracy of 80.6% was achieved for images taken with commercial video-otoscopes, while an accuracy of 78.7% was achieved for images captured on-site with a low cost custom-made video-otoscope. Interpretation The high accuracy of the proposed otitis media classification system compares well with the classification accuracy of general practitioners and pediatricians (~ 64% to 80%) using traditional otoscopes, and therefore holds promise for the future in making automated diagnosis of otitis media in medically underserved populations. PMID:27077122

5 CFR 9901.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9901.221 Administrative Personnel DEPARTMENT OF DEFENSE HUMAN RESOURCES MANAGEMENT AND LABOR RELATIONS SYSTEMS (DEPARTMENT OF DEFENSE-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF DEFENSE NATIONAL SECURITY PERSONNEL SYSTEM (NSPS) Classification Classification Process § 9901.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

5 CFR 9701.221 - Classification requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 9701.221 Administrative Personnel DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.221 Classification...

A real-time heat strain risk classifier using heart rate and skin temperature.

PubMed

Buller, Mark J; Latzka, William A; Yokota, Miyo; Tharion, William J; Moran, Daniel S

2008-12-01

Heat injury is a real concern to workers engaged in physically demanding tasks in high heat strain environments. Several real-time physiological monitoring systems exist that can provide indices of heat strain, e.g. physiological strain index (PSI), and provide alerts to medical personnel. However, these systems depend on core temperature measurement using expensive, ingestible thermometer pills. Seeking a better solution, we suggest the use of a model which can identify the probability that individuals are 'at risk' from heat injury using non-invasive measures. The intent is for the system to identify individuals who need monitoring more closely or who should apply heat strain mitigation strategies. We generated a model that can identify 'at risk' (PSI 7.5) workers from measures of heart rate and chest skin temperature. The model was built using data from six previously published exercise studies in which some subjects wore chemical protective equipment. The model has an overall classification error rate of 10% with one false negative error (2.7%), and outperforms an earlier model and a least squares regression model with classification errors of 21% and 14%, respectively. Additionally, the model allows the classification criteria to be adjusted based on the task and acceptable level of risk. We conclude that the model could be a valuable part of a multi-faceted heat strain management system.

Motor function domains in alternating hemiplegia of childhood.

PubMed

Masoud, Melanie; Gordon, Kelly; Hall, Amanda; Jasien, Joan; Lardinois, Kara; Uchitel, Julie; Mclean, Melissa; Prange, Lyndsey; Wuchich, Jeffrey; Mikati, Mohamad A

2017-08-01

To characterize motor function profiles in alternating hemiplegia of childhood, and to investigate interrelationships between these domains and with age. We studied a cohort of 23 patients (9 males, 14 females; mean age 9y 4mo, range 4mo-43y) who underwent standardized tests to assess gross motor, upper extremity motor control, motor speech, and dysphagia functions. Gross Motor Function Classification System (GMFCS), Gross Motor Function Measure-88 (GMFM-88), Manual Ability Classification System (MACS), and Revised Melbourne Assessment (MA2) scales manifested predominantly mild impairments; motor speech, moderate to severe; Modified Dysphagia Outcome and Severity Scale (M-DOSS), mild-to moderate deficits. GMFCS correlated with GMFM-88 scores (Pearson's correlation, p=0.002), MACS (p=0.038), and MA2 fluency (p=0.005) and accuracy (p=0.038) scores. GMFCS did not correlate with motor speech (p=0.399), MA2 dexterity (p=0.247), range of motion (p=0.063), or M-DOSS (p=0.856). Motor speech was more severely impaired than the GMFCS (p<0.013). There was no correlation between any of the assessment tools and age (p=0.210-0.798). Our data establish a detailed profile of motor function in alternating hemiplegia of childhood, argue against the presence of worse motor function in older patients, identify tools helpful in evaluating this population, and identify oropharyngeal function as the more severely affected domain, suggesting that brain areas controlling this function are more affected than others. © 2017 Mac Keith Press.

Oropharyngeal dysphagia and gross motor skills in children with cerebral palsy.

PubMed

Benfer, Katherine A; Weir, Kelly A; Bell, Kristie L; Ware, Robert S; Davies, Peter S W; Boyd, Roslyn N

2013-05-01

To determine the prevalence of oropharyngeal dysphagia (OPD) and its subtypes (oral phase, pharyngeal phase, saliva control), and their relationship to gross motor functional skills in preschool children with cerebral palsy (CP). It was hypothesized that OPD would be present across all gross motor severity levels, and children with more severe gross motor function would have increased prevalence and severity of OPD. Children with a confirmed diagnosis of CP, 18 to 36 months corrected age, born in Queensland between 2006 and 2009, participated. Children with neurodegenerative conditions were excluded. This was a cross-sectional population-based study. Children were assessed by using 2 direct OPD measures (Schedule for Oral Motor Assessment; Dysphagia Disorders Survey), and observations of signs suggestive of pharyngeal phase impairment and impaired saliva control. Gross motor skills were described by using the Gross Motor Function Measure, Gross Motor Function Classification System (GMFCS), Manual Ability Classification System, and motor type/ distribution. OPD was prevalent in 85% of children with CP, and there was a stepwise relationship between OPD and GMFCS level. There was a significant increase in odds of having OPD, or a subtype, for children who were nonambulant (GMFCS V) compared with those who were ambulant (GMFCS I) (odds ratio = 17.9, P = .036). OPD was present across all levels of gross motor severity using direct assessments. This highlights the need for proactive screening of all young children with CP, even those with mild impairments, to improve growth and nutritional outcomes and respiratory health.

The Bellevue Classification System: nursing's voice upon the library shelves*†

PubMed Central

Mages, Keith C

2011-01-01

This article examines the inspiration, construction, and meaning of the Bellevue Classification System (BCS), created during the 1930s for use in the Bellevue School of Nursing Library. Nursing instructor Ann Doyle, with assistance from librarian Mary Casamajor, designed the BCS after consulting with library leaders and examining leading contemporary classification systems, including the Dewey Decimal Classification and Library of Congress, Ballard, and National Health Library classification systems. A close textual reading of the classes, subclasses, and subdivisions of these classification systems against those of the resulting BCS, reveals Doyle's belief that the BCS was created not only to organize the literature, but also to promote the burgeoning intellectualism and professionalism of early twentieth-century American nursing. PMID:21243054

Coordination of Local Road Classification with the State Highway System Classification: Impact and Clarification of Related Language in the LVR Manual

DOT National Transportation Integrated Search

1996-02-01

This study reviewed the low volume road (LVR) classifications in Kansas in conjunction with the State A, B, C, D, E road classification system and addressed alignment of these differences. As an extension to the State system, an F, G, H classificatio...

Development of Single-Channel Hybrid BCI System Using Motor Imagery and SSVEP.

PubMed

Ko, Li-Wei; Ranga, S S K; Komarov, Oleksii; Chen, Chung-Chiang

2017-01-01

Numerous EEG-based brain-computer interface (BCI) systems that are being developed focus on novel feature extraction algorithms, classification methods and combining existing approaches to create hybrid BCIs. Several recent studies demonstrated various advantages of hybrid BCI systems in terms of an improved accuracy or number of commands available for the user. But still, BCI systems are far from realization for daily use. Having high performance with less number of channels is one of the challenging issues that persists, especially with hybrid BCI systems, where multiple channels are necessary to record information from two or more EEG signal components. Therefore, this work proposes a single-channel (C3 or C4) hybrid BCI system that combines motor imagery (MI) and steady-state visually evoked potential (SSVEP) approaches. This study demonstrates that besides MI features, SSVEP features can also be captured from C3 or C4 channel. The results show that due to rich feature information (MI and SSVEP) at these channels, the proposed hybrid BCI system outperforms both MI- and SSVEP-based systems having an average classification accuracy of 85.6 ± 7.7% in a two-class task.

Inter and intra-observer concordance for the diagnosis of portal hypertension gastropathy.

PubMed

Casas, Meritxell; Vergara, Mercedes; Brullet, Enric; Junquera, Félix; Martínez-Bauer, Eva; Miquel, Mireia; Sánchez-Delgado, Jordi; Dalmau, Blai; Campo, Rafael; Calvet, Xavier

2018-03-01

At present there is no fully accepted endoscopic classification for the assessment of the severity of portal hypertensive gastropathy (PHG). Few studies have evaluated inter and intra-observer concordance or the degree of concordance between different endoscopic classifications. To evaluate inter and intra-observer agreement for the presence of portal hypertensive gastropathy and enteropathy using different endoscopic classifications. Patients with liver cirrhosis were included into the study. Enteroscopy was performed under sedation. The location of lesions and their severity was recorded. Images were videotaped and subsequently evaluated independently by three different endoscopists, one of whom was the initial endoscopist. The agreement between observations was assessed using the kappa index. Seventy-four patients (mean age 63.2 years, 53 males and 21 females) were included. The agreement between the three endoscopists regarding the presence or absence of PHG using the Tanoue and McCormack classifications was very low (kappa scores = 0.16 and 0.27, respectively). The current classifications of portal hypertensive gastropathy have a very low degree of intra and inter-observer agreement for the diagnosis and assessment of gastropathy severity.

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer

PubMed Central

2012-01-01

Background Automated classification of histopathology involves identification of multiple classes, including benign, cancerous, and confounder categories. The confounder tissue classes can often mimic and share attributes with both the diseased and normal tissue classes, and can be particularly difficult to identify, both manually and by automated classifiers. In the case of prostate cancer, they may be several confounding tissue types present in a biopsy sample, posing as major sources of diagnostic error for pathologists. Two common multi-class approaches are one-shot classification (OSC), where all classes are identified simultaneously, and one-versus-all (OVA), where a “target” class is distinguished from all “non-target” classes. OSC is typically unable to handle discrimination of classes of varying similarity (e.g. with images of prostate atrophy and high grade cancer), while OVA forces several heterogeneous classes into a single “non-target” class. In this work, we present a cascaded (CAS) approach to classifying prostate biopsy tissue samples, where images from different classes are grouped to maximize intra-group homogeneity while maximizing inter-group heterogeneity. Results We apply the CAS approach to categorize 2000 tissue samples taken from 214 patient studies into seven classes: epithelium, stroma, atrophy, prostatic intraepithelial neoplasia (PIN), and prostate cancer Gleason grades 3, 4, and 5. A series of increasingly granular binary classifiers are used to split the different tissue classes until the images have been categorized into a single unique class. Our automatically-extracted image feature set includes architectural features based on location of the nuclei within the tissue sample as well as texture features extracted on a per-pixel level. The CAS strategy yields a positive predictive value (PPV) of 0.86 in classifying the 2000 tissue images into one of 7 classes, compared with the OVA (0.77 PPV) and OSC approaches (0.76 PPV). Conclusions Use of the CAS strategy increases the PPV for a multi-category classification system over two common alternative strategies. In classification problems such as histopathology, where multiple class groups exist with varying degrees of heterogeneity, the CAS system can intelligently assign class labels to objects by performing multiple binary classifications according to domain knowledge. PMID:23110677

Electro-optical seasonal weather and gender data collection

NASA Astrophysics Data System (ADS)

McCoppin, Ryan; Koester, Nathan; Rude, Howard N.; Rizki, Mateen; Tamburino, Louis; Freeman, Andrew; Mendoza-Schrock, Olga

2013-05-01

This paper describes the process used to collect the Seasonal Weather And Gender (SWAG) dataset; an electro-optical dataset of human subjects that can be used to develop advanced gender classification algorithms. Several novel features characterize this ongoing effort (1) the human subjects self-label their gender by performing a specific action during the data collection and (2) the data collection will span months and even years resulting in a dataset containing realistic levels and types of clothing corresponding to the various seasons and weather conditions. It is envisioned that this type of data will support the development and evaluation of more robust gender classification systems that are capable of accurate gender recognition under extended operating conditions.

Enlisted MOS Suitable for the Physically Handicapped

DTIC Science & Technology

1958-12-01

highly motivated in a mobili- zation situation. The pr.mary reason for using this approach was the need for a standardized classification system which...the classification process. The solution was to consider all disabili- ties as "severe" and motivation to perform "good." Thus any individual disabled...MC+e0)H 4E-4)OOHe~~~ A A A P44 O0O)HCeHl H’d e (d *Hc.3d,4-4 HO) HQ .r4 to’- L 4 Xe 𔃺- H r4 Ps4 p) HO -i -i--I<-) rdr r d 90 P 4-- >< d0I - d a)0SoSS

Classification of co-occurring depression and substance abuse symptoms predicts suicide attempts in adolescents.

PubMed

Effinger, Jenell M; Stewart, David G

2012-08-01

Although both depression and substance use have been found to contribute to suicide attempts, the synergistic impact of these disorders has not been fully explored. Additionally, the impact of subthreshold presentations of these disorders has not been researched. We utilized the Quadrant Model of Classification (a matrix of severity of two disorders) to assess for suicide attempt risk among adolescents. Logistic regression was used to examine the impact of co-occurring disorder classification on suicide risk attempts. Results indicate that quadrant classification had a dramatic impact on suicide attempt risk, with individuals with high severity co-occurring disorders at greatest risk. © 2012 The American Association of Suicidology.

A support vector machine approach for classification of welding defects from ultrasonic signals

NASA Astrophysics Data System (ADS)

Chen, Yuan; Ma, Hong-Wei; Zhang, Guang-Ming

2014-07-01

Defect classification is an important issue in ultrasonic non-destructive evaluation. A layered multi-class support vector machine (LMSVM) classification system, which combines multiple SVM classifiers through a layered architecture, is proposed in this paper. The proposed LMSVM classification system is applied to the classification of welding defects from ultrasonic test signals. The measured ultrasonic defect echo signals are first decomposed into wavelet coefficients by the wavelet packet transform. The energy of the wavelet coefficients at different frequency channels are used to construct the feature vectors. The bees algorithm (BA) is then used for feature selection and SVM parameter optimisation for the LMSVM classification system. The BA-based feature selection optimises the energy feature vectors. The optimised feature vectors are input to the LMSVM classification system for training and testing. Experimental results of classifying welding defects demonstrate that the proposed technique is highly robust, precise and reliable for ultrasonic defect classification.

Classification of time series patterns from complex dynamic systems

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

Schryver, J.C.; Rao, N.

1998-07-01

An increasing availability of high-performance computing and data storage media at decreasing cost is making possible the proliferation of large-scale numerical databases and data warehouses. Numeric warehousing enterprises on the order of hundreds of gigabytes to terabytes are a reality in many fields such as finance, retail sales, process systems monitoring, biomedical monitoring, surveillance and transportation. Large-scale databases are becoming more accessible to larger user communities through the internet, web-based applications and database connectivity. Consequently, most researchers now have access to a variety of massive datasets. This trend will probably only continue to grow over the next several years. Unfortunately,more » the availability of integrated tools to explore, analyze and understand the data warehoused in these archives is lagging far behind the ability to gain access to the same data. In particular, locating and identifying patterns of interest in numerical time series data is an increasingly important problem for which there are few available techniques. Temporal pattern recognition poses many interesting problems in classification, segmentation, prediction, diagnosis and anomaly detection. This research focuses on the problem of classification or characterization of numerical time series data. Highway vehicles and their drivers are examples of complex dynamic systems (CDS) which are being used by transportation agencies for field testing to generate large-scale time series datasets. Tools for effective analysis of numerical time series in databases generated by highway vehicle systems are not yet available, or have not been adapted to the target problem domain. However, analysis tools from similar domains may be adapted to the problem of classification of numerical time series data.« less

Behavior genetics of personality disorders: informing classification and conceptualization in DSM-5.

PubMed

South, Susan C; DeYoung, Nathaniel J

2013-07-01

Personality pathology is currently captured in the Diagnostic and Statistical Manual through 10 categorical personality disorder (PD) diagnoses grouped into three descriptive clusters. This classification system has been criticized by many for using discrete categories and arbitrary thresholds when making clinical decisions. To address these critiques, the DSM-5 Personality and Personality Disorders Work Group has put forth a proposal that significantly alters the structure and content of the DSM-IV PD section. If this DSM-5 Work Group has conducted its own systematic review of the empirical literature, this review has not been released or made widely available. As such, it is up to the psychology community at large to determine how well the suggested changes align with findings from extant PD research. The current article joins this effort by addressing the contribution of behavior genetic findings to the revision process for classification of PDs in DSM-5. First, we provide a brief review of the history of PD classification in the DSM. Next, we present an overview and rationale for each of the five major suggested changes to PD diagnoses. For each suggested change, we outline the available evidence from behavior genetics and interpretations of these findings. Finally, we offer a summary of considerations for PD classification as the DSM-5 moves forward. Review of the behavior genetics literature suggests that several features of the DSM-5 proposal, including the elimination of 4 PDs, merging clinical disorders and PDs on a single axis, and the implementation of a trait rating system, require significantly greater explication before a product is finalized.

Risk factors affecting injury severity determined by the MAIS score.

PubMed

Ferreira, Sara; Amorim, Marco; Couto, Antonio

2017-07-04

Traffic crashes result in a loss of life but also impact the quality of life and productivity of crash survivors. Given the importance of traffic crash outcomes, the issue has received attention from researchers and practitioners as well as government institutions, such as the European Commission (EC). Thus, to obtain detailed information on the injury type and severity of crash victims, hospital data have been proposed for use alongside police crash records. A new injury severity classification based on hospital data, called the maximum abbreviated injury scale (MAIS), was developed and recently adopted by the EC. This study provides an in-depth analysis of the factors that affect injury severity as classified by the MAIS score. In this study, the MAIS score was derived from the International Classification of Diseases. The European Union adopted an MAIS score equal to or greater than 3 as the definition for a serious traffic crash injury. Gains are expected from using both police and hospital data because the injury severities of the victims are detailed by medical staff and the characteristics of the crash and the site of its occurrence are also provided. The data were obtained by linking police and hospital data sets from the Porto metropolitan area of Portugal over a 6-year period (2006-2011). A mixed logit model was used to understand the factors that contribute to the injury severity of traffic victims and to explore the impact of these factors on injury severity. A random parameter approach offers methodological flexibility to capture individual-specific heterogeneity. Additionally, to understand the importance of using a reliable injury severity scale, we compared MAIS with length of hospital stay (LHS), a classification used by several countries, including Portugal, to officially report injury severity. To do so, the same statistical technique was applied using the same variables to analyze their impact on the injury severity classified according to LHS. This study showed the impact of variables, such as the presence of blood alcohol, the use of protection devices, the type of crash, and the site characteristics, on the injury severity classified according to the MAIS score. Additionally, the sex and age of the victims were analyzed as risk factors, showing that elderly and male road users are highly associated with MAIS 3+ injuries. The comparison between the marginal effects of the variables estimated by the MAIS and LHS models showed significant differences. In addition to the differences in the magnitude of impact of each variable, we found that the impact of the road environment variable was dependent on the injury severity classification. The differences in the effects of risk factors between the classifications highlight the importance of using a reliable classification of injury severity. Additionally, the relationship between LHS and MAIS levels is quite different among countries, supporting the previous conclusion that bias is expected in the assessment of risk factors if an injury severity classification other than MAIS is used.

[Diagnostics and treatment strategies for multiple trauma patients].

PubMed

Pfeifer, R; Pape, H-C

2016-02-01

Severe trauma is still one of the leading causes of death worldwide. The initial treatment and diagnostics are of immense importance in polytraumatized patients. The initial approach mainly focuses on the advanced trauma life support (ATLS) concept. This includes the identification of life-threatening conditions and application of life-saving interventions. Depending on the physiological condition of the patient, the surgical treatment strategies of early total care (ETC) or damage control orthopedics (DCO) can be chosen. Appropriate surgical management can reduce the incidence of associated delayed systemic complications. This review summarizes the most commonly used definitions of polytrauma (including the Berlin polytrauma definition) and classification systems of severely injured patients. Moreover, the recently introduced treatment strategy of the safe definitive surgery concept for severely injured patients is also discussed in this article.

Classifications of Acute Scaphoid Fractures: A Systematic Literature Review.

PubMed

Ten Berg, Paul W; Drijkoningen, Tessa; Strackee, Simon D; Buijze, Geert A

2016-05-01

Background In the lack of consensus, surgeon-based preference determines how acute scaphoid fractures are classified. There is a great variety of classification systems with considerable controversies. Purposes The purpose of this study was to provide an overview of the different classification systems, clarifying their subgroups and analyzing their popularity by comparing citation indexes. The intention was to improve data comparison between studies using heterogeneous fracture descriptions. Methods We performed a systematic review of the literature based on a search of medical literature from 1950 to 2015, and a manual search using the reference lists in relevant book chapters. Only original descriptions of classifications of acute scaphoid fractures in adults were included. Popularity was based on citation index as reported in the databases of Web of Science (WoS) and Google Scholar. Articles that were cited <10 times in WoS were excluded. Results Our literature search resulted in 308 potentially eligible descriptive reports of which 12 reports met the inclusion criteria. We distinguished 13 different (sub) classification systems based on (1) fracture location, (2) fracture plane orientation, and (3) fracture stability/displacement. Based on citations numbers, the Herbert classification was most popular, followed by the Russe and Mayo classifications. All classification systems were based on plain radiography. Conclusions Most classification systems were based on fracture location, displacement, or stability. Based on the controversy and limited reliability of current classification systems, suggested research areas for an updated classification include three-dimensional fracture pattern etiology and fracture fragment mobility assessed by dynamic imaging.

Ecosystem services classification: A systems ecology perspective of the cascade framework.

PubMed

La Notte, Alessandra; D'Amato, Dalia; Mäkinen, Hanna; Paracchini, Maria Luisa; Liquete, Camino; Egoh, Benis; Geneletti, Davide; Crossman, Neville D

2017-03-01

Ecosystem services research faces several challenges stemming from the plurality of interpretations of classifications and terminologies. In this paper we identify two main challenges with current ecosystem services classification systems: i) the inconsistency across concepts, terminology and definitions, and; ii) the mix up of processes and end-state benefits, or flows and assets. Although different ecosystem service definitions and interpretations can be valuable for enriching the research landscape, it is necessary to address the existing ambiguity to improve comparability among ecosystem-service-based approaches. Using the cascade framework as a reference, and Systems Ecology as a theoretical underpinning, we aim to address the ambiguity across typologies. The cascade framework links ecological processes with elements of human well-being following a pattern similar to a production chain. Systems Ecology is a long-established discipline which provides insight into complex relationships between people and the environment. We present a refreshed conceptualization of ecosystem services which can support ecosystem service assessment techniques and measurement. We combine the notions of biomass, information and interaction from system ecology, with the ecosystem services conceptualization to improve definitions and clarify terminology. We argue that ecosystem services should be defined as the interactions (i.e. processes) of the ecosystem that produce a change in human well-being, while ecosystem components or goods, i.e. countable as biomass units, are only proxies in the assessment of such changes. Furthermore, Systems Ecology can support a re-interpretation of the ecosystem services conceptualization and related applied research, where more emphasis is needed on the underpinning complexity of the ecological system.

Classification of close binary systems by Svechnikov

NASA Astrophysics Data System (ADS)

Dryomova, G. N.

The paper presents the historical overview of classification schemes of eclipsing variable stars with the foreground of advantages of the classification scheme by Svechnikov being widely appreciated for Close Binary Systems due to simplicity of classification criteria and brevity.

Classification of CT examinations for COPD visual severity analysis

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

2012-03-01

In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

Recursive heuristic classification

NASA Technical Reports Server (NTRS)

Wilkins, David C.

1994-01-01

The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

Diagnostic criteria, severity classification and guidelines of localized scleroderma.

PubMed

Asano, Yoshihide; Fujimoto, Manabu; Ishikawa, Osamu; Sato, Shinichi; Jinnin, Masatoshi; Takehara, Kazuhiko; Hasegawa, Minoru; Yamamoto, Toshiyuki; Ihn, Hironobu

2018-04-23

We established diagnostic criteria and severity classification of localized scleroderma because there is no established diagnostic criteria or widely accepted severity classification of the disease. Also, there has been no clinical guideline for localized scleroderma, so we established its clinical guideline ahead of all over the world. In particular, the clinical guideline was established by clinical questions based on evidence-based medicine according to the New Minds Clinical Practice Guideline Creation Manual (version 1.0). We aimed to make the guideline easy to use and reliable based on the newest evidence, and to present guidance as specific as possible for various clinical problems in treatment of localized scleroderma. © 2018 Japanese Dermatological Association.

Data Mining Methods for Recommender Systems

NASA Astrophysics Data System (ADS)

Amatriain, Xavier; Jaimes*, Alejandro; Oliver, Nuria; Pujol, Josep M.

In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

Utilizing feedback in adaptive SAR ATR systems

NASA Astrophysics Data System (ADS)

Horsfield, Owen; Blacknell, David

2009-05-01

Existing SAR ATR systems are usually trained off-line with samples of target imagery or CAD models, prior to conducting a mission. If the training data is not representative of mission conditions, then poor performance may result. In addition, it is difficult to acquire suitable training data for the many target types of interest. The Adaptive SAR ATR Problem Set (AdaptSAPS) program provides a MATLAB framework and image database for developing systems that adapt to mission conditions, meaning less reliance on accurate training data. A key function of an adaptive system is the ability to utilise truth feedback to improve performance, and it is this feature which AdaptSAPS is intended to exploit. This paper presents a new method for SAR ATR that does not use training data, based on supervised learning. This is achieved by using feature-based classification, and several new shadow features have been developed for this purpose. These features allow discrimination of vehicles from clutter, and classification of vehicles into two classes: targets, comprising military combat types, and non-targets, comprising bulldozers and trucks. The performance of the system is assessed using three baseline missions provided with AdaptSAPS, as well as three additional missions. All performance metrics indicate a distinct learning trend over the course of a mission, with most third and fourth quartile performance levels exceeding 85% correct classification. It has been demonstrated that these performance levels can be maintained even when truth feedback rates are reduced by up to 55% over the course of a mission.

Stand-off CWA imaging system: second sight MS

NASA Astrophysics Data System (ADS)

Bernascolle, Philippe F.; Elichabe, Audrey; Fervel, Franck; Haumonté, Jean-Baptiste

2012-06-01

In recent years, several manufactures of IR imaging devices have launched commercial models applicable to a wide range of chemical species. These cameras are rugged and sufficiently sensitive to detect low concentrations of toxic and combustible gases. Bertin Technologies, specialized in the design and supply of innovating systems for industry, defense and health, has developed a stand-off gas imaging system using a multi-spectral infrared imaging technology. With this system, the gas cloud size, localization and evolution can be displayed in real time. This technology was developed several years ago in partnership with the CEB, a French MoD CBRN organization. The goal was to meet the need for early warning caused by a chemical threat. With a night & day efficiency of up to 5 km, this process is able to detect Chemical Warfare Agents (CWA), critical Toxic Industrial Compounds (TIC) and also flammable gases. The system has been adapted to detect industrial spillage, using off-the-shelf uncooled infrared cameras, allowing 24/7 surveillance without costly frequent maintenance. The changes brought to the system are in compliance with Military Specifications (MS) and primarily focus on the signal processing improving the classification of the detected products and on the simplification of the Human Machine Interface (HMI). Second Sight MS is the only mass produced, passive stand-off CWA imaging system with a wide angle (up to 60°) already used by several regular armies around the world. This paper examines this IR gas imager performance when exposed to several CWA, TIC and simulant compounds. First, we will describe the Second Sight MS system. The theory of gas detection, visualization and classification functions has already been described elsewhere, so we will just summarize it here. We will then present the main topic of this paper which is the results of the tests done in laboratory on live agents and in open field on simulant. The sensitivity threshold of the camera measured in laboratory, on some CWA (G, H agents...) and TIC (ammonia, sulfur dioxide...) will be given. The result of the detection and visualization of a gas cloud in open field testing for some simulants (DMMP, SF6) at a far distance will be also shown.

Clinical aspects of autoimmune rheumatic diseases.

PubMed

Goldblatt, Fiona; O'Neill, Sean G

2013-08-31

Multisystem autoimmune rheumatic diseases are heterogeneous rare disorders associated with substantial morbidity and mortality. Efforts to create international consensus within the past decade have resulted in the publication of new classification or nomenclature criteria for several autoimmune rheumatic diseases, specifically for systemic lupus erythematosus, Sjögren's syndrome, and the systemic vasculitides. Substantial progress has been made in the formulation of new criteria in systemic sclerosis and idiopathic inflammatory myositis. Although the autoimmune rheumatic diseases share many common features and clinical presentations, differentiation between the diseases is crucial because of important distinctions in clinical course, appropriate drugs, and prognoses. We review some of the dilemmas in the diagnosis of these autoimmune rheumatic diseases, and focus on the importance of new classification criteria, clinical assessment, and interpretation of autoimmune serology. In this era of improvement of mortality rates for patients with autoimmune rheumatic diseases, we pay particular attention to the effect of leading complications, specifically cardiovascular manifestations and cancer, and we update epidemiology and prognosis. Copyright © 2013 Elsevier Ltd. All rights reserved.

A hospital-wide clinical findings dictionary based on an extension of the International Classification of Diseases (ICD).

PubMed

Bréant, C; Borst, F; Campi, D; Griesser, V; Momjian, S

1999-01-01

The use of a controlled vocabulary set in a hospital-wide clinical information system is of crucial importance for many departmental database systems to communicate and exchange information. In the absence of an internationally recognized clinical controlled vocabulary set, a new extension of the International statistical Classification of Diseases (ICD) is proposed. It expands the scope of the standard ICD beyond diagnosis and procedures to clinical terminology. In addition, the common Clinical Findings Dictionary (CFD) further records the definition of clinical entities. The construction of the vocabulary set and the CFD is incremental and manual. Tools have been implemented to facilitate the tasks of defining/maintaining/publishing dictionary versions. The design of database applications in the integrated clinical information system is driven by the CFD which is part of the Medical Questionnaire Designer tool. Several integrated clinical database applications in the field of diabetes and neuro-surgery have been developed at the HUG.

The Weathering of Antarctic Meteorites: Climatic Controls on Weathering Rates and Implications for Meteorite Accumulation

NASA Technical Reports Server (NTRS)

Benoit, P. H.; Akridge, J. M. C.; Sears, D. W. G.; Bland, P. A.

1995-01-01

Weathering of meteorites includes a variety of chemical and mineralogical changes, including conversion of metal to iron oxides, or rust. Other changes include the devitrification of glass, especially in fusion crust. On a longer time scale, major minerals such as olivine, pyroxene, and feldspar are partially or wholly converted to various phyllosilicates. The degree of weathering of meteorite finds is often noted using a qualitative system based on visual inspection of hand specimens. Several quantitative weathering classification systems have been proposed or are currently under development. Wlotzka has proposed a classification system based on mineralogical changes observed in polished sections and Mossbauer properties of meteorite powders have also been used. In the current paper, we discuss induced thermoluminescence (TL) as an indicator of degree of weathering of individual meteorites. The quantitative measures of weathering, including induced TL, suffer from one major flaw, namely that their results only apply to small portions of the meteorite.

Heterogeneous but “Standard” Coding Systems for Adverse Events: Issues in Achieving Interoperability between Apples and Oranges

PubMed Central

Richesson, Rachel L.; Fung, Kin Wah; Krischer, Jeffrey P.

2008-01-01

Monitoring adverse events (AEs) is an important part of clinical research and a crucial target for data standards. The representation of adverse events themselves requires the use of controlled vocabularies with thousands of needed clinical concepts. Several data standards for adverse events currently exist, each with a strong user base. The structure and features of these current adverse event data standards (including terminologies and classifications) are different, so comparisons and evaluations are not straightforward, nor are strategies for their harmonization. Three different data standards - the Medical Dictionary for Regulatory Activities (MedDRA) and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) terminologies, and Common Terminology Criteria for Adverse Events (CTCAE) classification - are explored as candidate representations for AEs. This paper describes the structural features of each coding system, their content and relationship to the Unified Medical Language System (UMLS), and unsettled issues for future interoperability of these standards. PMID:18406213

A hospital-wide clinical findings dictionary based on an extension of the International Classification of Diseases (ICD).

PubMed Central

Bréant, C.; Borst, F.; Campi, D.; Griesser, V.; Momjian, S.

1999-01-01

The use of a controlled vocabulary set in a hospital-wide clinical information system is of crucial importance for many departmental database systems to communicate and exchange information. In the absence of an internationally recognized clinical controlled vocabulary set, a new extension of the International statistical Classification of Diseases (ICD) is proposed. It expands the scope of the standard ICD beyond diagnosis and procedures to clinical terminology. In addition, the common Clinical Findings Dictionary (CFD) further records the definition of clinical entities. The construction of the vocabulary set and the CFD is incremental and manual. Tools have been implemented to facilitate the tasks of defining/maintaining/publishing dictionary versions. The design of database applications in the integrated clinical information system is driven by the CFD which is part of the Medical Questionnaire Designer tool. Several integrated clinical database applications in the field of diabetes and neuro-surgery have been developed at the HUG. Images Figure 1 PMID:10566451

Recognition of Arabic Sign Language Alphabet Using Polynomial Classifiers

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Al-Rousan, M.

2005-12-01

Building an accurate automatic sign language recognition system is of great importance in facilitating efficient communication with deaf people. In this paper, we propose the use of polynomial classifiers as a classification engine for the recognition of Arabic sign language (ArSL) alphabet. Polynomial classifiers have several advantages over other classifiers in that they do not require iterative training, and that they are highly computationally scalable with the number of classes. Based on polynomial classifiers, we have built an ArSL system and measured its performance using real ArSL data collected from deaf people. We show that the proposed system provides superior recognition results when compared with previously published results using ANFIS-based classification on the same dataset and feature extraction methodology. The comparison is shown in terms of the number of misclassified test patterns. The reduction in the rate of misclassified patterns was very significant. In particular, we have achieved a 36% reduction of misclassifications on the training data and 57% on the test data.

Analysis of x-ray hand images for bone age assessment

NASA Astrophysics Data System (ADS)

Serrat, Joan; Vitria, Jordi M.; Villanueva, Juan J.

1990-09-01

In this paper we describe a model-based system for the assessment of skeletal maturity on hand radiographs by the TW2 method. The problem consists in classiflying a set of bones appearing in an image in one of several stages described in an atlas. A first approach consisting in pre-processing segmentation and classification independent phases is also presented. However it is only well suited for well contrasted low noise images without superimposed bones were the edge detection by zero crossing of second directional derivatives is able to extract all bone contours maybe with little gaps and few false edges on the background. Hence the use of all available knowledge about the problem domain is needed to build a rather general system. We have designed a rule-based system for narrow down the rank of possible stages for each bone and guide the analysis process. It calls procedures written in conventional languages for matching stage models against the image and getting features needed in the classification process.

Drug-induced sedation endoscopy (DISE) classification systems: a systematic review and meta-analysis.

PubMed

Dijemeni, Esuabom; D'Amone, Gabriele; Gbati, Israel

2017-12-01

Drug-induced sedation endoscopy (DISE) classification systems have been used to assess anatomical findings on upper airway obstruction, and decide and plan surgical treatments and act as a predictor for surgical treatment outcome for obstructive sleep apnoea management. The first objective is to identify if there is a universally accepted DISE grading and classification system for analysing DISE findings. The second objective is to identify if there is one DISE grading and classification treatment planning framework for deciding appropriate surgical treatment for obstructive sleep apnoea (OSA). The third objective is to identify if there is one DISE grading and classification treatment outcome framework for determining the likelihood of success for a given OSA surgical intervention. A systematic review was performed to identify new and significantly modified DISE classification systems: concept, advantages and disadvantages. Fourteen studies proposing a new DISE classification system and three studies proposing a significantly modified DISE classification were identified. None of the studies were based on randomised control trials. DISE is an objective method for visualising upper airway obstruction. The classification and assessment of clinical findings based on DISE is highly subjective due to the increasing number of DISE classification systems. Hence, this creates a growing divergence in surgical treatment planning and treatment outcome. Further research on a universally accepted objective DISE assessment is critically needed.

Questions on Verbal Behavior and Its Application to Individuals with Autism: An Interview with the Experts

ERIC Educational Resources Information Center

Behavior Analyst Today, 2010

2010-01-01

The use of Skinner's Verbal Behavior (VB) classification system has been increasingly applied to learners with autism. In this interview, several of the best known behavior analysts were asked to answer some key questions regarding this practice, the state of research regarding the advantages of this approach, and the confusion that exists…

Disordered Quantum Gases and Spin-Dependent Lattices

DTIC Science & Technology

2013-07-07

regarding the role of disorder in many-particle quantum systems, such as superconductors and electronic solids. These issues are of great technological...REPORT Disordered Quantum Gases and Spin-Dependent Lattices 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: This grant supported the first realization of...the disordered Bose-Hubbard models using ultra-cold atoms trapped in a disordered optical lattice. Several critical questions regarding this crucial

A New Tool for Climatic Analysis Using the Koppen Climate Classification

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2011-01-01

The purpose of climate classification is to help make order of the seemingly endless spatial distribution of climates. The Koppen classification system in a modified format is the most widely applied system in use today. This system may not be the best nor most complete climate classification that can be conceived, but it has gained widespread…

Combat ocular trauma and systemic injury.

PubMed

Weichel, Eric D; Colyer, Marcus H

2008-11-01

To review the recent literature regarding combat ocular trauma during hostilities in Operations Iraqi Freedom and Enduring Freedom, describe the classification of combat ocular trauma, and offer strategies that may assist in the management of eye injuries. Several recent publications have highlighted features of combat ocular trauma from Operation Iraqi Freedom. The most common cause of today's combat ocular injuries is unconventional fragmentary munitions causing significant blast injuries. These explosive munitions cause high rates of concomitant nonocular injuries such as traumatic brain injury, amputation, and other organ injuries. The most frequent ocular injuries include open-globe and adnexal lacerations. The extreme severity of combat-related open-globe injuries leads to high rates of primary enucleation and retained intraocular foreign bodies. Visual outcomes of intraocular foreign body injuries are similar to other series despite delayed removal, and no cases of endophthalmitis have occurred. Despite these advances, however, significant vision loss persists in cases of perforating globe injuries as well as open and closed-globe trauma involving the posterior segment. This review summarizes the recent literature describing ocular and systemic injuries sustained during Operations Iraqi and Enduring Freedom. An emphasis on classification of ocular injuries as well as a discussion of main outcome measures and complications is discussed.

Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

PubMed

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

Advances in Spectral-Spatial Classification of Hyperspectral Images

NASA Technical Reports Server (NTRS)

Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

2012-01-01

Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

The postoperative COFAS end-stage ankle arthritis classification system: interobserver and intraobserver reliability.

PubMed

Krause, Fabian G; Di Silvestro, Matthew; Penner, Murray J; Wing, Kevin J; Glazebrook, Mark A; Daniels, Timothy R; Lau, Johnny T C; Younger, Alastair S E

2012-02-01

End-stage ankle arthritis is operatively treated with numerous designs of total ankle replacement and different techniques for ankle fusion. For superior comparison of these procedures, outcome research requires a classification system to stratify patients appropriately. A postoperative 4-type classification system was designed by 6 fellowship-trained foot and ankle surgeons. Four surgeons reviewed blinded patient profiles and radiographs on 2 occasions to determine the interobserver and intraobserver reliability of the classification. Excellent interobserver reliability (κ = .89) and intraobserver reproducibility (κ = .87) were demonstrated for the postoperative classification system. In conclusion, the postoperative Canadian Orthopaedic Foot and Ankle Society (COFAS) end-stage ankle arthritis classification system appears to be a valid tool to evaluate the outcome of patients operated for end-stage ankle arthritis.

[Scoring systems in intensive care medicine : principles, models, application and limits].

PubMed

Fleig, V; Brenck, F; Wolff, M; Weigand, M A

2011-10-01

Scoring systems are used in all diagnostic areas of medicine. Several parameters are evaluated and rated with points according to their value in order to simplify a complex clinical situation with a score. The application ranges from the classification of disease severity through determining the number of staff for the intensive care unit (ICU) to the evaluation of new therapies under study conditions. Since the introduction of scoring systems in the 1980's a variety of different score models has been developed. The scoring systems that are employed in intensive care and are discussed in this article can be categorized into prognostic scores, expenses scores and disease-specific scores. Since the introduction of compulsory recording of two scoring systems for accounting in the German diagnosis-related groups (DRG) system, these tools have gained more importance for all intensive care physicians. Problems remain in the valid calculation of scores and interpretation of the results.

Railroad Classification Yard Technology Manual: Volume II : Yard Computer Systems

DOT National Transportation Integrated Search

1981-08-01

This volume (Volume II) of the Railroad Classification Yard Technology Manual documents the railroad classification yard computer systems methodology. The subjects covered are: functional description of process control and inventory computer systems,...

Relationships between World Health Organization "International Classification of Functioning, Disability and Health" Constructs and Participation in Adults with Severe Mental Illness

ERIC Educational Resources Information Center

Sánchez, Jennifer; Rosenthal, David A.; Chan, Fong; Brooks, Jessica; Bezyak, Jill L.

2016-01-01

Purpose: To examine the World Health Organization "International Classification of Functioning, Disability and Health" (ICF) constructs as correlates of community participation of people with severe mental illnesses (SMI). Methods: Quantitative descriptive research design using multiple regression and correlational techniques was used to…

A new generic system for the pantropical Caesalpinia group (Leguminosae).

PubMed

Gagnon, Edeline; Bruneau, Anne; Hughes, Colin E; de Queiroz, Luciano Paganucci; Lewis, Gwilym P

2016-01-01

The Caesalpinia group is a large pantropical clade of ca. 205 species in subfamily Caesalpinioideae (Leguminosae) in which generic delimitation has been in a state of considerable flux. Here we present new phylogenetic analyses based on five plastid and one nuclear ribosomal marker, with dense taxon sampling including 172 (84%) of the species and representatives of all previously described genera in the Caesalpinia group. These analyses show that the current classification of the Caesalpinia group into 21 genera needs to be revised. Several genera ( Poincianella , Erythrostemon , Cenostigma and Caesalpinia sensu Lewis, 2005) are non-monophyletic and several previously unclassified Asian species segregate into clades that merit recognition at generic rank. In addition, the near-completeness of our taxon sampling identifies three species that do not belong in any of the main clades and these are recognised as new monospecific genera. A new generic classification of the Caesalpinia group is presented including a key for the identification of genera, full generic descriptions, illustrations (drawings and photo plates of all genera), and (for most genera) the nomenclatural transfer of species to their correct genus. We recognise 26 genera, with reinstatement of two previously described genera ( Biancaea Tod., Denisophytum R. Vig.), re-delimitation and expansion of several others ( Moullava , Cenostigma , Libidibia and Erythrostemon ), contraction of Caesalpinia s.s. and description of four new ones ( Gelrebia , Paubrasilia , Hererolandia and Hultholia ), and make 75 new nomenclatural combinations in this new generic system.

Cause of and factors associated with stillbirth: a systematic review of classification systems.

PubMed

Aminu, Mamuda; Bar-Zeev, Sarah; van den Broek, Nynke

2017-05-01

An estimated 2.6 million stillbirths occur worldwide each year. A standardized classification system setting out possible cause of death and contributing factors is useful to help obtain comparative data across different settings. We undertook a systematic review of stillbirth classification systems to highlight their strengths and weaknesses for practitioners and policymakers. We conducted a systematic search and review of the literature to identify the classification systems used to aggregate information for stillbirth and perinatal deaths. Narrative synthesis was used to compare the range and depth of information required to apply the systems, and the different categories provided for cause of and factors contributing to stillbirth. A total of 118 documents were screened; 31 classification systems were included, of which six were designed specifically for stillbirth, 14 for perinatal death, three systems included neonatal deaths and two included infant deaths. Most (27/31) were developed in and first tested using data obtained from high-income settings. All systems required information from clinical records. One-third of the classification systems (11/31) included information obtained from histology or autopsy. The percentage where cause of death remained unknown ranged from 0.39% using the Nordic-Baltic classification to 46.4% using the Keeling system. Over time, classification systems have become more complex. The success of application is dependent on the availability of detailed clinical information and laboratory investigations. Systems that adopt a layered approach allow for classification of cause of death to a broad as well as to a more detailed level. © 2017 The Authors. Acta Obstetricia et Gynecologica Scandinavica published by John Wiley & Sons Ltd on behalf of Nordic Federation of Societies of Obstetrics and Gynecology (NFOG).

[TNM 2010. What's new?].

PubMed

Wittekind, C

2010-10-01

In the seventh edition of the TNM Classification of Malignant Tumours there are several entirely new classifications: upper aerodigestive mucosal melanoma, gastrointestinal stromal tumour, gastrointestinal carcinoid (neuroendocrine tumour), intrahepatic cholangiocarcinoma, Merkel cell carcinoma, uterine sarcomas, and adrenal cortical carcinoma. Significant modifications concern carcinomas of the oesophagus, oesophagogastric junction, stomach, appendix, biliary tract, lung, skin, prostate and ophthalmic tumours, which will be not addressed in this article. For several tumour entities only minor changes were introduced which might be of importance in daily practice. The new classifications and changes will be commented on without going into details.

Advances in algorithm fusion for automated sea mine detection and classification

NASA Astrophysics Data System (ADS)

Dobeck, Gerald J.; Cobb, J. Tory

2002-11-01

Along with other sensors, the Navy uses high-resolution sonar to detect and classify sea mines in mine-hunting operations. Scientists and engineers have devoted substantial effort to the development of automated detection and classification (D/C) algorithms for these high-resolution systems. Several factors spurred these efforts, including: (1) aids for operators to reduce work overload; (2) more optimal use of all available data; and (3) the introduction of unmanned minehunting systems. The environments where sea mines are typically laid (harbor areas, shipping lanes, and the littorals) give rise to many false alarms caused by natural, biologic, and manmade clutter. The objective of the automated D/C algorithms is to eliminate most of these false alarms while maintaining a very high probability of mine detection and classification (PdPc). In recent years, the benefits of fusing the outputs of multiple D/C algorithms (Algorithm Fusion) have been studied. To date, the results have been remarkable, including reliable robustness to new environments. In this paper a brief history of existing Algorithm Fusion technology and some techniques recently used to improve performance are presented. An exploration of new developments is presented in conclusion.

A Hilbert Transform-Based Smart Sensor for Detection, Classification, and Quantification of Power Quality Disturbances

PubMed Central

Granados-Lieberman, David; Valtierra-Rodriguez, Martin; Morales-Hernandez, Luis A.; Romero-Troncoso, Rene J.; Osornio-Rios, Roque A.

2013-01-01

Power quality disturbance (PQD) monitoring has become an important issue due to the growing number of disturbing loads connected to the power line and to the susceptibility of certain loads to their presence. In any real power system, there are multiple sources of several disturbances which can have different magnitudes and appear at different times. In order to avoid equipment damage and estimate the damage severity, they have to be detected, classified, and quantified. In this work, a smart sensor for detection, classification, and quantification of PQD is proposed. First, the Hilbert transform (HT) is used as detection technique; then, the classification of the envelope of a PQD obtained through HT is carried out by a feed forward neural network (FFNN). Finally, the root mean square voltage (Vrms), peak voltage (Vpeak), crest factor (CF), and total harmonic distortion (THD) indices calculated through HT and Parseval's theorem as well as an instantaneous exponential time constant quantify the PQD according to the disturbance presented. The aforementioned methodology is processed online using digital hardware signal processing based on field programmable gate array (FPGA). Besides, the proposed smart sensor performance is validated and tested through synthetic signals and under real operating conditions, respectively. PMID:23698264

[New colposcopic terminology: Rio de Janeiro--2011].

PubMed

Zlatkov, V; Kostova, P

2014-01-01

The purpose of this work is to review the new colposcopic classification of the International Federation for Cervical Pathology and Colposcopy (IFCPC) from 2011 and the possibilities for its application in diagnostic and treatment processes and research. It fulfills the necessity for a modern and widely applicable nomenclature of the findings and it is based on the latest knowledge in this area. Colposcopic terminology of the vagina, as part of the pathology of the lower genital tract, is included as well, while the vulva and perineum terminology is not yet finally adopted. Furthermore, the various cervical excisional techniques are evaluated and described. According to experts, the popularity of colposcopy will not diminish and it will continue to be used as a routine technique in daily practice. In a critical sense, despite its descriptive and punctual character, the accepted terminology classification does not give a new interpretation of the severity of changes, and as such, it does not significantly modify the diagnostic and therapeutic approach. The lack of a scoring system that would allow the dynamic comparison of the severity of symptoms and the categories over time is a serious weakness. This limits the new colposcopic classification as no more than a working sheet that descriptively assesses the findings of the lower genital tract.

Floating drug delivery systems: a review.

PubMed

Arora, Shweta; Ali, Javed; Ahuja, Alka; Khar, Roop K; Baboota, Sanjula

2005-10-19

The purpose of writing this review on floating drug delivery systems (FDDS) was to compile the recent literature with special focus on the principal mechanism of floatation to achieve gastric retention. The recent developments of FDDS including the physiological and formulation variables affecting gastric retention, approaches to design single-unit and multiple-unit floating systems, and their classification and formulation aspects are covered in detail. This review also summarizes the in vitro techniques, in vivo studies to evaluate the performance and application of floating systems, and applications of these systems. These systems are useful to several problems encountered during the development of a pharmaceutical dosage form.

A real-time phenotyping framework using machine learning for plant stress severity rating in soybean.

PubMed

Naik, Hsiang Sing; Zhang, Jiaoping; Lofquist, Alec; Assefa, Teshale; Sarkar, Soumik; Ackerman, David; Singh, Arti; Singh, Asheesh K; Ganapathysubramanian, Baskar

2017-01-01

Phenotyping is a critical component of plant research. Accurate and precise trait collection, when integrated with genetic tools, can greatly accelerate the rate of genetic gain in crop improvement. However, efficient and automatic phenotyping of traits across large populations is a challenge; which is further exacerbated by the necessity of sampling multiple environments and growing replicated trials. A promising approach is to leverage current advances in imaging technology, data analytics and machine learning to enable automated and fast phenotyping and subsequent decision support. In this context, the workflow for phenotyping (image capture → data storage and curation → trait extraction → machine learning/classification → models/apps for decision support) has to be carefully designed and efficiently executed to minimize resource usage and maximize utility. We illustrate such an end-to-end phenotyping workflow for the case of plant stress severity phenotyping in soybean, with a specific focus on the rapid and automatic assessment of iron deficiency chlorosis (IDC) severity on thousands of field plots. We showcase this analytics framework by extracting IDC features from a set of ~4500 unique canopies representing a diverse germplasm base that have different levels of IDC, and subsequently training a variety of classification models to predict plant stress severity. The best classifier is then deployed as a smartphone app for rapid and real time severity rating in the field. We investigated 10 different classification approaches, with the best classifier being a hierarchical classifier with a mean per-class accuracy of ~96%. We construct a phenotypically meaningful 'population canopy graph', connecting the automatically extracted canopy trait features with plant stress severity rating. We incorporated this image capture → image processing → classification workflow into a smartphone app that enables automated real-time evaluation of IDC scores using digital images of the canopy. We expect this high-throughput framework to help increase the rate of genetic gain by providing a robust extendable framework for other abiotic and biotic stresses. We further envision this workflow embedded onto a high throughput phenotyping ground vehicle and unmanned aerial system that will allow real-time, automated stress trait detection and quantification for plant research, breeding and stress scouting applications.

Balance System

NASA Technical Reports Server (NTRS)

1988-01-01

TherEx Inc.'s AT-1 Computerized Ataxiameter precisely evaluates posture and balance disturbances that commonly accompany neurological and musculoskeletal disorders. Complete system includes two-strain gauged footplates, signal conditioning circuitry, a computer monitor, printer and a stand-alone tiltable balance platform. AT-1 serves as assessment tool, treatment monitor, and rehabilitation training device. It allows clinician to document quantitatively the outcome of treatment and analyze data over time to develop outcome standards for several classifications of patients. It can evaluate specifically the effects of surgery, drug treatment, physical therapy or prosthetic devices.

Studies of volatiles and organic materials in early terrestrial and present-day outer solar system environments

NASA Technical Reports Server (NTRS)

Sagan, Carl; Thompson, W. Reid; Chyba, Christopher F.; Khare, B. N.

1991-01-01

A review and partial summary of projects within several areas of research generally involving the origin, distribution, chemistry, and spectral/dielectric properties of volatiles and organic materials in the outer solar system and early terrestrial environments are presented. The major topics covered include: (1) impact delivery of volatiles and organic compounds to the early terrestrial planets; (2) optical constants measurements; (3) spectral classification, chemical processes, and distribution of materials; and (4) radar properties of ice, hydrocarbons, and organic heteropolymers.

The Continuous Plankton Imaging and Classification Sensor (CPICS): A Sensor for Quantifying Mesoplankton Biodiversity and Community Structure

NASA Astrophysics Data System (ADS)

Gallager, S. M.

2016-02-01

Marine ecosystems are changing at a variety of time scales as a function of a diverse suite of forcing functions both natural and anthropogenic. Establishing a continuous plankton time series consisting of scales from rapid (seconds) to long-term (decades), provides a sentinel for ecosystem change. The key is to measure plankton biodiversity at sufficiently fast time scales that allow disentanglement of physical (transport) and biological (growth) properties of an ecosystem. CPICS is a plankton and particle imaging microscope system that is designed to produce crisp darkfield images of light scattering material in aquatic environments. The open flow design is non-invasive and non-restrictive providing images of very fragile plankton in their natural orientation. Several magnifications are possible from 0.5 to 5x forming a field of view of 10cm to 1mm, respectively. CPICS has been installed on several cabled observing systems called OceanCubes off the coast of Okinawa and Tokyo, Japan providing a continuous stream of plankton images to a machine vision image classifier located at WHOI. Image features include custom algorithms for texture, color pattern, morphology and shape, which are extracted from in-focus target. The features are then used to train a classifier (e.g., Random Forest) resulting in classifications that are tested using cross-validation, confusion matrices and ROC curves. High (>90%) classification accuracies are possible depending on the number of training categories and target complexity. A web-based utility allows access to raw images, training sets, classifiers and classification results. Combined with chemical and physical data from the observatories, an ecologically meaningful plankton index of biodiversity and its variance is developed using a combination of species and taxon groups, which provides an approach for understanding ecosystem change without the need to identify all targets to species. http://oceancubes.whoi.edu/instruments/CPICS

A new map of standardized terrestrial ecosystems of Africa

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Hak, Jon; Josse, Carmen; Bow, Jacquie; Warner, Harumi; Larwanou, Mahamane; Kelbessa, Ensermu; Bekele, Tamrat; Kehl, Harald; Amena, Ruba; Andriamasimanana, Rado; Ba, Taibou; Benson, Laurence; Boucher, Timothy; Brown, Matthew; Cress, Jill J.; Dassering, Oueddo; Friesen, Beverly A.; Gachathi, Francis; Houcine, Sebei; Keita, Mahamadou; Khamala, Erick; Marangu, Dan; Mokua, Fredrick; Morou, Boube; Mucina, Ladislav; Mugisha, Samuel; Mwavu, Edward; Rutherford, Michael; Sanou, Patrice; Syampungani, Stephen; Tomor, Bojoi; Vall, Abdallahi Ould Mohamed; Vande Weghe, Jean Pierre; Wangui, Eunice; Waruingi, Lucy

2013-01-01

Terrestrial ecosystems and vegetation of Africa were classified and mapped as part of a larger effort and global protocol (GEOSS – the Global Earth Observation System of Systems), which includes an activity to map terrestrial ecosystems of the earth in a standardized, robust, and practical manner, and at the finest possible spatial resolution. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datalayers (including coastline, landforms, surficial lithology, and bioclimates) were developed at spatial and classification resolutions finer than existing similar datalayers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree (CART) inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover. Multi-scale ecosystems were classified and mapped in an increasingly detailed hierarchical framework using vegetation-based concepts of class, subclass, formation, division, and macrogroup levels. The finest vegetation units (macrogroups) classified and mapped in this effort are defined using diagnostic plant species and diagnostic growth forms that reflect biogeographic differences in composition and sub-continental to regional differences in mesoclimate, geology, substrates, hydrology, and disturbance regimes (FGDC, 2008). The macrogroups are regarded as meso-scale (100s to 10,000s of hectares) ecosystems. A total of 126 macrogroup types were mapped, each with multiple, repeating occurrences on the landscape. The modeling effort was implemented at a base spatial resolution of 90 m. In addition to creating several rich, new continent-wide biophysical datalayers describing African vegetation and ecosystems, our intention was to explore feasible approaches to rapidly moving this type of standardized, continent-wide, ecosystem classification and mapping effort forward.

Searching bioremediation patents through Cooperative Patent Classification (CPC).

PubMed

Prasad, Rajendra

2016-03-01

Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation.

Identification and characterization of neutrophil extracellular trap shapes in flow cytometry

NASA Astrophysics Data System (ADS)

Ginley, Brandon; Emmons, Tiffany; Sasankan, Prabhu; Urban, Constantin; Segal, Brahm H.; Sarder, Pinaki

2017-03-01

Neutrophil extracellular trap (NET) formation is an alternate immunologic weapon used mainly by neutrophils. Chromatin backbones fused with proteins derived from granules are shot like projectiles onto foreign invaders. It is thought that this mechanism is highly anti-microbial, aids in preventing bacterial dissemination, is used to break down structures several sizes larger than neutrophils themselves, and may have several more uses yet unknown. NETs have been implied to be involved in a wide array of systemic host immune defenses, including sepsis, autoimmune diseases, and cancer. Existing methods used to visually quantify NETotic versus non-NETotic shapes are extremely time-consuming and subject to user bias. These limitations are obstacles to developing NETs as prognostic biomarkers and therapeutic targets. We propose an automated pipeline for quantitatively detecting neutrophil and NET shapes captured using a flow cytometry-imaging system. Our method uses contrast limited adaptive histogram equalization to improve signal intensity in dimly illuminated NETs. From the contrast improved image, fixed value thresholding is applied to convert the image to binary. Feature extraction is performed on the resulting binary image, by calculating region properties of the resulting foreground structures. Classification of the resulting features is performed using Support Vector Machine. Our method classifies NETs from neutrophils without traps at 0.97/0.96 sensitivity/specificity on n = 387 images, and is 1500X faster than manual classification, per sample. Our method can be extended to rapidly analyze whole-slide immunofluorescence tissue images for NET classification, and has potential to streamline the quantification of NETs for patients with diseases associated with cancer and autoimmunity.

Taxanes: vesicants, irritants, or just irritating?

PubMed

Barbee, Meagan S; Owonikoko, Taofeek K; Harvey, R Donald

2014-01-01

Several classes of antineoplastic agents are universally referred to as vesicants with ample supporting literature. However, the literature surrounding the taxanes is controversial. While the American Society of Clinical Oncology and Oncology Nursing Society Chemotherapy Administration Safety Standards and the Chemotherapy and Biotherapy Guidelines and Recommendations for Practice identify the risks of extravasation and the parameters surrounding the infusion of known vesicants, recommend administration sites for known agents, and recommend antidotes for particular extravasation cases, they fail to provide specific recommendations for the administration of individual taxanes, or a classification system for antineoplastic agents as vesicants, irritants, or inert compounds. There is also a lack of prescribing information regarding such recommendations. The lack of a formal classification system further complicates the accurate delineation of vesicant antineoplastic agents and subsequent appropriate intravenous administration and extravasation management. There are several factors that make the classification of taxanes as vesicants or irritants challenging. Comprehensive preclinical data describing potential mechanisms of tissue damage or vesicant-like properties are lacking. Furthermore, most case reports of taxane extravasation fail to include the parameters surrounding administration, such as the concentration of medication and duration of infusion, making it difficult to set parameters for vesicant potential. Subsequently, many practitioners default to central venous administration of taxanes without evidence that such administration minimizes the risk of extravasation or improves outcomes thereof. Here, we review briefly the data surrounding taxane extravasation and potential vesicant or irritant properties, classify the taxanes, and propose a spectrum for antineoplastic agent potential to cause tissue injury that warrants clinical intervention if extravasation occurs.

Should Age at Diagnosis Be Included as an Additional Variable in the Risk of Recurrence Classification System in Patients with Differentiated Thyroid Cancer

PubMed Central

Pitoia, Fabián; Jerkovich, Fernando; Smulever, Anabella; Brenta, Gabriela; Bueno, Fernanda; Cross, Graciela

2017-01-01

Objective To evaluate the influence of age at diagnosis on the frequency of structural incomplete response (SIR) according to the modified risk of recurrence (RR) staging system from the American Thyroid Association guidelines. Patients and Methods We performed a retrospective analysis of 268 patients with differentiated thyroid cancer (DTC) followed up for at least 3 years after initial treatment (total thyroidectomy and remnant ablation). The median follow-up in the whole cohort was 74.3 months (range: 36.1-317.9) and the median age at diagnosis was 45.9 years (range: 18-87). The association between age at diagnosis and the initial and final response to treatment was assessed with analysis of variance (ANOVA). Patients were also divided into several groups considering age younger and older than 40, 50, and 60 years. Results Age at diagnosis was not associated with either an initial or final statistically significant different SIR to treatment (p = 0.14 and p = 0.58, respectively). Additionally, we did not find any statistically significant differences when the percentages of SIR considering the classification of RR were compared between different groups of patients by using several age cutoffs. Conclusions When patients are correctly risk stratified, it seems that age at diagnosis is not involved in the frequency of having a SIR at the initial evaluation or at the final follow-up, so it should not be included as an additional variable to be considered in the RR classifications. PMID:28785543

Total motile sperm count: a better indicator for the severity of male factor infertility than the WHO sperm classification system.

PubMed

Hamilton, J A M; Cissen, M; Brandes, M; Smeenk, J M J; de Bruin, J P; Kremer, J A M; Nelen, W L D M; Hamilton, C J C M

2015-05-01

Does the prewash total motile sperm count (TMSC) have a better predictive value for spontaneous ongoing pregnancy (SOP) than the World Health Organization (WHO) classification system? The prewash TMSC shows a better correlation with the spontaneous ongoing pregnancy rate (SOPR) than the WHO 2010 classification system. According to the WHO classification system, an abnormal semen analysis can be diagnosed as oligozoospermia, astenozoospermia, teratozoospermia or combinations of these and azoospermia. This classification is based on the fifth percentile cut-off values of a cohort of 1953 men with proven fertility. Although this classification suggests accuracy, the relevance for the prognosis of an infertile couple and the choice of treatment is questionable. The TMSC is obtained by multiplying the sample volume by the density and the percentage of A and B motility spermatozoa. We analyzed data from a longitudinal cohort study among unselected infertile couples who were referred to three Dutch hospitals between January 2002 and December 2006. Of the total cohort of 2476 infertile couples, only the couples with either male infertility as a single diagnosis or unexplained infertility were included (n = 1177) with a follow-up period of 3 years. In all couples a semen analysis was performed. Based on the best semen analysis if more tests were performed, couples were grouped according to the WHO classification system and the TMSC range, as described in the Dutch national guidelines for male infertility. The primary outcome measure was the SOPR, which occurred before, during or after treatments, including expectant management, intrauterine insemination, in vitro fertilization or intracytoplasmic sperm injection. After adjustment for the confounding factors (female and male age, duration and type of infertility and result of the postcoital test) the odd ratios (ORs) for risk of SOP for each WHO and TMSC group were calculated. The couples with unexplained infertility were used as reference. A total of 514 couples did and 663 couples did not achieve a SOP. All WHO groups have a lower SOPR compared with the unexplained group (ORs varying from 0.136 to 0.397). Comparing the couples within the abnormal WHO groups, there are no significant differences in SOPR, except when oligoasthenoteratozoospermia is compared with asthenozoospermia [OR 0.501 (95% CI 0.311-0.809)] and teratozoospermia [OR 0.499 (95% CI: 0.252-0.988)], and oligoasthenozoospermia is compared with asthenozoospermia [OR 0.572 (95% CI: 0.373-0.877)]. All TMSC groups have a significantly lower SOPR compared with the unexplained group (ORs varying from 0.171 to 0.461). Couples with a TMSC of <1 × 10(6) and 1-5 × 10(6) have significantly lower SOPR compared with couples with a TMSC of 5-10 × 10(6) [respectively, OR 0.371 (95% CI: 0.215-0.64) and OR 0.505 (95% CI: 0.307-0.832)]. To include all SOPs during the follow-up period of 3 years, couples were not censured at the start of treatment. Roughly, three prognostic groups can be discerned: couples with a TMSC <5, couples with a TMSC between 5 and 20 and couples with a TMSC of more than 20 × 10(6) spermatozoa. We suggest using TMSC as the method of choice to express severity of male infertility. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A New Classification System to Report Complications in Growing Spine Surgery: A Multicenter Consensus Study.

PubMed

Smith, John T; Johnston, Charles; Skaggs, David; Flynn, John; Vitale, Michael

2015-12-01

The use of growth-sparing instrumentation in pediatric spinal deformity is associated with a significant incidence of adverse events. However, there is no consistent way to report these complications, allowing for meaningful comparison of different growth-sparing techniques and strategies. The purpose of this study is to develop consensus for a new classification system to report these complications. The authors, who represent lead surgeons from 5 major pediatric spine centers, collaborated to develop a classification system to report complications associated with growing spine surgery. Following IRB approval, this system was then tested using a minimum of 10 patients from each center with at least 2-year follow-up after initial implantation of growing instrumentation to assess ease of use and consistency in reporting complications. Inclusion criteria were only patients who had surgical treatment of early onset scoliosis and did not include casting or bracing.Complications are defined as an unplanned medical event in the course of treatment that may or may not affect final outcome. Severity refers to the level of care and urgency required to treat the complication, and can be classified as device related or disease related. Severity grade (SV) I is a complication that does not require unplanned surgery, and can be corrected at the next scheduled surgery. SVII requires an unplanned surgery, with SVIIA requiring a single trip and SVIIB needing multiple trips for resolution. SVIII is a complication that substantially alters the planned course of treatment. Disease-related complications are classified as grade SVI if no hospitalization is required and grade SVII if hospitalization is required. SVIV was defined as death, either disease or device related. A total of 65 patients from 5 institutions met enrollment criteria for the study; 56 patients had at least 1 complication and 9 had no complications. There were 14 growing rods, 47 VEPTRs, ,and 4 hybrid constructs. The average age at implant was 4.7 years. There were an average of 5.4 expansions, 1.6 revisions, and 0.8 exchanges per patient. The minimum follow-up was 2 years. The most common complications were migration (60), infection (31), pneumonia (21), and instrumentation failure (23). When classified, the complications were grade I (57), grade IIA (79), grade IIB (10), and grade III (6). Well-documented uncertainty in clinical decision making in this area highlights the need for more rigorous clinical research. Reporting complications standardized for severity and impact on the course of treatment in growing spine surgery is a necessary prerequisite for meaningful comparative evaluation of different treatment options. This study shows that although complications were common, only 9% (SVIII) were severe enough to change the planned course of treatment. We propose that future studies reporting complications of different methods of growth-sparing spine surgery use this classification moving forward so that meaningful comparisons can be made between different treatment techniques.

Unravelling the myotonic dystrophy type 1 clinical spectrum: A systematic registry-based study with implications for disease classification.

PubMed

De Antonio, M; Dogan, C; Hamroun, D; Mati, M; Zerrouki, S; Eymard, B; Katsahian, S; Bassez, G

2016-10-01

The broad clinical spectrum of myotonic dystrophy type 1 (DM1) creates particular challenges for both medical care and design of clinical trials. Clinical onset spans a continuum from birth to late adulthood, with symptoms that are highly variable in both severity and nature of the affected organ systems. In the literature, this complex phenotype is divided into three grades (mild, classic, and severe) and four or five main clinical categories (congenital, infantile/juvenile, adult-onset and late-onset forms), according to symptom severity and age of onset, respectively. However, these classifications are still under discussion with no consensus thus far. While some specific clinical features have been primarily reported in some forms of the disease, there are no clear distinctions. As a consequence, no modifications in the management of healthcare or the design of clinical studies have been proposed based on the clinical form of DM1. The present study has used the DM-Scope registry to assess, in a large cohort of DM1 patients, the robustness of a classification divided into five clinical forms. Our main aim was to describe the disease spectrum and investigate features of each clinical form. The five subtypes were compared by distribution of CTG expansion size, and the occurrence and onset of the main symptoms of DM1. Analyses validated the relevance of a five-grade model for DM1 classification. Patients were classified as: congenital (n=93, 4.5%); infantile (n=303, 14.8%); juvenile (n=628, 30.7%); adult (n=694, 34.0%); and late-onset (n=326, 15.9%). Our data show that the assumption of a continuum from congenital to the late-onset form is valid, and also highlights disease features specific to individual clinical forms of DM1 in terms of symptom occurrence and chronology throughout the disease course. These results support the use of the five-grade model for disease classification, and the distinct clinical profiles suggest that age of onset and clinical form may be key criteria in the design of clinical trials when considering DM1 health management and research. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Polyp morphology: an interobserver evaluation for the Paris classification among international experts.

PubMed

van Doorn, Sascha C; Hazewinkel, Y; East, James E; van Leerdam, Monique E; Rastogi, Amit; Pellisé, Maria; Sanduleanu-Dascalescu, Silvia; Bastiaansen, Barbara A J; Fockens, Paul; Dekker, Evelien

2015-01-01

The Paris classification is an international classification system for describing polyp morphology. Thus far, the validity and reproducibility of this classification have not been assessed. We aimed to determine the interobserver agreement for the Paris classification among seven Western expert endoscopists. A total of 85 short endoscopic video clips depicting polyps were created and assessed by seven expert endoscopists according to the Paris classification. After a digital training module, the same 85 polyps were assessed again. We calculated the interobserver agreement with a Fleiss kappa and as the proportion of pairwise agreement. The interobserver agreement of the Paris classification among seven experts was moderate with a Fleiss kappa of 0.42 and a mean pairwise agreement of 67%. The proportion of lesions assessed as "flat" by the experts ranged between 13 and 40% (P<0.001). After the digital training, the interobserver agreement did not change (kappa 0.38, pairwise agreement 60%). Our study is the first to validate the Paris classification for polyp morphology. We demonstrated only a moderate interobserver agreement among international Western experts for this classification system. Our data suggest that, in its current version, the use of this classification system in daily practice is questionable and it is unsuitable for comparative endoscopic research. We therefore suggest introduction of a simplification of the classification system.

A complete electrical shock hazard classification system and its application

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

Gordon, Lloyd; Cartelli, Laura; Graham, Nicole

Current electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. As a result, this leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. We find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz power. This paper proposes a method of classifying allmore » of the electrical shock hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Lastly, the new comprehensive electrical shock hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards.« less

A complete electrical shock hazard classification system and its application

DOE PAGES

Gordon, Lloyd; Cartelli, Laura; Graham, Nicole

2018-02-08

Current electrical safety standards evolved to address the hazards of 60-Hz power that are faced primarily by electricians, linemen, and others performing facility and utility work. As a result, this leaves a substantial gap in the management of electrical hazards in Research and Development (R&D) and specialized high voltage and high power equipment. We find substantial use of direct current (dc) electrical energy, and the use of capacitors, inductors, batteries, and radiofrequency (RF) power. The electrical hazards of these forms of electricity and their systems are different than for 50/60 Hz power. This paper proposes a method of classifying allmore » of the electrical shock hazards found in all types of R&D and utilization equipment. Examples of the variation of these hazards from NFPA 70E include (a) high voltage can be harmless, if the available current is sufficiently low, (b) low voltage can be harmful if the available current/power is high, (c) high voltage capacitor hazards are unique and include severe reflex action, affects on the heart, and tissue damage, and (d) arc flash hazard analysis for dc and capacitor systems are not provided in existing standards. This work has led to a comprehensive electrical hazard classification system that is based on various research conducted over the past 100 years, on analysis of such systems in R&D, and on decades of experience. Lastly, the new comprehensive electrical shock hazard classification system uses a combination of voltage, shock current available, fault current available, power, energy, and waveform to classify all forms of electrical hazards.« less

Real-time color-based texture analysis for sophisticated defect detection on wooden surfaces

NASA Astrophysics Data System (ADS)

Polzleitner, Wolfgang; Schwingshakl, Gert

2004-10-01

We describe a scanning system developed for the classification and grading of surfaces of wooden tiles. The system uses color imaging sensors to analyse the surfaces of either hard- or softwood material in terms of the texture formed by grain lines (orientation, spatial frequency, and color), various types of colorization, and other defects like knots, heart wood, cracks, holes, etc. The analysis requires two major tracks: the assignment of a tile to its texture class (like A, B, C, 1, 2, 3, Waste), and the detection of defects that decrease the commercial value of the tile (heart wood, knots, etc.). The system was initially developed under the international IMS program (Intelligent Manufacturing Systems) by an industry consortium. During the last two years it has been further developed, and several industrial systems have been installed, and are presently used in production of hardwood flooring. The methods implemented reflect some of the latest developments in the field of pattern recognition: genetic feature selection, two-dimensional second order statistics, special color space transforms, and classification by neural networks. In the industrial scenario we describe, many of the features defining a class cannot be described mathematically. Consequently a focus was the design of a learning architecture, where prototype texture samples are presented to the system, which then automatically finds the internal representation necessary for classification. The methods used in this approach have a wide applicability to problems of inspection, sorting, and optimization of high-value material typically used in the furniture, flooring, and related wood manufacturing industries.

Degree Classification and Recent Graduates' Ability: Is There Any Signalling Effect?

ERIC Educational Resources Information Center

Di Pietro, Giorgio

2017-01-01

Research across several countries has shown that degree classification (i.e. the final grade awarded to students successfully completing university) is an important determinant of graduates' first destination outcome. Graduates leaving university with higher degree classifications have better employment opportunities and a higher likelihood of…

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

5 CFR 9701.222 - Reconsideration of classification decisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RESOURCES MANAGEMENT SYSTEM (DEPARTMENT OF HOMELAND SECURITY-OFFICE OF PERSONNEL MANAGEMENT) DEPARTMENT OF HOMELAND SECURITY HUMAN RESOURCES MANAGEMENT SYSTEM Classification Classification Process § 9701.222...

Prioritization of reproductive toxicants in unconventional oil and gas operations using a multi-country regulatory data-driven hazard assessment.

PubMed

Inayat-Hussain, Salmaan H; Fukumura, Masao; Muiz Aziz, A; Jin, Chai Meng; Jin, Low Wei; Garcia-Milian, Rolando; Vasiliou, Vasilis; Deziel, Nicole C

2018-08-01

Recent trends have witnessed the global growth of unconventional oil and gas (UOG) production. Epidemiologic studies have suggested associations between proximity to UOG operations with increased adverse birth outcomes and cancer, though specific potential etiologic agents have not yet been identified. To perform effective risk assessment of chemicals used in UOG production, the first step of hazard identification followed by prioritization specifically for reproductive toxicity, carcinogenicity and mutagenicity is crucial in an evidence-based risk assessment approach. To date, there is no single hazard classification list based on the United Nations Globally Harmonized System (GHS), with countries applying the GHS standards to generate their own chemical hazard classification lists. A current challenge for chemical prioritization, particularly for a multi-national industry, is inconsistent hazard classification which may result in misjudgment of the potential public health risks. We present a novel approach for hazard identification followed by prioritization of reproductive toxicants found in UOG operations using publicly available regulatory databases. GHS classification for reproductive toxicity of 157 UOG-related chemicals identified as potential reproductive or developmental toxicants in a previous publication was assessed using eleven governmental regulatory agency databases. If there was discordance in classifications across agencies, the most stringent classification was assigned. Chemicals in the category of known or presumed human reproductive toxicants were further evaluated for carcinogenicity and germ cell mutagenicity based on government classifications. A scoring system was utilized to assign numerical values for reproductive health, cancer and germ cell mutation hazard endpoints. Using a Cytoscape analysis, both qualitative and quantitative results were presented visually to readily identify high priority UOG chemicals with evidence of multiple adverse effects. We observed substantial inconsistencies in classification among the 11 databases. By adopting the most stringent classification within and across countries, 43 chemicals were classified as known or presumed human reproductive toxicants (GHS Category 1), while 31 chemicals were classified as suspected human reproductive toxicants (GHS Category 2). The 43 reproductive toxicants were further subjected to analysis for carcinogenic and mutagenic properties. Calculated hazard scores and Cytoscape visualization yielded several high priority chemicals including potassium dichromate, cadmium, benzene and ethylene oxide. Our findings reveal diverging GHS classification outcomes for UOG chemicals across regulatory agencies. Adoption of the most stringent classification with application of hazard scores provides a useful approach to prioritize reproductive toxicants in UOG and other industries for exposure assessments and selection of safer alternatives. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multisensory System for Fruit Harvesting Robots. Experimental Testing in Natural Scenarios and with Different Kinds of Crops

PubMed Central

Fernández, Roemi; Salinas, Carlota; Montes, Héctor; Sarria, Javier

2014-01-01

The motivation of this research was to explore the feasibility of detecting and locating fruits from different kinds of crops in natural scenarios. To this end, a unique, modular and easily adaptable multisensory system and a set of associated pre-processing algorithms are proposed. The offered multisensory rig combines a high resolution colour camera and a multispectral system for the detection of fruits, as well as for the discrimination of the different elements of the plants, and a Time-Of-Flight (TOF) camera that provides fast acquisition of distances enabling the localisation of the targets in the coordinate space. A controlled lighting system completes the set-up, increasing its flexibility for being used in different working conditions. The pre-processing algorithms designed for the proposed multisensory system include a pixel-based classification algorithm that labels areas of interest that belong to fruits and a registration algorithm that combines the results of the aforementioned classification algorithm with the data provided by the TOF camera for the 3D reconstruction of the desired regions. Several experimental tests have been carried out in outdoors conditions in order to validate the capabilities of the proposed system. PMID:25615730

Risk-informed radioactive waste classification and reclassification.

PubMed

Croff, Allen G

2006-11-01

Radioactive waste classification systems have been developed to allow wastes having similar hazards to be grouped for purposes of storage, treatment, packaging, transportation, and/or disposal. As recommended in the National Council on Radiation Protection and Measurements' Report No. 139, Risk-Based Classification of Radioactive and Hazardous Chemical Wastes, a preferred classification system would be based primarily on the health risks to the public that arise from waste disposal and secondarily on other attributes such as the near-term practicalities of managing a waste, i.e., the waste classification system would be risk informed. The current U.S. radioactive waste classification system is not risk informed because key definitions--especially that of high-level waste--are based on the source of the waste instead of its inherent characteristics related to risk. A second important reason for concluding the existing U.S. radioactive waste classification system is not risk informed is there are no general principles or provisions for exempting materials from being classified as radioactive waste which would then allow management without regard to its radioactivity. This paper elaborates the current system for classifying and reclassifying radioactive wastes in the United States, analyzes the extent to which the system is risk informed and the ramifications of its not being so, and provides observations on potential future direction of efforts to address shortcomings in the U.S. radioactive waste classification system as of 2004.

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 3 2011-10-01 2011-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 3 2012-10-01 2012-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Programs 219.303 Determining North American Industry Classification System (NAICS) codes and size standards...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 3 2014-10-01 2014-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

48 CFR 219.303 - Determining North American Industry Classification System (NAICS) codes and size standards.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 3 2013-10-01 2013-10-01 false Determining North American Industry Classification System (NAICS) codes and size standards. 219.303 Section 219.303 Federal... Determining North American Industry Classification System (NAICS) codes and size standards. Contracting...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2012 CFR

2012-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2013 CFR

2013-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2010 CFR

2010-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2014 CFR

2014-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

Code of Federal Regulations, 2011 CFR

2011-01-01

... System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce and... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... classification scheme based on regional variations in the nation's coastal zone has been developed. The...

Fitness Tracker for Weight Lifting Style Workouts

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

Wihl, B. M.

This document proposes an early, high level design for a fitness tracking system which can automatically log weight lifting style workouts. The system will provide an easy to use interface both physically through the use of several wireless wristband style motion trackers worn on the limbs, and graphically through a smartphone application. Exercise classification will be accomplished by calibration of the user’s specific motions. The system will accurately track a user’s workout, miscounting no more than one repetition in every 20, have sufficient battery life to last several hours, work with existing smartphones and have a cost similar to thosemore » of current fitness tracking devices. This document presents the mission background, current state-of-theart, stakeholders and their expectations, the proposed system’s context and concepts, implementation concepts, system requirements, first sublevel function decomposition, possible risks for the system, and a reflection on the design process.« less

Use of Deo's classification system on rock : final report.

DOT National Transportation Integrated Search

1983-01-01

A shale from a construction site on Route 23 in Wise County, Virginia, was classified using Deo's classification system, and the usefulness of the classification system was evaluated. In addition, rock that had previously been used in the development...

Can callous-unemotional traits enhance the understanding, diagnosis, and treatment of serious conduct problems in children and adolescents? A comprehensive review.

PubMed

Frick, Paul J; Ray, James V; Thornton, Laura C; Kahn, Rachel E

2014-01-01

This article provides a comprehensive review of the research on the use of callous and unemotional (CU) traits for designating an important subgroup of children and adolescents with severe conduct problems. It focuses on the etiological significance of recognizing this subgroup of youths with severe conduct problems, its implications for diagnostic classification, and the treatment implications of this research. The review highlights limitations in existing research and provides directions for future research. The available research suggests that children and adolescents with severe conduct problems and elevated CU traits show distinct genetic, cognitive, emotional, biological, environmental, and personality characteristics that seem to implicate different etiological factors underlying their behavior problems relative to other youths with severe conduct problems. Recognizing these subgroups could be critical for guiding future research on the causes of severe conduct problems in children and adolescents. Further, children and adolescents with both severe conduct problems and elevated CU traits appear to be at risk for more severe and persistent antisocial outcomes, even controlling for the severity of their conduct problems, the age of onset of their conduct problems, and common comorbid problems, which supports the clinical importance of designating this group in diagnostic classification systems. Finally, although children and adolescents with both severe conduct problems and elevated CU traits tend to respond less positively to typical interventions provided in mental health and juvenile justice settings, they show positive responses to certain intensive interventions tailored to their unique emotional and cognitive characteristics. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature.

PubMed

Wang, Xinglong; Rak, Rafal; Restificar, Angelo; Nobata, Chikashi; Rupp, C J; Batista-Navarro, Riza Theresa B; Nawaz, Raheel; Ananiadou, Sophia

2011-10-03

The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest's Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task's development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew's Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality: A systematic review and meta-analysis.

PubMed

Gagné, Mathieu; Moore, Lynne; Beaudoin, Claudia; Batomen Kuimi, Brice Lionel; Sirois, Marie-Josée

2016-03-01

The International Classification of Diseases (ICD) is the main classification system used for population-based injury surveillance activities but does not contain information on injury severity. ICD-based injury severity measures can be empirically derived or mapped, but no single approach has been formally recommended. This study aimed to compare the performance of ICD-based injury severity measures to predict in-hospital mortality among injury-related admissions. A systematic review and a meta-analysis were conducted. MEDLINE, EMBASE, and Global Health databases were searched from their inception through September 2014. Observational studies that assessed the performance of ICD-based injury severity measures to predict in-hospital mortality and reported discriminative ability using the area under a receiver operating characteristic curve (AUC) were included. Metrics of model performance were extracted. Pooled AUC were estimated under random-effects models. Twenty-two eligible studies reported 72 assessments of discrimination on ICD-based injury severity measures. Reported AUC ranged from 0.681 to 0.958. Of the 72 assessments, 46 showed excellent (0.80 ≤ AUC < 0.90) and 6 outstanding (AUC ≥ 0.90) discriminative ability. Pooled AUC for ICD-based Injury Severity Score (ICISS) based on the product of traditional survival proportions was significantly higher than measures based on ICD mapped to Abbreviated Injury Scale (AIS) scores (0.863 vs. 0.825 for ICDMAP-ISS [p = 0.005] and ICDMAP-NISS [p = 0.016]). Similar results were observed when studies were stratified by the type of data used (trauma registry or hospital discharge) or the provenance of survival proportions (internally or externally derived). However, among studies published after 2003 the Trauma Mortality Prediction Model based on ICD-9 codes (TMPM-9) demonstrated superior discriminative ability than ICISS using the product of traditional survival proportions (0.850 vs. 0.802, p = 0.002). Models generally showed poor calibration. ICISS using the product of traditional survival proportions and TMPM-9 predict mortality more accurately than those mapped to AIS codes and should be preferred for describing injury severity when ICD is used to record injury diagnoses. Systematic review and meta-analysis, level III.

Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands

PubMed Central

Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

2016-01-01

Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too. PMID:27656140

Deep Learning with Convolutional Neural Networks Applied to Electromyography Data: A Resource for the Classification of Movements for Prosthetic Hands.

PubMed

Atzori, Manfredo; Cognolato, Matteo; Müller, Henning

2016-01-01

Natural control methods based on surface electromyography (sEMG) and pattern recognition are promising for hand prosthetics. However, the control robustness offered by scientific research is still not sufficient for many real life applications, and commercial prostheses are capable of offering natural control for only a few movements. In recent years deep learning revolutionized several fields of machine learning, including computer vision and speech recognition. Our objective is to test its methods for natural control of robotic hands via sEMG using a large number of intact subjects and amputees. We tested convolutional networks for the classification of an average of 50 hand movements in 67 intact subjects and 11 transradial amputees. The simple architecture of the neural network allowed to make several tests in order to evaluate the effect of pre-processing, layer architecture, data augmentation and optimization. The classification results are compared with a set of classical classification methods applied on the same datasets. The classification accuracy obtained with convolutional neural networks using the proposed architecture is higher than the average results obtained with the classical classification methods, but lower than the results obtained with the best reference methods in our tests. The results show that convolutional neural networks with a very simple architecture can produce accurate results comparable to the average classical classification methods. They show that several factors (including pre-processing, the architecture of the net and the optimization parameters) can be fundamental for the analysis of sEMG data. Larger networks can achieve higher accuracy on computer vision and object recognition tasks. This fact suggests that it may be interesting to evaluate if larger networks can increase sEMG classification accuracy too.

Computer-aided diagnostic approach of dermoscopy images acquiring relevant features

NASA Astrophysics Data System (ADS)

Castillejos-Fernández, H.; Franco-Arcega, A.; López-Ortega, O.

2016-09-01

In skin cancer detection, automated analysis of borders, colors, and structures of a lesion relies upon an accurate segmentation process and it is an important first step in any Computer-Aided Diagnosis (CAD) system. However, irregular and disperse lesion borders, low contrast, artifacts in images and variety of colors within the interest region make the problem difficult. In this paper, we propose an efficient approach of automatic classification which considers specific lesion features. First, for the selection of lesion skin we employ the segmentation algorithm W-FCM.1 Then, in the feature extraction stage we consider several aspects: the area of the lesion, which is calculated by correlating axes and we calculate the specific the value of asymmetry in both axes. For color analysis we employ an ensemble of clusterers including K-Means, Fuzzy K-Means and Kohonep maps, all of which estimate the presence of one or more colors defined in ABCD rule and the values for each of the segmented colors. Another aspect to consider is the type of structures that appear in the lesion Those are defined by using the ell-known GLCM method. During the classification stage we compare several methods in order to define if the lesion is benign or malignant. An important contribution of the current approach in segmentation-classification problem resides in the use of information from all color channels together, as well as the measure of each color in the lesion and the axes correlation. The segmentation and classification measures have been performed using sensibility, specificity, accuracy and AUC metric over a set of dermoscopy images from ISDIS data set

SAR data for river ice monitoring. How to meet requirements?

NASA Astrophysics Data System (ADS)

Łoś, Helena; Osińska-Skotak, Katarzyna; Pluto-Kossakowska, Joanna

2017-04-01

Although river ice is a natural element of rivers regime it can lead to severe problems such as winter floods or damages of bridges and bank revetments. Services that monitor river ice condition are still often based on field observation. For several year, however, Earth observation data have become of a great interest, especially SAR images, which allows to observe ice and river condition independently of clouds and sunlight. One of requirements of an effective monitoring system is frequent and regular data acquisition. To help to meet this requirement we assessed an impact of selected SAR data parameters into automatic ice types identification. Presented work consists of two parts. The first one focuses on comparison of C-band and X-band data in terms of the main ice type detection. The second part contains an analysis of polarisation reduction from quad-pol to dual-pol data. As the main element of data processing we chose the supervised classification with maximum likelihood algorithm adapted to Wishart distribution. The classification was preceded by statistical analysis of radar signal obtained for selected ice types including separability measures. Two river were selected as areas of interest - the Peace River in Canada and the Vistula in Poland. The results shows that using data registered in both bands similar accuracy of classification into main ice types can be obtain. Differences appear with details e.g. thin initial ice. Classification results obtained from quad-pol and dual-pol data were similar while four classes were selected. With six classes, however, differences between polarisation types have been noticed.

A General Framework for Discovery and Classification in Astronomy

NASA Astrophysics Data System (ADS)

Dick, Steven J.

2012-09-01

An analysis of the discovery of 82 classes of astronomical objects reveals an extended structure of discovery, consisting of detection, interpretation and understanding, each with its own nuances and a microstructure including conceptual, technological and social roles. This is true with a remarkable degree of consistency over the last 400 years of telescopic astronomy, ranging from Galileo's discovery of satellites, planetary rings and star clusters, to the discovery of quasars and pulsars. Telescopes have served as ``engines of discovery'' in several ways, ranging from telescope size and sensitivity (planetary nebulae and spiral nebulae), to specialized detectors (TNOs) and the opening of the electromagnetic spectrum for astronomy (pulsars, pulsar planets, and most active galaxies). A few classes (radiation belts, the solar wind and cosmic rays) were initially discovered without the telescope. Classification also plays an important role in discovery. While it might seem that classification marks the end of discovery, or a post-discovery phase, in fact it often marks the beginning, even a pre-discovery phase. Nowhere is this more clearly seen than in the classification of stellar spectra, long before dwarfs, giants and supergiants were known, or their evolutionary sequence recognized. Classification may also be part of a post-discovery phase, as in the MK system of stellar classification, constructed after the discovery of stellar luminosity classes. Some classes are declared rather than detected, as in the case of gas and ice giant planets, and, infamously, Pluto as a dwarf planet. Others are inferred rather than detected, including most classes of stars.

Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

NASA Astrophysics Data System (ADS)

Chestek, Cynthia A.; Gilja, Vikash; Blabe, Christine H.; Foster, Brett L.; Shenoy, Krishna V.; Parvizi, Josef; Henderson, Jaimie M.

2013-04-01

Objective. Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.Approach. We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants. Main results. Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system. Significance. These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training, and characterization of non-stationarities such that ECoG could be a viable signal source for grasp control for amputees or individuals with paralysis.

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

Siegel, S.

An increased level of mathematical sophistication will be needed in the future to be able to handle the spectrum of information as it comes from a broad array of biological systems and other sources. Classification will be an increasingly complex and difficult issue. Several projects that are discussed are being developed by the US Department of Health and Human Services (DHHS), including a directory of risk assessment projects and a directory of exposure information resources.

Micro/nano-particles and Cells: Manipulation, Transport, and Self-assembly

DTIC Science & Technology

2014-10-23

SECURITY CLASSIFICATION OF: Technologies that control nano- and micron- sized inert as well as biological materials are crucial to realizing engineered...that control nano- and micron- sized inert as well as biological materials are crucial to realizing engineered systems that can assemble, transport, and...nano-scale particles offer several advantages as building blocks of artificial materials . The relative ease of modifying their charge states

Outcome Assessments in Children with Cerebral Palsy, Part II: Discriminatory Ability of Outcome Tools

ERIC Educational Resources Information Center

Bagley, Anita M; Gorton, George; Oeffinger, Donna; Barnes, Douglas; Calmes, Janine; Nicholson, Diane; Damiano, Diane; Abel, Mark; Kryscio, Richard; Rogers, Sarah; Tylkowski, Chester

2007-01-01

Discriminatory ability of several pediatric outcome tools was assessed relative to Gross Motor Function Classification System (GMFCS) level in patients with cerebral palsy. Five hundred and sixty-two patients (400 with diplegia, 162 with hemiplegia; 339 males, 223 females; age range 4-18y, mean 11y 1mo [SD 3y 7mo]), classified as GMFCS Levels I to…

A Model Assessment and Classification System for Men and Women in Correctional Institutions.

ERIC Educational Resources Information Center

Hellervik, Lowell W.; And Others

The report describes a manpower assessment and classification system for criminal offenders directed towards making practical training and job classification decisions. The model is not concerned with custody classifications except as they affect occupational/training possibilities. The model combines traditional procedures of vocational…

A comparison of KABCO and AIS injury severity metrics using CODES linked data.

PubMed

Burch, Cynthia; Cook, Lawrence; Dischinger, Patricia

2014-01-01

The research objective is to compare the consistency of distributions between crash assigned (KABCO) and hospital assigned (Abbreviated Injury Scale, AIS) injury severity scoring systems for 2 states. The hypothesis is that AIS scores will be more consistent between the 2 studied states (Maryland and Utah) than KABCO. The analysis involved Crash Outcome Data Evaluation System (CODES) data from 2 states, Maryland and Utah, for years 2006-2008. Crash report and hospital inpatient data were linked probabilistically and International Classification of Diseases (CMS 2013) codes from hospital records were translated into AIS codes. KABCO scores from police crash reports were compared to those AIS scores within and between the 2 study states. Maryland appears to have the more severe crash report KABCO scoring for injured crash participants, with close to 50 percent of all injured persons being coded as a level B or worse, and Utah observes approximately 40 percent in this group. When analyzing AIS scores, some fluctuation was seen within states over time, but the distribution of MAIS is much more comparable between states. Maryland had approximately 85 percent of hospitalized injured cases coded as MAIS = 1 or minor. In Utah this percentage was close to 80 percent for all 3 years. This is quite different from the KABCO distributions, where Maryland had a smaller percentage of cases in the lowest injury severity category as compared to Utah. This analysis examines the distribution of 2 injury severity metrics different in both design and collection and found that both classifications are consistent within each state from 2006 to 2008. However, the distribution of both KABCO and Maximum Abbreviated Injury Scale (MAIS) varies between the states. MAIS was found to be more consistent between states than KABCO.

Refining the classification of children with selective mutism: a latent profile analysis.

PubMed

Cohan, Sharon L; Chavira, Denise A; Shipon-Blum, Elisa; Hitchcock, Carla; Roesch, Scott C; Stein, Murray B

2008-10-01

The goal of this study was to develop an empirically derived classification system for selective mutism (SM) using parent-report measures of social anxiety, behavior problems, and communication delays. The sample consisted of parents of 130 children (ages 5-12) with SM. Results from latent profile analysis supported a 3-class solution made up of an anxious-mildly oppositional group, an anxious-communication delayed group, and an exclusively anxious group. Follow-up tests indicated significant group differences on measures of SM symptom severity, externalizing problems, and expressive/receptive language abilities. These results suggest that, although social anxiety is typically a prominent feature of SM, children with the disorder are also likely to present with communication delays and/or mild behavior problems.

Comments on new classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus and ileosigmoid knotting: necessity and utility.

PubMed

Aksungur, N; Korkut, E

2018-05-24

We read Atamanalp classification, treatment algorithm and prognosis-estimating systems for sigmoid volvulus (SV) and ileosigmoid knotting (ISK) in Colorectal Disease [1,2]. Our comments relate to necessity and utility of these new classification systems. Classification or staging systems are generally used in malignant or premalignant pathologies such as colorectal cancers [3] or polyps [4]. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Person detection and tracking with a 360° lidar system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2017-10-01

Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

Towards automated human gait disease classification using phase space representation of intrinsic mode functions

NASA Astrophysics Data System (ADS)

Pratiher, Sawon; Patra, Sayantani; Pratiher, Souvik

2017-06-01

A novel analytical methodology for segregating healthy and neurological disorders from gait patterns is proposed by employing a set of oscillating components called intrinsic mode functions (IMF's). These IMF's are generated by the Empirical Mode Decomposition of the gait time series and the Hilbert transformed analytic signal representation forms the complex plane trace of the elliptical shaped analytic IMFs. The area measure and the relative change in the centroid position of the polygon formed by the Convex Hull of these analytic IMF's are taken as the discriminative features. Classification accuracy of 79.31% with Ensemble learning based Adaboost classifier validates the adequacy of the proposed methodology for a computer aided diagnostic (CAD) system for gait pattern identification. Also, the efficacy of several potential biomarkers like Bandwidth of Amplitude Modulation and Frequency Modulation IMF's and it's Mean Frequency from the Fourier-Bessel expansion from each of these analytic IMF's has been discussed for its potency in diagnosis of gait pattern identification and classification.

Perspectives on current tumor-node-metastasis (TNM) staging of cancers of the colon and rectum.

PubMed

Hu, Huankai; Krasinskas, Alyssa; Willis, Joseph

2011-08-01

Improvements in classifications of cancers based on discovery and validation of important histopathological parameters and new molecular markers continue unabated. Though still not perfect, recent updates of classification schemes in gastrointestinal oncology by the American Joint Commission on Cancer (tumor-node-metastasis [TNM] staging) and the World Health Organization further stratify patients and guide optimization of treatment strategies and better predict patient outcomes. These updates recognize the heterogeneity of patient populations with significant subgrouping of each tumor stage and use of tumor deposits to significantly "up-stage" some cancers; change staging parameters for subsets of IIIB and IIIC cancers; and introduce of several new subtypes of colon carcinomas. By the nature of the process, recent discoveries that are important to improving even routine standards of patient care, especially new advances in molecular medicine, are not incorporated into these systems. Nonetheless, these classifications significantly advance clinical standards and are welcome enhancements to our current methods of cancer reporting. Copyright © 2011 Elsevier Inc. All rights reserved.

Hierarchical classification of dynamically varying radar pulse repetition interval modulation patterns.

PubMed

Kauppi, Jukka-Pekka; Martikainen, Kalle; Ruotsalainen, Ulla

2010-12-01

The central purpose of passive signal intercept receivers is to perform automatic categorization of unknown radar signals. Currently, there is an urgent need to develop intelligent classification algorithms for these devices due to emerging complexity of radar waveforms. Especially multifunction radars (MFRs) capable of performing several simultaneous tasks by utilizing complex, dynamically varying scheduled waveforms are a major challenge for automatic pattern classification systems. To assist recognition of complex radar emissions in modern intercept receivers, we have developed a novel method to recognize dynamically varying pulse repetition interval (PRI) modulation patterns emitted by MFRs. We use robust feature extraction and classifier design techniques to assist recognition in unpredictable real-world signal environments. We classify received pulse trains hierarchically which allows unambiguous detection of the subpatterns using a sliding window. Accuracy, robustness and reliability of the technique are demonstrated with extensive simulations using both static and dynamically varying PRI modulation patterns. Copyright © 2010 Elsevier Ltd. All rights reserved.

Landscape object-based analysis of wetland plant functional types: the effects of spatial scale, vegetation classes and classifier methods

NASA Astrophysics Data System (ADS)

Dronova, I.; Gong, P.; Wang, L.; Clinton, N.; Fu, W.; Qi, S.

2011-12-01

Remote sensing-based vegetation classifications representing plant function such as photosynthesis and productivity are challenging in wetlands with complex cover and difficult field access. Recent advances in object-based image analysis (OBIA) and machine-learning algorithms offer new classification tools; however, few comparisons of different algorithms and spatial scales have been discussed to date. We applied OBIA to delineate wetland plant functional types (PFTs) for Poyang Lake, the largest freshwater lake in China and Ramsar wetland conservation site, from 30-m Landsat TM scene at the peak of spring growing season. We targeted major PFTs (C3 grasses, C3 forbs and different types of C4 grasses and aquatic vegetation) that are both key players in system's biogeochemical cycles and critical providers of waterbird habitat. Classification results were compared among: a) several object segmentation scales (with average object sizes 900-9000 m2); b) several families of statistical classifiers (including Bayesian, Logistic, Neural Network, Decision Trees and Support Vector Machines) and c) two hierarchical levels of vegetation classification, a generalized 3-class set and more detailed 6-class set. We found that classification benefited from object-based approach which allowed including object shape, texture and context descriptors in classification. While a number of classifiers achieved high accuracy at the finest pixel-equivalent segmentation scale, the highest accuracies and best agreement among algorithms occurred at coarser object scales. No single classifier was consistently superior across all scales, although selected algorithms of Neural Network, Logistic and K-Nearest Neighbors families frequently provided the best discrimination of classes at different scales. The choice of vegetation categories also affected classification accuracy. The 6-class set allowed for higher individual class accuracies but lower overall accuracies than the 3-class set because individual classes differed in scales at which they were best discriminated from others. Main classification challenges included a) presence of C3 grasses in C4-grass areas, particularly following harvesting of C4 reeds and b) mixtures of emergent, floating and submerged aquatic plants at sub-object and sub-pixel scales. We conclude that OBIA with advanced statistical classifiers offers useful instruments for landscape vegetation analyses, and that spatial scale considerations are critical in mapping PFTs, while multi-scale comparisons can be used to guide class selection. Future work will further apply fuzzy classification and field-collected spectral data for PFT analysis and compare results with MODIS PFT products.

Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

PubMed

Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M

2012-05-01

In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.

Evolutionary fuzzy ARTMAP neural networks for classification of semiconductor defects.

PubMed

Tan, Shing Chiang; Watada, Junzo; Ibrahim, Zuwairie; Khalid, Marzuki

2015-05-01

Wafer defect detection using an intelligent system is an approach of quality improvement in semiconductor manufacturing that aims to enhance its process stability, increase production capacity, and improve yields. Occasionally, only few records that indicate defective units are available and they are classified as a minority group in a large database. Such a situation leads to an imbalanced data set problem, wherein it engenders a great challenge to deal with by applying machine-learning techniques for obtaining effective solution. In addition, the database may comprise overlapping samples of different classes. This paper introduces two models of evolutionary fuzzy ARTMAP (FAM) neural networks to deal with the imbalanced data set problems in a semiconductor manufacturing operations. In particular, both the FAM models and hybrid genetic algorithms are integrated in the proposed evolutionary artificial neural networks (EANNs) to classify an imbalanced data set. In addition, one of the proposed EANNs incorporates a facility to learn overlapping samples of different classes from the imbalanced data environment. The classification results of the proposed evolutionary FAM neural networks are presented, compared, and analyzed using several classification metrics. The outcomes positively indicate the effectiveness of the proposed networks in handling classification problems with imbalanced data sets.

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy.

PubMed

Welikala, R A; Fraz, M M; Dehmeshki, J; Hoppe, A; Tah, V; Mann, S; Williamson, T H; Barman, S A

2015-07-01

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis. Copyright © 2015 Elsevier Ltd. All rights reserved.