A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases

Journal of Biomedical Informatics

Volumn 58, Issue , 2015, Pages S92-S102

  Kotfila, Christopher ^a   Uzuner, Özlem ^a  

^a STATE UNIVERSITY OF NEW YORK   (United States)

Author keywords

Classification; Natural language processing; Phenotyping

Indexed keywords

BIOINFORMATICS; COMPUTATIONAL LINGUISTICS; COMPUTER AIDED DESIGN; DATA MINING; LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS; SUPPORT VECTOR MACHINES; VECTOR SPACES;

CARDIO-VASCULAR DISEASE; CLASSIFICATION TECHNIQUE; CLASSIFIER PERFORMANCE; NATURAL LANGUAGE PROCESSING; PHENOTYPE IDENTIFICATION; PHENOTYPING; STATISTICAL SIGNIFICANCE; SUPPORT VECTOR MACHINE (SVMS);

CLASSIFICATION (OF INFORMATION);

ARTICLE; CONTROLLED STUDY; CORONARY ARTERY ATHEROSCLEROSIS; DIABETES MELLITUS; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; FAMILY HISTORY; HUMAN; HYPERLIPIDEMIA; HYPERTENSION; KERNEL METHOD; MEDICAL HISTORY; NATURAL LANGUAGE PROCESSING; OBESITY; PRIORITY JOURNAL; RADIAL BASIS FUNCTION; SUPPORT VECTOR MACHINE; SYSTEMATIC ERROR; VALIDATION PROCESS; AUTOMATED PATTERN RECOGNITION; CARDIOVASCULAR DISEASES; CLINICAL DECISION SUPPORT SYSTEM; COMPUTER ASSISTED DIAGNOSIS; DATA MINING; ELECTRONIC HEALTH RECORD; NEW YORK; ORGANIZATION AND MANAGEMENT; PHENOTYPE; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICS AND NUMERICAL DATA;

CARDIOVASCULAR DISEASES; DATA MINING; DECISION SUPPORT SYSTEMS, CLINICAL; DIABETES MELLITUS; DIAGNOSIS, COMPUTER-ASSISTED; ELECTRONIC HEALTH RECORDS; HUMANS; NATURAL LANGUAGE PROCESSING; NEW YORK; OBESITY; PATTERN RECOGNITION, AUTOMATED; PHENOTYPE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

EID: 84940703244     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2015.07.016     Document Type: Article

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