Feature selection and syndrome prediction for liver cirrhosis in traditional Chinese medicine

Computer Methods and Programs in Biomedicine

Volumn 95, Issue 3, 2009, Pages 249-257

  Wang, Yan ^a   Ma, Lizhuang ^a,b   Liu, Ping ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b SHANGHAI UNIVERSITY OF TRADITIONAL CHINESE MEDICINE   (China)

Author keywords

Feature selection; Syndrome prediction; TCMSP; Traditional Chinese medicine

Indexed keywords

APPLICATION PROSPECT; CLASS LABELS; CLINICAL DECISION; DATA MINING ALGORITHM; DATA SETS; FEATURE SELECTION; INFORMATION GAIN METHOD; LIVER CIRRHOSIS; LUNG CANCER; MAJORITY VOTING; MULTI-VIEW; NOVEL METHODS; SECOND PHASE; SYNDROME PREDICTION; TCMSP; TRADITIONAL CHINESE MEDICINE; TWO PHASIS;

DATA MINING; INFORMATION MANAGEMENT; LIVER; MINING;

MEDICINE;

ACCURACY; ARTICLE; CHINESE MEDICINE; CLINICAL DECISION MAKING; DAMP HEAT SMOLDERING SYNDROME; DATA MINING; HUMAN; INFORMATION PROCESSING; LIVER CIRRHOSIS; LIVER KIDNEY YIN DEFICIENCY SYNDROME; MAJOR CLINICAL STUDY; METHODOLOGY; PHYSICIAN; PREDICTION; STASIS HEAT SMOLDERING SYNDROME; SYNDROME; TRADITIONAL CHINESE MEDICINE SYNDROME PREDICTION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; LIVER CIRRHOSIS; MEDICINE, CHINESE TRADITIONAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; SYNDROME;

EID: 67649394161     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2009.03.004     Document Type: Article

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