Evolutionary-driven support vector machines for determining the degree of liver fibrosis in chronic hepatitis C

Artificial Intelligence in Medicine

Volumn 51, Issue 1, 2011, Pages 53-65

  Stoean, Ruxandra ^a   Stoean, Catalin ^a   Lupsor, Monica ^b   Stefanescu, Horia ^b   Badea, Radu ^b  

^a UNIVERSITY OF CRAIOVA   (Romania)

^b IULIU HATIEGANU UNIVERSITY OF MEDICINE AND PHARMACY   (Romania)

Author keywords

Chronic hepatitis C; Evolutionary algorithms; Feature selection; Formula for class prediction; Liver fibrosis stage; Support vector machines

Indexed keywords

CHRONIC HEPATITIS; CLASS PREDICTION; FEATURE SELECTION; LIVER FIBROSIS STAGE; SUPPORT VECTOR;

ARTIFICIAL INTELLIGENCE; DECISION MAKING; FEATURE EXTRACTION; FORECASTING; LIVER; OPTIMIZATION; SUPPORT VECTOR MACHINES; VECTORS;

EVOLUTIONARY ALGORITHMS;

ARTICLE; ARTIFICIAL INTELLIGENCE; DISEASE CLASSIFICATION; EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM; HEPATITIS C; LIVER FIBROSIS; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUTOMATION, LABORATORY; BIOPSY; ELASTICITY IMAGING TECHNIQUES; FEMALE; HEPATITIS C, CHRONIC; HUMANS; LIVER; LIVER CIRRHOSIS; MALE; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SEVERITY OF ILLNESS INDEX;

EID: 78650938513     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2010.06.002     Document Type: Article

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