Mixture classification model based on clinical markers for breast cancer prognosis

Artificial Intelligence in Medicine

Volumn 48, Issue 2-3, 2010, Pages 129-137

  Zeng, T ^a   Liu, J ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Breast cancer prognosis; Clinical marker; Mixture classification model; Rough set; Support vector machine

Indexed keywords

BREAST CANCER; BREAST CANCER CELLS; BREAST CANCER PROGNOSIS; BREAST CANCER TUMORS; BREAST TUMOR; CANCER PROGNOSIS; CANCER TREATMENT; CLASSIFICATION METHODS; CLASSIFICATION MODELS; CLINICAL APPLICATION; CLINICAL DATA; COMPARISON RESULT; CROSS VALIDATION; DATA SETS; ENSEMBLE CLASSIFICATION; ENSEMBLE MODELS; EXISTING METHOD; FORMAL DESCRIPTION; GENE EXPRESSION DATA; HIGH QUALITY; MAPPING FUNCTIONS; MICROARRAY EXPERIMENTS; MICROARRAY TECHNOLOGIES; NODE-NEGATIVE; POOR PERFORMANCE; PREDICTION ACCURACY; PROGNOSIS MODELS; PROGNOSIS PREDICTION; ROUGH SET; SECOND LAYER; STRICT CONSTRAINT; SVM CLASSIFIERS; TEST SETS; TWO LAYERS; VOTING PROCESS;

CLASSIFIERS; FORECASTING; GENE EXPRESSION; GROUP TECHNOLOGY; INFORMATION USE; MIXTURES; ROUGH SET THEORY; STATISTICAL TESTS; SUPPORT VECTOR MACHINES; TUMORS; VECTORS;

EXPERIMENTS;

ACCURACY; ARTICLE; BREAST CANCER; CANCER CLASSIFICATION; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; DATA ANALYSIS; DISEASE MARKER; HUMAN; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; REFERENCE DATABASE; ROUGH SET; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; DATA MINING; DATABASES, GENETIC; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; GENETIC MARKERS; HUMANS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; PROGNOSIS; REPRODUCIBILITY OF RESULTS; SYSTEMS BIOLOGY; SYSTEMS INTEGRATION; TUMOR MARKERS, BIOLOGICAL;

EID: 77951630294     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2009.07.008     Document Type: Article

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