Impacts of Predictive Genomic Classifier Performance on Subpopulation-Specific Treatment Effects Assessment

Statistics in Biosciences

Volumn 8, Issue 1, 2016, Pages 129-158

  Wang, Sue Jane ^a   Li, Ming Chung ^b  

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

^b NATIONAL CANCER INSTITUTE   (United States)

Author keywords

Composite genomic biomarker; Cross validated machine learning voting algorithm; Pharmacogenomics; Positive or negative predictive value; Prevalence; Subpopulation treatment effect

Indexed keywords

BIOLOGICAL MARKER;

ALGORITHM; ARTICLE; BREIMANS MACHINE LEARNING; CANCER CHEMOTHERAPY; CONTROLLED STUDY; GENE EXPRESSION; GENE INTERACTION; HUMAN; MACHINE LEARNING; MEASUREMENT ACCURACY; MICROARRAY ANALYSIS; NON SMALL CELL LUNG CANCER; PHARMACOGENOMICS; PREDICTIVE VALUE; PREVALENCE; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL; SENSITIVITY AND SPECIFICITY; SIMULATION; TREATMENT OUTCOME; VALIDATION PROCESS;

EID: 84878413342     PISSN: 18671764     EISSN: 18671772     Source Type: Journal    
DOI: 10.1007/s12561-013-9092-y     Document Type: Article

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