Accurate prediction of coronary artery disease using reliable diagnosis system

Journal of Medical Systems

Volumn 36, Issue 5, 2012, Pages 3353-3373

  Mandal, Indrajit ^a   Sairam, N ^a  

^a SASTRA UNIVERSITY   (India)

Author keywords

Bayesian network; Coronary artery disease; Principal components method; Quality; Software reliability

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; CLASSIFIER; CONTROLLED STUDY; CORONARY ARTERY DISEASE; CORRESPONDENCE ANALYSIS; DECISION TREE; DIAGNOSTIC ACCURACY; DIAGNOSTIC ERROR; DIAGNOSTIC VALUE; EXPERT SYSTEM; GENETIC ALGORITHM; HUMAN; KERNEL METHOD; LEARNING ALGORITHM; MACHINE LEARNING; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY; RANDOM FOREST; STUDENT T TEST; SUPPORT VECTOR MACHINE; AGE; ALGORITHM; BAYES THEOREM; BLOOD; BLOOD PRESSURE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; ELECTROCARDIOGRAPHY; GLUCOSE BLOOD LEVEL; METHODOLOGY; REPRODUCIBILITY; RISK ASSESSMENT; SEX DIFFERENCE;

CHOLESTEROL;

AGE FACTORS; ALGORITHMS; BAYES THEOREM; BLOOD GLUCOSE; BLOOD PRESSURE; CHOLESTEROL; CORONARY ARTERY DISEASE; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROCARDIOGRAPHY; HUMANS; NEURAL NETWORKS (COMPUTER); PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; RISK ASSESSMENT; SEX FACTORS; SOFTWARE DESIGN;

EID: 84867292482     PISSN: 01485598     EISSN: 1573689X     Source Type: Journal    
DOI: 10.1007/s10916-012-9828-0     Document Type: Article

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