Classifier design for computer-aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiers

Medical Physics

Volumn 26, Issue 12, 1999, Pages 2654-2668

  Chan, Heang Ping ^a   Sahiner, Berkman ^a   Wagner, Robert F ^b   Petrick, Nicholas ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

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

Author keywords

Classifier design; Computer aided diagnosis; Feature space dimensionality; Linear classifier; Neural network; Quadratic classifier; ROC analysis; Sample size

Indexed keywords

BACKPROPAGATION; COMPUTER AIDED ANALYSIS; COMPUTER AIDED DIAGNOSIS; COMPUTER AIDED NETWORK ANALYSIS; COMPUTER NETWORKS; COVARIANCE MATRIX; NEURAL NETWORKS; NORMAL DISTRIBUTION; SAMPLING;

CLASSIFIER DESIGN; FEATURE SPACE; LINEAR CLASSIFIERS; QUADRATIC CLASSIFIERS; ROC ANALYSIS; SAMPLE SIZES;

CLASSIFICATION (OF INFORMATION);

ACCURACY; ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; PERFORMANCE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SAMPLE; SIGNAL NOISE RATIO;

EID: 0033461791     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.598805     Document Type: Article

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