Prediction of Malignant Breast Lesions from MRI Features. A Comparison of Artificial Neural Network and Logistic Regression Techniques

Academic Radiology

Volumn 16, Issue 7, 2009, Pages 842-851

  McLaren, Christine E ^a   Chen, Wen Pin ^a   Nie, Ke ^a   Su, Min Ying ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Artificial Neural Network; Breast Cancer Diagnostic Model; Logistic Regression

Indexed keywords

GADODIAMIDE;

ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BENIGN TUMOR; BREAST CANCER; BREAST LESION; CANCER CLASSIFICATION; CLINICAL FEATURE; CONFIDENCE INTERVAL; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; DISEASE CLASSIFICATION; ENERGY; ENTROPY; HUMAN; INTERMETHOD COMPARISON; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; MORPHOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; RECEIVER OPERATING CHARACTERISTIC;

ALGORITHMS; BREAST NEOPLASMS; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LOGISTIC MODELS; MAGNETIC RESONANCE IMAGING; MIDDLE AGED; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 67349120047     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2009.01.029     Document Type: Article

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