A neural network approach to breast cancer diagnosis as a constraint satisfaction problem

Medical Physics

Volumn 28, Issue 5, 2001, Pages 804-811

  Tourassi, Georgia D ^a   Markey, Mia K ^b   Lo, Joseph Y ^c   Floyd, Carey E ^c  

^a DUKE UNIVERSITY MEDICAL CENTER   (United States)

^b Duke University   (United States)

^c DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Breast cancer; Constraint satisfaction; Data mining; Neural networks

Indexed keywords

ASSOCIATIVE PROCESSING; ASSOCIATIVE STORAGE; CONSTRAINT SATISFACTION PROBLEMS; DATA MINING; DIAGNOSIS; DISEASES; PROBLEM SOLVING;

BACKPROPAGATION ARTIFICIAL NEURAL NETWORKS; BREAST CANCER; BREAST CANCER DIAGNOSIS; CONSTRAINT SATISFACTION; CONSTRAINT-SATISFACTION PROBLEMS; DIAGNOSTIC DECISIONS; MAMMOGRAPHIC; NEURAL-NETWORKS; PATIENT HISTORY; RECEIVER OPERATING CHARACTERISTICS ANALYSIS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; ASSOCIATION; ASSOCIATIVE MEMORY; BREAST BIOPSY; BREAST CANCER; CANCER DIAGNOSIS; DATA BASE; HUMAN; MAMMOGRAPHY; PRIORITY JOURNAL; TUMOR BIOPSY;

EID: 0035006815     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.1367861     Document Type: Article

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