Diagnosing breast cancer from FNAs: Variable relevance in neural network and logistic regression models

Studies in Health Technology and Informatics

Volumn 52, Issue , 1998, Pages 537-540

  Ohno Machado, Lucila ^a   Bialek, Donald ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

Author keywords

Breast Cancer; Logistic Regression; Neural Networks

Indexed keywords

COMPUTER AIDED DIAGNOSIS; DISEASES; NEURAL NETWORKS;

BREAST CANCER; CLASSIFICATION MODELS; FINE-NEEDLE ASPIRATIONS; LOGISTIC REGRESSION MODELING; LOGISTIC REGRESSION MODELS; LOGISTIC REGRESSIONS; NEURAL NETWORK MODEL; SELECTION OF VARIABLES;

REGRESSION ANALYSIS;

ANALYSIS OF VARIANCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST TUMOR; COMPARATIVE STUDY; FEMALE; HUMAN; MULTIVARIATE ANALYSIS; NEEDLE BIOPSY; PATHOLOGY; STATISTICAL MODEL;

ANALYSIS OF VARIANCE; BIOPSY, NEEDLE; BREAST NEOPLASMS; FEMALE; HUMANS; LOGISTIC MODELS; MULTIVARIATE ANALYSIS; NEURAL NETWORKS (COMPUTER);

EID: 84887791264     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: 10.3233/978-1-60750-896-0-537     Document Type: Conference Paper

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