Computer Aided Breast Cancer Diagnosis.

Abstract

The long range goal of this project is to improve the accuracy and consistency of breast cancer diagnosis by developing a Computer Aided Diagnosis (CAD) system for early prediction of breast cancer from the patients' mammographic findings and medical history. Our total case database is over 500. We have investigated two alternative network architectures for predicting malignancy: a genetic algorithm approach, and an adaptive learning rule for the feed-forward network.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1996
Accession Number
ADA325798

Entities

People

  • Carey E. Floyd

Organizations

  • Duke University Hospital

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Breast Cancer
  • Cancer
  • Computer-Aided Diagnosis
  • Computers
  • Computing System Architectures
  • Consistency
  • Databases
  • Genetic Algorithms
  • Heuristic Methods
  • Learning
  • Neoplasms
  • Network Architecture

Fields of Study

  • Medicine

Readers

  • Computer Science.
  • Neural Network Machine Learning.
  • Women's Health and Cancer Risk Research: African American Women and Pregnancy Outcomes.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology
  • Biotechnology - Cancer Biotech