Accession Number:

ADA411710

Title:

Prognostic Comparison of Statistical, Neural and Fuzzy Methods of Analysis of Breast Cancer Image Cytometric Data

Descriptive Note:

Conference paper

Corporate Author:

COVENTRY UNIV (UNITED KINGDOM) SCHOOL OF MATHEMATICAL AND INFORMATION SCIENCES

Report Date:

2001-10-25

Pagination or Media Count:

5.0

Abstract:

This paper aims to predict a breast cancer patients prognosis and to determine the most important prognostic factors by means of logistic regression LR as a conventional statistical method, multilayer backpropagation neural network MLBPNN as a neural network method, fuzzy K-nearest neighbor algorithm FK-NN as a fuzzy logic method, a fuzzy measurement based on the FK-NN and the leave-one-out error method. The data used for breast cancer prognostic prediction were collected from 100 women who were clinically diagnosed with breast disease in the form of carcinoma or benign conditions.

Subject Categories:

  • Medicine and Medical Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE