Association, statistical, mathematical and neural approaches for mining breast cancer patterns

P. C. Pendharkar, J. A. Rodger, G. J. Yaverbaum, N. Herman, M. Benner

Research output: Contribution to journalArticle

77 Scopus citations

Abstract

Using several association and classification approaches to study breast cancer patterns, this study illustrates how these approaches can be used to predict and diagnose the occurrence of breast cancer. The results of the study, based on data obtained from a large medical facility in western Pennsylvania, show that data mining can be a viable tool for breast cancer diagnosis.

Original languageEnglish (US)
Pages (from-to)223-232
Number of pages10
JournalExpert Systems With Applications
Volume17
Issue number3
DOIs
StatePublished - Jan 1 1999

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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