A fuzzy-genetic approach to breast cancer diagnosis

Carlos Andrés Pe, Moshe Sipper

Research output: Contribution to journalArticlepeer-review

158 Scopus citations


The automatic diagnosis of breast cancer is an important, real-world medical problem. In this paper we focus on the Wisconsin breast cancer diagnosis (WBCD) problem, combining two methodologies - fuzzy systems and evolutionary algorithms - so as to automatically produce diagnostic systems. We find that our fuzzy-genetic approach produces systems exhibiting two prime characteristics: first, they attain high classification performance (the best shown to date), with the possibility of attributing a confidence measure to the output diagnosis; second, the resulting systems involve a few simple rules, and are therefore (human-) interpretable.

Original languageEnglish
Pages (from-to)131-155
Number of pages25
JournalArtificial Intelligence in Medicine
Issue number2
StatePublished - 1 Oct 1999
Externally publishedYes


  • Breast cancer diagnosis
  • Fuzzy systems
  • Genetic algorithms

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Artificial Intelligence


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