Back
A fuzzy-genetic approach to breast cancer diagnosis.
Journal article

A fuzzy-genetic approach to breast cancer diagnosis.

  • Pena-Reyes CA Logic Systems Laboratory, Swiss Federal Institute of Technology, IN-Ecublens, CH-1015, Lausanne, Switzerland. carlos.pena@di.epfl.ch
  • Sipper M
  • 1999-10-13
Published in:
  • Artificial intelligence in medicine. - 1999
Algorithms
Artificial Intelligence
Breast Neoplasms
Databases, Factual
Diagnosis, Computer-Assisted
Female
Fuzzy Logic
Genome
Humans
Models, Biological
English 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.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://folia.unifr.ch/global/documents/45343
Statistics
Document views: 50 File downloads: