Combining evolutionary and fuzzy techniques in medical diagnosis

Carlos Andrés Pena-Reyes, Moshe Sipper

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


In this chapter we focus on the Wisconsin breast cancer diagnosis (WBCD) problem, combining two methodologies—fuzzy systems and evolutionary algorithms—to automatically produce diagnostic systems. We present two hybrid approaches: (1) a fuzzy-genetic algorithm, and (2) Fuzzy CoCo, a novel cooperative coevolutionary approach to fuzzy modeling. Both methods produce systems exhibiting high classification performance, and which are also human-interpretable. Fuzzy CoCo obtains higher-performance systems than the standard fuzzy-genetic approach while using less computational effort.
Original languageEnglish GB
Title of host publicationComputational Intelligence Processing in Medical Diagnosis
EditorsM. Schmitt, H.-N. Teodorescu, A. Jain, S. Jain
Place of PublicationHeidelberg
Number of pages36
ISBN (Print)978-3-7908-2509-1
StatePublished - 2002


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