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 the highest classification performance shown to date, and which are also (human-)interpretable.
|Pages||I-135 - I-139|
|State||Published - 1 Dec 1999|
|Event||Proceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99 - Seoul, South Korea|
Duration: 22 Aug 1999 → 25 Aug 1999
|Conference||Proceedings of the 1999 IEEE International Fuzzy Systems Conference, FUZZ-IEEE'99|
|City||Seoul, South Korea|
|Period||22/08/99 → 25/08/99|