Complementary use of Fuzzy Decision Trees and Augmented Fuzzy Cognitive Maps for Decision Making in Medical Informatics

This work focuses on the formalization of a Fuzzy Cognitive Map based decision support system using complementary the fuzzy decision tree method for producing fuzzy If-Then rules (extracted from data) accompanied with the available experts´ knowledge. The proposed approach is applied to build a Fuzzy Cognitive Map based decision support system (FCM- DSS) used in medical informatics. In this approach, an augmented FCM-DSS is developed combining knowledge from experts and fuzzy rules generated from data using fuzzy decision tree based extraction method. In this research work, our scope is to introduce a new methodology for medical decision making tasks using the soft computing technique of FCMs, producing an augmented FCM decision support system. The proposed approach is implemented in a well-known benchmark medical problem with real clinical data for thyroid disease diagnosis. The first results are very promising and better than other fuzzy-based computational intelligent techniques.