Fuzzy Decision Trees in medical decision Making Support System

Abstract

Decision Making Support System based on Fuzzy Logic is considered in this paper for oncology disease diagnosis. The decision making procedure corresponds to the recognition (classification) of the new case by analyzing a set of instances (already solved cases) for which classes are known. Ontology (solved cases) is defined as Fuzzy Classification Rules that are formed by different Fuzzy Decision Trees. Three types of Fuzzy Decision Trees (Non-ordered, ordered and Stable) are considered in the paper. Induction of these Fuzzy Decision Trees is based on Cumulative Information Estimates. The proposed approach is implemented based on medical problem benchmark with real clinical data for breast cancer diagnosis. © 2012 Polish Info Processing Socit.