HYBRID EXPERT SYSTEM FOR DECISION SUPPORT IN THE MEDICAL AREA

The Knowledge Acquisition (KA) process consists on extracting and representing knowledge of a domain expert. In this work, one of the main goals was to minimise the intrinsic difficulties of the KA process. We have obtained all possible rules from the domain expert in a short time and also a set of examples. Moreover, we developed a Hybrid Expert System (HES) to minimise the problems of the KA task using a new methodology. Building this kind of hybrid architecture has led us to use many tools: symbolic paradigm, connectionist paradigm, fuzzy logic and, Genetic Algorithm (GA). The methodology developed to HES was tested for two cases: toy and real problems (e.g., a medical domain area).