Fuzzy Expert System for Diagnosis of Diabetes Using Fuzzy Determination Mechanism

Abstract

A Fuzzy Expert System is simply an expert system used in field of medicine, uses a collection of fuzzy membership functions and rules, to analysis the diabetes data. By applying the fuzzy determination mechanism the diagnosis of diabetes becomes simple for medical practitioners. The fuzzy determination mechanism consists of fuzzy inference, implication and aggregation. The knowledge is constructed by using the fuzzification to convert crisp values into fuzzy values for the diagnosis of diabetes. This mechanism contains set of rules with fuzzy operators T-norm and T-Conorm. Defuzzification step converts the resulting fuzzy set into crisp values. The proposed algorithm can work more effectively for diabetes application and also improves the accuracy. The result of the proposed methods is compared with earlier method using accuracy as metrics.