Fuzzy Expert System for Diabetes Using Fuzzy Verdict Mechanism

The fuzzy logic and expert system is an important technique to enhance the machine learning reasoning. In this paper, we propose a fuzzy expert system framework which constructs large scale knowledge based system effectively for diabetes. The knowledge is constructed by using the fuzzification to convert crisp values into fuzzy values. By applying the fuzzy verdict mechanism, diagnosis of diabetes becomes simple for medical practitioners. Fuzzy verdict mechanism uses triangular membership function with mamdani's inference. Defuzzification method is adopted to convert the fuzzy values into crisp values. The result of the proposed method is compared with earlier method using accuracy as metrics. The proposed fuzzy expert system can work more effectively for diabetes application and also improves the accuracy of fuzzy expert system.