DESIGN OF A FUZZY MODEL FOR THALASSEMIA DISEASE DIAGNOSIS: USING MAMDANI TYPE FUZZY INFERENCE SYSTEM (FIS)

Objective: Diagnosis process of Thalassemia requires several types of medical test, and results of this test together identify the stage of Thalassemia. The objective of this study is to design a Fuzzy Inference System to diagnose the severity of the Thalassemia disease of a patient by using Fuzzy Logic.Methods: In this paper, a new approach based on fuzzy inference system was presented for prediction of Thalassemia disease in patients. The proposed Fuzzy model combined the expert's knowledge and the fuzzy logic approach which is then combined in fuzzy rule base to diagnose the presence of the disease. The performances of the system graphically represented by fuzzy inference system tools in MATLAB8.4.Results: It was found that our program matched the doctor's diagnosis in 12 cases perfectly. The other 3 were marginally off. This results with an accuracy of about 80 %.Conclusion: The result suggests that the model provides the most effective way to identify Thalassemia type in patients. The results in this work can be obtained by a simple and inexpensive method. This would generate, in economic terms, significant savings.Keywords: CBC Test, Fuzzy Logic, Mamdani Fuzzy Inference System, Thalassemia Diseas