Prediction of Coronary Heart Disease Using Fuzzy Logic: Case Study in Albania

Coronary Heart Disease causes many deaths in the world's population. Unfortunately, this issue of concern will become more and more troublesome in the future. This paper presents a fuzzy logic model for predicting coronary heart disease. This model has been developed with 7 input variables, and 1 output variable, that was implemented for 30 patients in Albania. In this research, the fuzzy logic toolbox is used for this model. Fuzzy model inputs are considered: the blood pressure, cholesterol, physical activity, diabetes, age, BMI, and smoking, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen appropriately. The centroid method is used for defuzzification. The database is taken from University Hospital Centre "Mother Teresa" in Tirana, Albania.