Improved Coronary Heart Disease (CHD) Occurrence Early Prediction

Abstract

this project aims to predict the incidence of coronary heart disease in people who did not know the factors associated with the development of this disease. Based on the analysis of several factors associated with this disease, the first step is to examine the effect of etiological factors on disease severity and use fuzzy logic to establish organ functions and factor classification rules. This project relied on applying fuzzy logic to binary and continuous values, which helped get more accurate results in predicting a person's coronary heart disease. this project proposed approach will be a solution in recognizing coronary heart disease in the early stages and being able to treat and reduce the number of deaths resulting from this disease.