Fuzzy Soft Expert System in Prediction of Coronary Artery Disease

Abstract

Coronary artery disease affects millions of people all over the world including a major portion in Egypt every year. Although much progress has been done in medical science, early detection of this disease is still a challenge for prevention. In this paper we, will extend the concept of fuzzy soft set theory so as to develop a knowledge-based system in medicine and devise a prediction system named fuzzy soft expert system consisting of four main components. These are a fuzzification which translates inputs into fuzzy values, fuzzification of data sets to obtain fuzzy soft sets, a new fuzzy soft set by normal parameter reduction of fuzzy soft set and an algorithm to produce the resultant output. The fuzzy soft expert system developed is then used to predict for coronary artery disease using systolic blood pressure, low-density lipoprotein cholesterol, maximum heart rate, blood sugar, old peak and age of patients. A preliminary study is conducted on nine male patients undergoing treatment in the Cardiac Unit of the Faculty of Medicine, Assiut University, Egypt. It is found that the fuzzy soft expert system developed is able is to help the expert doctor to decide whether a patient needs to be given drug therapy or intervention.