A SURVEY ON HEART DISEASE PREDICTION USING SOFT COMPUTING

Large number of people has being affected due to heart disease and it has become a major problem. One of such threat is Cardiovascular Disease (CVD). If it is not treated and detected at an early and proper stage may lead to death. Especially in medical sector there is no such adequate research focus on effective analysis tool to discover and trends in data. Large amount of complex clinical data of patients and other hospital resources are being generated by health care industry nowadays. In male as well as female, it is the first leading cause of death according to world health organisation (WHO). Various heart diseases are caused due to reduction in supply of blood and oxygen. Therefore main objective of our paper is to predict more accurately the percentage of possibility of cardiovascular disease in minimum number of attributes (like blood pressure, cholesterol, type of chest pain, blood sugar, etc). Many data mining techniques are used to analyse this rich collection of data from different perspectives and deriving useful information. This project intends to design and develop, diagnosis and prediction system for heart disease based on soft computing technique that is ANFIS.