Abstract: Cardiovascular diseases have become the main cause of death in most of the countries of the world. The considerable growing of cardiovascular disease and its effects and complications as well as the high costs of treatment makes medical community seek for solutions to prevention, early identification and effective treatment with lower costs. Thus, valuable knowledge can be established by using artificial intelligence, the discovered knowledge makes improve the quality of service. Heart disease is a term assigned to a large number of medical conditions related to heart. These medical conditions describe the abnormal health conditions that directly influence the heart and all its parts. Heart disease is a major health problem in today’s time. Technically, the ANFIS performs a vital role for prediction of diseases in medical industry. Diagnosis of heart disease by using machine learning methods is one of the challenges in the health field .This project will be provided on a particular dataset using classification and feature selection approach. In this we will use feature ranking on effective factors of disease related to Cleveland clinic database and by using ANFIS, 13 effective factors reduced in terms of cost and accuracy.
Keywords: heart disease diagnosis, ANFIS, classification, feature selection.