Published Paper Details:

Heart Disease is the one of major causes of death globally. Around 17.9 million people die each year. Cardiovascular diseases include disorders of the heart and blood vessels. Four out of five cardiovascular disease deaths are due to heart attacks. One-third of these deaths occur prematurely under the age of seventy. The major number of deaths have occurred in developing countries. India is one of them. For heart disease diagnosis we need cardiologists, which are in limited number in developing countries. Also, the tests for cardiovascular diseases are quite expensive; sometimes out of the budget for common people. Early detection is important in case of heart disease with less expensive prediction techniques. As we know, now-a-days Machine Learning algorithms are used for predicting various diseases. They are also used for predicting Heart Disease. This paper deals with the survey of Machine Learning algorithms used for predicting heart disease, the importance of attributes to predict the disease and selection of important attributes for predication.