Heart Disease Prediction Using Machine Learning

CVD is the one of the main reason of death compared to other diseases globally. Nearly 17.9 million people die every year because of this disease. WORLD HEALTH ORGANIZATION predicts that the deaths will increases by 24.5 million in 2030. Heart diseases involve diseases of the guts and blood vessels/artery. Four out of five deaths are occurs due to heart attacks. Nearly One-third of those deaths occur under the age of 70. The most of the people died in developing countries only. India is also comes under this category. For heart disease identification by examining the symptoms we need vascular specialists, which are very finite number in developing nations. Also, the medical tests/procedures for heart diseases are that’s a bit steep; At times out of the range for patient’s family. Early recognition is important in these type of diseases with low cost forecasting. In these days ML algorithms are used for forecasting of many other applications. These algorithms can be used for forecasting of CVD. The timely prediction of the heart diseases helped in taking decisions about the patients which resulted reduction of their risks. This project proposes a prediction model to predict whether patient have a heart disease or not by using entered symptoms in webform and to give an awareness on heart disease and some useful tips on heart disease.