Web Application for Heart Disease Prediction using Machine Learning for Early Warning

Heart is an essential part of our body. People are leading to death due to heart diseases. The deaths due to heart diseases are increasing in number day by day. The heart disease can be taken care of if examined at the early stage but become lethal if the disease is examined late. Thus, it’s necessary to diagnose the heart disease at an early stage to prevent it from getting serious. This paper aims at designing a web application for predicting heart diseases with proper analysis using machine learning algorithms which includes Random Forest, Ada Boosting, Gradient descent Boosting and XG Boosting. The best model is saved and integrated with the web application designed to enter the features and predict the possibility to get a heart disease.