Cardio vascular disease prediction using machine learning web application

Abstract

The Principal Target of this application to be create and make a strategy model that can forecast a patient's status of health based on a large amount of data. Coronary illness is the most common cause of mortality among humans. ML provides many classification techniques to divine the chance of a patient having HD based on the specified task. This project tries to recognize at-risk traits and classify data based on those aspects, allowing for exactprediction. To arrive at efficient findings, the dataset is first pre-handled and investigated against different calculations, with their accuracies evaluated. The efficient method is then employed in the back-end and connected with the front-end as a web application to predict whether or not a person has disease based on the input values. As a result, this web application would be the efficient need of the hour for obtaining precise health outcomes.