Heart Disease Prediction System using Supervised Machine Learning Algorithms

Abstract

This project aims to help prevent heart disease by predicting it early and recommending ways to reduce the risk. Heart problems can affect people of all ages nowadays, so prevention is really important. We're using information about your health and lifestyle to figure out if you're at risk of having heart issues soon. The good thing about our system is that we're using machine learning, which means we've trained computers to analyze a lot of data and make pretty accurate predictions about heart disease. However, the downside is that existing systems usually just tell you if you're at risk or not. They don't give you any advice on how to lower that risk. Plus, these systems aren't easily accessible for everyone to use.We're testing different models like Logistic Regression, Decision Tree, Random Forest, Support Vector Machines, K-nearest Neighbor, and XGBoost to see which one works best for predicting heart disease. This way, we hope to make it easier for people to take control of their heart health and reduce the chances of having problems in the future. Additionally, we're planning to deploy our website so that everyone can access it easily. This means you won't need any special software or knowledge to use our system—it'll be available to anyone with an internet connection.