Paper Title
Heart Disease Prediction using Learning Techniques

Abstract
Heart disease prediction is a vital area of research in health care, aiming to reduce the mortality rate through early diagnosis and intervention. This project focuses on developing an advanced system that leverages Artificial Intelligence and Machine Learning (AIML) techniques to predict the risk of heart disease with high accuracy. The system provides healthcare professionals and patients with a reliable tool for assessing cardiovascular health, enabling proactive management and timely treatment. The proposed model is developed using a combination of machine learning algorithms and data analytics. It performs three key stages in heart disease prediction: patient data preprocessing, feature extraction, and risk classification, ensuring a fast, real-time, and efficient predictive solution. Keywords - Heart Disease Prediction, Artificial Intelligence, Machine Learning, Risk classification, Healthcare Analytics