Heart Disease Prediction Using Ecg

Authors: Hemanth R, Manoj H, Chiranth BS, Kushith S, Dr Ashwin M

Abstract: Heart disease continues to be one of the most serious health concerns worldwide, often going undetected until the condition becomes life- threatening. Early diagnosis can save lives, but interpreting Electrocardiogram (ECG) readings requires clinical expertise and can be time- consuming in busy or underserved healthcare environments. To address this challenge, this project presents an AI-powered web application that analyzes ECG reports and predicts the risk of heart disease in real time. The system allows users to upload ECG images or files, which are then processed through advanced signal analysis and machine learning techniques. Important cardiac features such as heart rate, waveform patterns, and irregular signals are extracted to assess potential heart abnormalities. The trained model classifies the user’s condition into different risk levels and provides helpful recommendations based on the results. This solution focuses on accessibility, accuracy, and rapid assessment, making it useful for both patients and healthcare professionals. By combining intelligent prediction with a simple and interactive interface, the system supports early screening and encourages timely medical consultation, ultimately contributing to better cardiac health outcomes and improved quality of life.