Coronary Heart Disease Prediction Using Deep Learning

Abstract - Coronary Heart Disease (CHD) is a leading cause of mortality worldwide, making early detection and prediction crucial for effective treatment and prevention. The project presents a Coronary Heart Disease Prediction Web Application that enables users to assess their risk based on medical parameters and a Computed Tomography (CT) image. The system allows users to input personal details, including name, age, and blood pressure, and select relevant symptoms such as chest pain, heart attack, heart failure, and arrhythmia via check The uploaded CT image is analyzed using a trained machine learning or deep learning model, which determines whether chronic heart disease is confirmed or not. If the disease is detected, the system suggests possible medications; otherwise, it reassures the user that no coronary heart disease is present. The collected data is stored in an Excel data sheet for further analysis. The web application is built using Flask for the backend and a simple HTML-based frontend. Key Words: Documentation purposes, SEO optimization, Academic paper writing, Project categorization, Search functionality implementation, Database indexing, API documentation, Content organization