Heart Diseases Prediction
Year: 2025
Type: article
Abstract: The Heart Disease Prediction System is designed to assist in the early identification of individuals at risk of heart-related ailments by analyzing various health parameters. The project utilizes key medical attributes such as age, gender, blood pressure, cholesterol level, blood sugar, resting ECG results, and other vital indicators to predict the likelihood of heart disease. By applying advanced machine learning algorithms, the system can learn patterns and correlations within the dataset to generate accurate predictions. A user-friendly web interface is developed to allow users or healthcare professionals to input patient data and instantly receive prediction results in a clear and visual format. This project aims to enhance medical decision-making, reduce the time required for diagnosis, and promote early prevention measures. Ultimately, the system contributes to improving the quality of healthcare services by providing a reliable, efficient, and easily accessible tool for heart disease prediction and risk assessment.
Authors: Sasidaran.D, Vinithkumar.S, Siva.S, Seenivasan.P, Dr.V.Kamalaveni
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7093339698
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