Heart Dieses Detection using Machine Learning

Author(s): Saloni Chaudhari, Dr. Hitesh Parmar, Rana Jay Bharatbhai

Publication #: 2506010

Date of Publication: 08.06.2025

Country: India

Pages: 1-7

Published In: Volume 11 Issue 3 June-2025

Abstract

The Heart disease detection project aims to build a tool that will help users detect the presence of heart disease.

It uses python and the supervised learning technique of classification to accurately product the presence of heart

disease based on different medical factors. This system leverages machine learning and data analytics to detect

heart disease risk factors, enabling early intervention and prevention. By integrating electronic health records,

diagnostic tests, and lifestyle data, our system provides personalized risk assessments and predictive analytics.

This approach facilitates timely medical attention, reduces complications, and improves patient outcomes. Our

system offers a proactive solution for cardiovascular health management, potentially reducing mortality rates

and healthcare costs. The research tackles issues such as climate change, resource shortages, and food insecurity

by utilizing sophisticated machine learning, specifically random forests, to contribute towards enhanced global

farming practices through intelligent data-driven approaches.

Keywords: Electrocardiogram, cardiac biomarkers, Torpotin Test, Cardiac ultrasound, stress test

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