Cardiovascular Disease (CVD) is the number one cause of death worldwide, killing thousands of people every day. Recent advances in Machine Learning (ML) have brought new ways to diagnose CVD at a fraction of time and costs. This is a ML model developed as part of a bigger project for my BSc dissertation to help cardiologists diagnose and visualize their patients’ condition. The project experimented with five ML classification algorithms, with Random Forest performing the best in a variety of metrics, and therefore being deployed on the developed platform.
Web platform development: https://github.com/rafkol98/CVD-web