DETECTION OF CARDIOVASCULAR DISEASE USING DATA MINING ALGORITHMS

Since cardiovascular disease (CVD) is one of the leading causes of death worldwide, efficient tools for early detection and diagnosis must be developed. Data mining algorithms have become effective tools in the healthcare industry, enabling the extraction of significant knowledge from big medical databases. This study attempts to investigate how data mining techniques can be used to find cardiovascular illness. It concentrates on using these algorithms to forecast CVD risk based on patient information, such as demographics, medical history, and lifestyle factors. The effectiveness of several data mining techniques is compared and evaluated in the study, with a focus on their advantages and disadvantages for the identification of CVD.