Cardiovascular Disease Prediction using Machine Learning Algorithms

Abstract

The term "cardiovascular disease" (CVD) encompasses a broad range of disorders affecting the heart and blood arteries include heart failure, stroke, and plaque in the arteries. It's a well-researched fact that Glob- ally, heart conditions (cardiovascular diseases) constitute the primary cause of mortality. According to estimates, 17.9 million deaths worldwide in 2019 were attributed to CVDs, accounting for 32% of allfatalities worldwide. Heart attacks and strokes were the main causes of 85% of these fatalities._x000D_ It is frequently discovered that avoiding hazards such as tobacco use, poor nutrition, obesity, lack of physical activity, and excessive drinking may avoid the majority of these illnesses. People who have cardiovascular disorders or individuals with risk factors such as diabetes, elevated blood pressure, or hyperlipidemia that put them at high risk of developing cardiovascular problems, or effectively treated illness should seek medical attention as soon as possible. With the changing times, the healthcare expenses have been skyrocketing and it can get difficult for one to get advanced healthcare. One can if one is cognizant of the early indications of CVDs, they will be more likely to notice threats early on. Here, various machine learning algorithms would be utilized to automate the process of CVD prediction using the patient's medical history and several other factors. After this, the most exact and precise model according to the performance of various specified algorithms would be selected.