Heart diseases are a major threat and concern in the lifestyle of people and in the medical field. It has been detected as a disease that has one of the major mortality rates. Many areas of the world are affected by cardiovascular diseases. Taking these factors into consideration, the prediction of cardiovascular diseases becomes crucial and the methodologies that predict CVD (Cardiovascular Disease) would help with reducing the mortality rate. Diagnosing heart disease is a little complicated task to do. Therefore, there is a requirement for an automated system that is able to predict the likelihood of heart disease in a person. Maintaining a prediction system ensures the quality of decisions made in the medical field. A system that predicts the level of heart disease of a patient is developed using and collecting data on the attributes such as age, sex, chest pain type, blood pressure, fasting blood sugar, etc. Python language is used as a coding language and VScode is used as the software platform. Three machine learning algorithms namely, Logistic regression, K-Nearest Neighbor (KNN), and random forest are used and the performance of all the algorithms are compared to get better results.



Software And Hardware