Heart Disease Prediction using Machine Learning
Asmit Srivastava, Ashish Kumar Singh
Abstract
According to a recent WHO study, cardiovascular diseases are on the rise. As a result of which we can see that people dies in a year is approx. 17.9 million. With the growing population, it becomes more and more difficult to diagnose and begin treatment early. But thanks to recent advances in technology, machine learning techniques have accelerated the health sector through more research. Thus, the purpose of this project is to construct an ML model for predicting heart disease based on related parameters. We used the UCI heart prediction benchmark database for this research project, which covers 14 different heart-related parameters. In our study we also tried to find correlations between the various features found in the database with the help of standard Mechanical Learning. Methods and use them effectively in predicting the risk of heart disease. This model can be useful to medical staff at their clinic as a decision support system.