Heart Disease Prediction Using Supervised Machine Learning Algorithms
Narendra Mohan, Vinod Jain, Gauranshi Agrawal
Abstract
Predicting and detecting cardiac disease has always been a difficult and time-consuming undertaking for doctors. To treat cardiac disorders, hospitals and other clinics are giving costly therapies and operations. As a result, anticipating cardiac disease in its early stages will be beneficial to people all around the world, allowing them to take required treatment before it becomes serious. Heart disease has been a major issue in recent years, with the primary causes being excessive alcohol use, tobacco use, and a lack of physical activity. Machine learning methods are utilized to forecast cardiac illnesses in this article. For training and testing, a data collection containing diverse human health parameters is used. Many AI&ML algorithms are used to predict cardiac disorders. The performance of the machine learning algorithm is compared after it has been implemented.