Heart Disease Prediction Using Machine Learning Classifiers - Nahista Anjum Abuzar Ansari ,Sunita Nandgave,Md Mozakkir Ansari,Shital Gupta ,Faheem Kasuar (International Journal of Advanced Science and Technology, 2020)
In today's era the main cause of death is Heart Disease. The most efficient way to reduce the risk of heart disease is Machine learning. According to the CDC (Centers for Disease Controller) due to heart disease in the world, 80% of people died in the last ten years. The term Cardiovascular Disease is an interchangeable term with Heart Disease. The heart disease presence can spare people living these days precisely. In most of the individuals, we found the cardiovascular disease, which needs to be treated at its early time to overcome the Heart Disease. In medical history, the traditional way to diagnose heart disease has been considered as not reliable in many aspects. Noninvasive methods such as Machine Learning plays a crucial role in predicting the presence or absence of Heart Disease Machine learning algorithms used for mathematics bioinformatics to their deployment in clinical diagnosis, prognosis and drug development. The machine learning system will assist the doctors to treat heart patients efficiently. It will have a great impact on classifiers performance in accordance of accuracy and execution time of classifiers.  In the study, we proposed a machine-learning-based diagnosis system for heart disease prediction by using heart disease dataset. The proposed system, Heart Disease Prediction System with the help of Machine Learning Algorithms. Here the system is going to use SVM and KNN Algorithm to process the large scale data to predict Heart Disease