Online Social Networks in Business Frameworks

29Machine Learning Techniques for Heart Disease Detection using E-Health Monitoring System

Vijay Ramalingam^*, T. Ragupathi, Arul Prakash A., S. Vignesh, Rahin Batcha R. and D. Saravanan

Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India

Abstract

The greatest incidence of coronary artery disease (CAD) is seen in the United States. This medical condition arises when extra fat lodges in the body’s arteries and veins, impairing circulation. The heart’s internal organs and heart itself do not get enough oxygen when blood flow into the heart is limited. Angina pectoris is the term for the condition in which the heart hurts from inadequate blood flow. If this is happening to you, there is a serious problem with your heart. Heart disease accounts for one death out of every five in India. Over the last several decades, heart disease has become the leading cause of death in the United States, surpassing all other causes. It is more difficult for medical experts to offer a timely and correct diagnosis due to several important hurdles. This article examines several machine learning algorithms for the purpose of identifying cardiac disease. The studies’ findings indicate that the SVM algorithm is the most effective in identifying cardiac issues.

Keywords: Machine learning, SVM, accuracy, sensitivity, specificity, heart disease prediction, E-Health

29.1 Introduction

It is estimated that approximately one million people per year ...