Heart Disease Severity Prediction using Machine Learning: A Survey

Authors

  • Nagaprasad K
  • Saathvik Shekar
  • Mahadevaiah S G
  • Sanjay M Shetty
  • Nagaraja B G

Keywords:

Algorithm, Body Parameters, ECG, Heart Disease, Machine Learning, Naïve Bayes

Abstract

There is a very steep increase in heart stroke at the early age, we have to find out something that will help us to detect the symptoms of heart disease at the starting age and prevent people from finding out about their disease at the last stage. It is not an easy task for a common people to go to hospital frequently and go through costly tests which include ECG and for the same reason we should have some software which is easily accessible and cheap and time saving in predicting the heart disease. So, we plan on develop a website application which will predict the heart disease with the help of symptoms and different body parameters which relates to heart. So, we use machine learning algorithm preferably naïve base algorithm which gives the most accurate result and hence we have used it in the proposed model.

Published

2022-06-28

How to Cite

Nagaprasad K, Saathvik Shekar, Mahadevaiah S G, Sanjay M Shetty, & Nagaraja B G. (2022). Heart Disease Severity Prediction using Machine Learning: A Survey. Journal of Power Electronics and Devices, 8(2), 9–12. Retrieved from http://matjournals.co.in/index.php/JOPED/article/view/736

Issue

Section

Review Paper