Enhanced Analysis and Risk Prediction of Cardio Vascular Disease

  • Bellamgari Pranavi, Chanda Varun Raj, Bokka Sai Kiran Reddy, Arelly Sri Chaitanya Kumar, Raghu Kumar Lingamallu
Keywords: Data Mining Technologies, Heart Disease, Decision Tree, Prediction

Abstract

In today's world, fatalities from heart disease have become a significant problem; about one person dies from heart disease every minute. The contents of this article primarily concentrate on different data mining techniques that are useful in predicting heart disease using various data mining technologies that are available. If the heart does not operate correctly, it will cause problems in other areas of the body, such as the brain and kidneys. Heart disease is a condition that affects the heart's ability to operate. In today's world, heart disease is the leading cause of mortality. This ratio takes into account both male and female categories, and it may vary depending on the area. It also takes into account individuals between the ages of 25 and 69. This does not rule out the possibility of cardiac disease in individuals of other age groups. This issue may occur at any age, and predicting the origin and illness is a difficult task today. We've covered a variety of algorithms and methods for predicting heart disease in this article.

Published
2021-08-08
How to Cite
Arelly Sri Chaitanya Kumar, Raghu Kumar Lingamallu, B. P. C. V. R. B. S. K. R. (2021). Enhanced Analysis and Risk Prediction of Cardio Vascular Disease. Design Engineering, 7669- 7680. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/3276
Section
Articles