An Efficient Machine Learning Based Methodology for Accurate Heart Disease Detection

• Author(s): Prem Singh ; Prof. Suraksha Tiwari
• Paper ID: 1703653
• Page: 668-671
• Published Date: 30-07-2022
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 1 July-2022

Abstract

It is possible to examine the efficacy of medical treatments by using data mining, a multidisciplinary field of research originating in database statistics. Diabetics are at an increased risk of developing diabetes-related heart disease. When the pancreas stops producing enough insulin, or when the body doesn't utilise the insulin it does generate correctly, diabetes sets in. Cardiovascular disease, or heart disease, refers to a group of illnesses that affect the heart or blood arteries. Many data mining classification methods exist for predicting heart disease, however there is insufficient data for predicting heart disease in diabetic individuals. Proposed decision tree based method is achieving better accuracy than the existing classifier.

Keywords

Data Mining, Machine Learning, Decision Tree, Naïve Bayes, Support Vector Machine, Accuracy, Classification, Prediction

Citations

IRE Journals:
Prem Singh , Prof. Suraksha Tiwari "An Efficient Machine Learning Based Methodology for Accurate Heart Disease Detection" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 668-671

IEEE:
Prem Singh , Prof. Suraksha Tiwari "An Efficient Machine Learning Based Methodology for Accurate Heart Disease Detection" Iconic Research And Engineering Journals, 6(1)