A Comparative Study of Machine Learning Models for Heart Disease Prediction
Advances and Challenges in Science and Technology Vol. 2,
20 September 2023
,
Page 59-71
https://doi.org/10.9734/bpi/acst/v2/6348C
Abstract
Heart disease continues to be a major global public health issue, contributing to innumerable deaths and disabilities. Effective preventive interventions and individualized treatment programs depend on timely and precise risk prediction of heart disease. Significant advancements in the field of cardiac disease prediction have been made thanks to the development of machine learning techniques. This book chapter offers a thorough analysis of the strengths, flaws, and overall effectiveness of the various machine learning models used for heart disease prediction.
- Heart disease prediction
- machine learning models
- comparative study
- logistic regression
- decision trees
- random forest
- Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN)