Predicting Coronary Heart Disease Using a Suite of Machine Learning Models

Jamal Al-Karaki, Philip Ilono, Sanchit Baweja, Jalal Naghiyev, Raja Singh Yadav +1 more
9/21/2024
cs.AI

No confident code implementation found for this paper.

Abstract

Coronary Heart Disease affects millions of people worldwide and is a well-studied area of healthcare. There are many viable and accurate methods for the diagnosis and prediction of heart disease, but they have limiting points such as invasiveness, late detection, or cost. Supervised learning via machine learning algorithms presents a low-cost (computationally speaking), non-invasive solution that can be a precursor for early diagnosis. In this study, we applied several well-known methods and benchmarked their performance against each other. It was found that Random Forest with oversampling of the predictor variable produced the highest accuracy of 84%.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Classification and Prediction of Heart Diseases using Machine Learning Algorithms

89% match2024

An Explainable AI-Enhanced Machine Learning Approach for Cardiovascular Disease Detection and Risk Assessment

87% match2025

The Significance of Machine Learning in Clinical Disease Diagnosis: A Review

86% match2023

Advancements In Heart Disease Prediction: A Machine Learning Approach For Early Detection And Risk Assessment

86% match2024

Multi-class heart disease Detection, Classification, and Prediction using Machine Learning Models

85% match2024

Heart Diseases Prediction Using Block-chain and Machine Learning

85% match2023

Cite this paper

@article{alkaraki2024predicting,
  title  = {Predicting Coronary Heart Disease Using a Suite of Machine Learning Models},
  author = {Jamal Al-Karaki and Philip Ilono and Sanchit Baweja and Jalal Naghiyev and Raja Singh Yadav and Muhammad Al-Zafar Khan},
  year   = {2024},
  eprint = {2409.14231},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.14231v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2409.14231.svg)](https://codeofpaper.com/paper/2409.14231)

Discussion