| Issue |
E3S Web Conf.
Volume 351, 2022
10th International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES’2022)
|
|
|---|---|---|
| Article Number | 01037 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202235101037 | |
| Published online | 24 May 2022 | |
Comparative study of machine learning algorithms (SVM, Logistic Regression and KNN) to predict cardiovascular diseases
1 ERSC, E3S Research Center, Mohammed V University of Rabat, Morocco
2 ERSC, E3S Research Center, Mohammed V University of Rabat, Morocco
mohammedmarouanesaim@research.emi.ac.ma
ammor@emi.ac.ma
Artificial intelligence has had an impact on a variety of fields, including medicine and, most importantly, cardiovascular diseases. Indeed, early diagnosis of many disorders is a serious medical issue. In this article, we will compare various machine learning algorithms in order to select the optimal one for diagnosing people who might suffer from heart disease based on a variety of clinical data from patients. The effort in this article is focused on studying the dataset using data mining algorithms, and also explaining the used machine learning algorithms in predicting heart disease, in order to assist future researchers in getting the most out of these skills.
Key words: Data Mining Algorithms / Heart Disease / Risk Prediction / Support Vector Machine / K-Nearest Neighbor / Logistic Regression / Boruta / Performance metrics
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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