Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis
The study aims to accurately predict the presence of heart disease using machine learning models. The research evaluates and compares the performance of five algorithms - Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, and Gradient Boosting - on a dataset containing...
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| Main Authors: | Aiym B. Temirbayeva, Arshyn Altybay |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Peoples’ Friendship University of Russia (RUDN University)
2025-07-01
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| Series: | RUDN Journal of Engineering Research |
| Subjects: | |
| Online Access: | https://journals.rudn.ru/engineering-researches/article/viewFile/45012/25005 |
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