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Volume 13
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases

by
Norma Latif Fitriyani
1,†,
Muhammad Syafrudin
1,†,
Nur Chamidah
2,3,*,
Marisa Rifada
2,3,
Hendri Susilo
4,
Dursun Aydin
5,6,
Syifa Latif Qolbiyani
7 and
Seung Won Lee
8,9,10,11,*
1
Department of Artificial Intelligence and Data Science, Sejong University, Seoul 05006, Republic of Korea
2
Department of Mathematics, Faculty of Science and Technology, Airlangga University, Surabaya 60115, Indonesia
3
Research Group of Statistical Modeling in Life Science, Faculty of Science and Technology, Airlangga University, Surabaya 60115, Indonesia
4
Department of Cardiology and Vascular Medicine, Faculty of Medicine, Airlangga University, Surabaya 60286, Indonesia
5
Department of Statistics, Faculty of Science, Muğla Sıtkı Koçman University, Muğla 48000, Turkey
6
Department of Mathematics, University of Wisconsin, Oshkosh Algoma Blvd, Oshkosh, WI 54901, USA
7
Department of Community Development, Universitas Sebelas Maret, Surakarta 57126, Indonesia
8
Department of Precision Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea
9
Department of Metabiohealth, Sungkyunkwan University, Suwon 16419, Republic of Korea
10
Personalized Cancer Immunotherapy Research Center, Sungkyunkwan University School of Medicine, Suwon 16419, Republic of Korea
11
Department of Artificial Intelligence, Sungkyunkwan University, Suwon 16419, Republic of Korea
 
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*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Mathematics 2025, 13(13), 2194; https://doi.org/10.3390/math13132194
Submission received: 7 May 2025 / Revised: 31 May 2025 / Accepted: 2 July 2025 / Published: 4 July 2025
(This article belongs to the Special Issue Application of Artificial Intelligence in Decision Making)
Versions Notes

Abstract

Cardiovascular diseases (CVDs) rank among the leading global causes of mortality, underscoring the necessity for early detection and effective management. This research presents a novel prediction model for CVDs utilizing a bagging algorithm that incorporates histogram gradient boosting as the estimator. This study leverages three preprocessed cardiovascular datasets, employing the Local Outlier Factor technique for outlier removal and the information gain method for feature selection. Through rigorous experimentation, the proposed model demonstrates superior performance compared to conventional machine learning approaches, such as Logistic Regression, Support Vector Classification, Gaussian Naïve Bayes, Multi-Layer Perceptron, k-nearest neighbors, Random Forest, AdaBoost, gradient boosting, and histogram gradient boosting. Evaluation metrics, including precision, recall, F1 score, accuracy, and AUC, yielded impressive results: 93.90%, 98.83%, 96.30%, 96.25%, and 0.9916 for dataset I; 94.17%, 99.05%, 96.54%, 96.48%, and 0.9931 for dataset II; and 89.81%, 82.40%, 85.91%, 86.66%, and 0.9274 for dataset III. The findings indicate that the proposed prediction model has the potential to facilitate early CVD detection, thereby enhancing preventive strategies and improving patient outcomes.
Keywords: machine learning; bagging algorithm; histogram gradient boosting; local outlier factor; information gain machine learning; bagging algorithm; histogram gradient boosting; local outlier factor; information gain

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MDPI and ACS Style

Fitriyani, N.L.; Syafrudin, M.; Chamidah, N.; Rifada, M.; Susilo, H.; Aydin, D.; Qolbiyani, S.L.; Lee, S.W. A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases. Mathematics 2025, 13, 2194. https://doi.org/10.3390/math13132194

AMA Style

Fitriyani NL, Syafrudin M, Chamidah N, Rifada M, Susilo H, Aydin D, Qolbiyani SL, Lee SW. A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases. Mathematics. 2025; 13(13):2194. https://doi.org/10.3390/math13132194

Chicago/Turabian Style

Fitriyani, Norma Latif, Muhammad Syafrudin, Nur Chamidah, Marisa Rifada, Hendri Susilo, Dursun Aydin, Syifa Latif Qolbiyani, and Seung Won Lee. 2025. "A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases" Mathematics 13, no. 13: 2194. https://doi.org/10.3390/math13132194

APA Style

Fitriyani, N. L., Syafrudin, M., Chamidah, N., Rifada, M., Susilo, H., Aydin, D., Qolbiyani, S. L., & Lee, S. W. (2025). A Novel Approach Utilizing Bagging, Histogram Gradient Boosting, and Advanced Feature Selection for Predicting the Onset of Cardiovascular Diseases. Mathematics, 13(13), 2194. https://doi.org/10.3390/math13132194

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