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- Vol. 7 Issue 2
- Article
Heart Disease Prediction Using Machine Learning Techniques
Authors
1 2 Department of Computer Science & Engineering, BIT Mesra, Patna Campus, Bihar, India.
Article Information
- Published In
- Volume 7, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 336-340
- Article Type
- Original Article
References
1. Detrano, R., et al. (1989). International application of a new probability algorithm for the diagnosis of coronary artery disease.
American Journal of Cardiology.
2. Cleveland Heart Disease Dataset. UCI Machine Learning Repository. https://archive.ics.uci.edu/ml/datasets/Heart+Disease
3. World Health Organization (WHO). (2023). Cardiovascular Diseases (CVDs). https://www.who.int
4. Kaur, H., & Kumari, V. (2017). Predictive modelling and analytics for diabetes using machine learning approach. Applied Computing
and Informatics.
5. Soni, J., Ansari, U., Sharma, D., & Soni, S. (2011). Predictive data mining for medical diagnosis: An overview of heart disease
prediction. International Journal of Computer Applications.
6. Uddin, S., et al. (2019). Comparing different supervised machine learning algorithms for disease prediction. BMC Medical Informatics
and Decision Making.
7. Breiman, L. (2001). Random Forests. Machine Learning Journal.
8. Cortes, C., & Vapnik, V. (1995). Support Vector Networks. Machine Learning Journal.
9. Cover, T., & Hart, P. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions.
10. Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. Wiley.
11. Han, J., Kamber, M., & Pei, J. (2011). Data Mining: Concepts and Techniques. Elsevier.
12. Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. O’Reilly Media.
13. Pedregosa, F., et al. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research.
14. Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine Learning in Medicine. New England Journal of Medicine.
15. Chaurasia, V., & Pal, S. (2014). Data mining approach to detect heart diseases. International Journal of Advanced Computer Science.
American Journal of Cardiology.
2. Cleveland Heart Disease Dataset. UCI Machine Learning Repository. https://archive.ics.uci.edu/ml/datasets/Heart+Disease
3. World Health Organization (WHO). (2023). Cardiovascular Diseases (CVDs). https://www.who.int
4. Kaur, H., & Kumari, V. (2017). Predictive modelling and analytics for diabetes using machine learning approach. Applied Computing
and Informatics.
5. Soni, J., Ansari, U., Sharma, D., & Soni, S. (2011). Predictive data mining for medical diagnosis: An overview of heart disease
prediction. International Journal of Computer Applications.
6. Uddin, S., et al. (2019). Comparing different supervised machine learning algorithms for disease prediction. BMC Medical Informatics
and Decision Making.
7. Breiman, L. (2001). Random Forests. Machine Learning Journal.
8. Cortes, C., & Vapnik, V. (1995). Support Vector Networks. Machine Learning Journal.
9. Cover, T., & Hart, P. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions.
10. Hosmer, D. W., & Lemeshow, S. (2000). Applied Logistic Regression. Wiley.
11. Han, J., Kamber, M., & Pei, J. (2011). Data Mining: Concepts and Techniques. Elsevier.
12. Géron, A. (2019). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow. O’Reilly Media.
13. Pedregosa, F., et al. (2011). Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research.
14. Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine Learning in Medicine. New England Journal of Medicine.
15. Chaurasia, V., & Pal, S. (2014). Data mining approach to detect heart diseases. International Journal of Advanced Computer Science.
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