Abstract

Early identification is essential for efficient treatment of heart disease, which continues to rank among the leading causes of mortality worldwide. This article proposes an ensemble-based machine learning approach for cardiac disease prediction using the Cleveland dataset. Unlike prior research that focused on only two algorithms, this study integrates six supervised learning models—K-Nearest Neighbors (KNN), Logistic Regression, Support Vector Machine (SVM), Decision Tree, Random Forest, and Naive Bayes—into a single ensemble system. GridSearchCV-based hyperparameter optimization is used to optimize model accuracy. The ensemble model outperformed the individual models in terms of accuracy, with a prediction accuracy of over 90%. This approach supports computerized diagnosis and early medical intervention.

References

• Kavitha, M., Gnaneswar, G., Dinesh, R., Sai, Y. R., & Suraj, R. S. (2021, January). Heart disease prediction using hybrid machine learning model. In 2021 6th International Conference on Inventive Computation Technologies (ICICT) (pp. 1329-1333). IEEE.
• Katarya, R., & Srinivas, P. (2020, July). Predicting heart disease at early stages using machine learning: a survey. In 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 302-305). IEEE.
• Geetha, S., Devi, C. P., Kalaivani, V., Haritha, C. J., & Preetha, G. (2021). Prediction Techniques of Heart Disease and Diabetes Disease using Machine Learning. Turkish Journal of Computer and Mathematics Education, 12(10), 3316-3325.
• El Hamdi, S., Refaat, K., Abbaoui, W., Lasri, I., Riadsolh, A., & Ziti, S. (2024). Predicting Heart Disease with Advanced Machine Learning Techniques. Journal of Innovation and Digital Health, 1(2), 42-51, Vol. 1 No. 2 (2024)
• Patil, M. S., Anuradha, B., Madhuri, G., & Supriya, S. (2024). CARDIO PREDICT: HARNESSING MACHINE LEARNING FOR ADVANCED HEART DISEASE RISK ASSESSMENT. blood pressure, 11(4), Volume 11, Issue 4, April – 2024, DOI: https://doi.org/10.26662/ijiert.v11i4.pp28-32.
• Ahmed, M., & Husien, I. (2024). Heart Disease Prediction Using Hybrid Machine Learning: A Brief Review. Journal of Robotics and Control (JRC), 5(3), 884-892, DOI: https://doi.org/10.18196/jrc.v5i3.21606, Vol. 5 No. 3 (2024).
• Logabiraman, G., Ganesh, D., Kumar, M. S., Kumar, A. V., & Bhardwaj, N. (2024). Heart disease prediction using machine learning algorithms. In MATEC Web of Conferences DOI: https://doi.org/10.1051/matecconf/202439201122, Volume 392 (2024).
• Yusuf, M., & Hajara, I. O. (2024). A Review of Hybrid Intelligent System for Diagnosis and Prediction of Heart Disease. Journal of Agricultural and Food Chemical Engineering, 4(2), 1-8. Volume: 4, Issue: 2, Pages: 1 – 8, DOI:.https://doi.org/10.58612/jafce421
• Chaporkar T, Joshi T, Khanzode M, Prof Misalkar H.D., Malpani H, (2024), “Effective heart disease prediction using Hybrid machine learning Technique”, IJNRD, 9(4), 2456-4184. DOI: https://doi.org/10.26524/sajet.2022.12.49, Vol. 12 No. 3 (2022): Vol 12, Issue 3.
• Rufes, P., Jenita, J. S., & Divya, M. S. (2024). Heart Disease Prediction Using Machine Learning. International Research Journal on Advanced Engineering Hub (IRJAEH), 2(03),485-490, DOI: https://doi.org/10.47392/IRJAEH.2024.0070, Vol.02 Issue 03- [March 24].
• Gautam, C. S., & Pandey, P. (2022). A review on genetic algorithm models for Hadoop MapReduce in big data. International Journal of Recent Scientific Research, 13(3E), 771–775. https://doi.org/10.24327/ijrsr.2022.1303.0166
• Gautam, C. S., Soni, L. N., & Pandey, P. (2022). Clustering of big data using genetic algorithm in Hadoop MapReduce. European Chemical Bulletin, 12, 963–973.
• Gautam, C. S., & Waoo, A. A. (2024). Genetic algorithm vs ant colony optimization for offloading in mobile augmented reality. ShodhKosh: Journal of Visual and Performing Arts, 5.
• Gautam, C. S., & Pandey, P. (2023). Improving query optimization process in Hadoop MapReduce using ACO-genetic algorithm and HDFS MapReduce technique. International Journal of Current Engineering and Technology, 13(2). https://doi.org/10.14741/ijcet/v.13.2.8
• Gautam, C. S., & Pandey, P. (2019). A review of big data environment, tools and challenges. Journal of Emerging Technologies and Innovative Research, 6, 569–575.
• Chaudhari, S., Gautam, C. S., & Waoo, A. A. (2024). Enhancing heart disease prediction accuracy: A comparative study of machine learning models with ensemble method. JARIIE, 10, 4827–4833.
• Kar, S. K., Pandey, A., & Gautam, C. S. (2025). A review of machine learning techniques for breast cancer prediction. International Journal of Current Engineering and Technology, 15(3).
• Shrivastava, P., Gautam, C. S., & Kar, S. K. (2024). Assessing the performance of Cataract Net and other deep learning systems for automated cataract detection. ShodhKosh: Journal of Visual and Performing Arts, 5(5).
• Shrivastava, P., & Gautam, C. S. (2025). A systematic review of digital twin and reinforcement learning applications in underground load-haul-dump (LHD) systems. The Indian Mining & Engineering Journal, 64(10–11), 39–48.
• Patel, H. S., Gautam, C. S., & Waoo, A. A. (2025). AI-powered intrusion systems in cybersecurity and zero-day attack detection. International Journal of Scientific Research in Engineering and Management (IJSREM), 9(11). https://doi.org/10.55041/IJSREM54733
• Shrivastava, R., & Gautam, C. S. (2026). An optimized hybrid classification approach for early detection of heart disease. International Journal of Computer Science Trends and Technology (IJCST), 14(1), 25–31.
• Gautam, C. S., & Waoo, A. A. (2024). Genetic algorithm vs ant colony optimization for offloading in mobile augmented reality. ShodhKosh: Journal of Visual and Performing Arts, 5(5), 352–361. https://doi.org/10.29121/shodhkosh.v5.i5.2024.1886
• R. Shrivastava, S. Mewad, and P. Sharma, “An approach to give first rank for website and webpage through SEO,” International Journal of Computer Sciences and Engineering (IJCSE), vol. 2, no. 6, pp. —, Jun. 2014, E-ISSN: 2347-2693.
• R. Shrivastava, c. S. Gautam, and s. K. Kar, “promoting a website with the help of seo using ppc (pay per click),” shodhkosh: journal of visual and performing arts, vol. 5, no. 5, pp. 133–140, may 2024, issn (online): 2582-7472, doi: 10.29121/shodhkosh. v5.i5.2024.361.
• Shrivastava, R., & Gautam, C. S. (2026). An optimized hybrid classification approach for early detection of heart disease. International Journal of Computer Science Trends and Technology (IJCST), 14(1). ISSN 2347-8578.
• Shrivastava, R., Mewad, S., & Sharma, P. (2014). An approach to give first rank for website and webpage through SEO. International Journal of Computer Sciences and Engineering (IJCSE), 2(6). E-ISSN 2347-2693.
• Shrivastava, R., Gautam, C. S., & Kar, S. K. (2024). Promoting a website with the help of SEO using PPC (Pay Per Click). Shodhkosh: Journal of Visual and Performing Arts, 5(5), 133–140. https://doi.org/10.29121/shodhkosh.v5.i5.2024.361
• Shrivastava, R., & Gautam, C. S. (2026). An optimized hybrid classification approach for early detection of heart disease. International Journal of Computer Science Trends and Technology (IJCST), 14(1). ISSN 2347-8578.