A Novel Hybrid Feature Selection Framework with Dimensionality Reduction for Early Cardiovascular Disease Detection
By: G. Muthuselvi and J. Jebamalar Tamilselvi
References
- Abdellatif, A., Mubarak, H., Abdellatef, H., Kanesan, J., Abdelltif, Y., & Chow, C. O. (2024). Computational detection and interpretation of heart disease based on conditional variational auto-encoder and stacked ensemble-learning framework. Biomedical Signal Processing and Control, 88, 105644. DOI: 10.1016/j.bspc.2023.105644
- Abdullahi, A., Barre, M. A., & Elmi, A. H. (2024). A machine learning approach to cardiovascular disease prediction with advanced feature selection. Indonesian Journal of Electrical Engineering and Computer Science, 33(2), 1030–1041. DOI: 10.11591/ijeecs.v33.i2.pp1030-1041
- Ahmed, M., & Husien, I. (2024). Heart disease prediction using hybrid machine learning: A brief review. Journal of Robotics and Control, 5(3), 884–892. DOI: 10.18196/jrc.v5i3.21606
- Al-Sayed, A., Khayyat, M. M., & Zamzami, N. (2023). Predicting heart disease using collaborative clustering and ensemble learning techniques. Applied Sciences, 13(24), 13278. DOI: 10.3390/app132413278
- Jayasudha, R., Suragali, C., Thirukrishna, J. T., et al. (2023). Hybrid optimization enabled deep learning-based ensemble classification for heart disease detection. Signal, Image and Video Processing, 17, 4235–4244. DOI: 10.1007/s11760-023-02656-2
- Kallimani, J. S., Walia, R., & Belete, B. (2022). A novel feature selection with hybrid deep learning based heart disease detection and classification in the e-healthcare environment. Computational Intelligence and Neuroscience, 2022, Article ID. DOI: 10.1155/2022
- Khan, H., Javaid, N., Bashir, T., Akbar, M., Alrajeh, N., & Aslam, S. (2024). Heart disease prediction using novel ensemble and blending based cardiovascular disease detection networks: EnsCVDD-Net and BlCVDD-Net. IEEE Access, 12, 109230–109254. DOI: 10.1109/ACCESS.2024.3421241
- Laishram, R., & Rabidas, R. (2024). Binary tunicate swarm algorithm based novel feature selection framework for mammographic mass classification. Measurement, 235, 114928. DOI: 10.1016/j.measurement.2024.114928
- Mandula, A., & Vijaya Kumar, B. S. (2024). Integrated feature selection and ensemble learning for heart disease detection: A 2-tier approach with ALAN and ET-ABDF machine learning model. International Journal of Information Technology, 16(7), 4489–4503. DOI: 10.1007/s41870-024-02016-4
- Mienye, I. D., & Sun, Y. (2021). Improved heart disease prediction using particle swarm optimization based stacked sparse autoencoder. Electronics, 10(19), 2347. DOI: 10.3390/electronics10192347
- Milosevic, M., Jin, Q., Singh, A., & Amal, S. (2024). Applications of AI in multi-modal imaging for cardiovascular disease. Frontiers in Radiology, 3, 1294068. DOI: 10.3389/fradi.2023.1294068
- Paul, V. V., & Masood, J. A. I. S. (2024). Exploring predictive methods for cardiovascular disease: A survey of methods and applications. IEEE Access, 12, 101497–101505.
- Prakruthi, N., Udupa, D., & Santosha. (2023). Influence of gender, education and occupation on stipulate of demand for residential property. European Economic Letters, 13(3).
- Raman, R., Kumar, V., Saini, D., Rabadiya, D., Rastogi, S., & Pandey, D. (2024). Enhanced cardiovascular disease prediction using advanced machine learning with hybrid feature selection. In Proceedings of the 2024 Fourth International Conference on Multimedia Processing, Communication & Information Technology (MPCIT) (pp. 297–302). IEEE. DOI: 10.1109/MPCIT62449.2024.10892767
- Razzaque, A., & Badholia, D. A. (2024). PCA based feature extraction and MPSO based feature selection for gene expression microarray medical data classification. Measurement Sensors, 31, 100945. DOI: 10.1016/j.measen.2023.100945
- Santosh Kumar, S., & Bharathi, S. H. (2023). Enhancing the performance of single-channel blind source separation by using ConvTransFormer. International Journal of Communication Networks and Information Security, 15(2), 159–170.
- Subramani, S., Varshney, N., Anand, M. V., Soudagar, M. E., Ahmed, L., Upadhyay, T. K., Alshammari, N., Saeed, M., Subramanian, K., Anbarasu, K., & Rohini, K. (2023). Cardiovascular disease prediction by machine learning incorporation with deep learning. Frontiers in Medicine, 10. DOI: 10.3389/fmed.2023
- Spagnolo, F., Lal, B., Corsonello, P., & Gravina, R. (2025). A novel compressive sensing method for secure and energy efficient ECG signal transmission applications. IEEE Journal of Biomedical and Health Informatics, 1–12. DOI: 10.1109/jbhi.2025.3530082
- Asha, M., & Ramya, G. (2024). Artificial Flora Algorithm Based Feature Selection with Support Vector Machine for Cardiovascular Disease Classification. IEEE Access, 1. DOI: 10.1109/access.2024.3524577
- Reshan, M. S. A., Amin, S., Zeb, M. A., Sulaiman, A., Alshahrani, H., & Shaikh, A. (2023). A robust heart disease prediction system using hybrid deep neural networks. IEEE Access, 11, 121574–121591. DOI: 10.1109/access.2023.3328909
- Rao, G.M., Ramesh, D., Sharma, V. et al. AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach. Sci Rep 14, 7833 (2024).
https://doi.org/10.1038/s41598-024-56931-4
DOI: https://doi.org/10.2478/ijssis-2026-0059 | Journal eISSN: 1178-5608
Language: English
Submitted on: May 14, 2026
Published on: Aug 13, 2026
Published by: International Journal on Smart Sensing and Intelligent Systems
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Related subjects:
© 2026 G. Muthuselvi, J. Jebamalar Tamilselvi, published by International Journal on Smart Sensing and Intelligent Systems
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.