EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 74 (2025) ITM Web Conf., 74 (2025) 01005 References
Open Access
Issue
ITM Web Conf.
Volume 74, 2025
International Conference on Contemporary Pervasive Computational Intelligence (ICCPCI-2024)
Article Number 01005
Number of page(s) 13
Section Artificial Intelligence and Machine Learning Applications
DOI https://doi.org/10.1051/itmconf/20257401005
Published online 20 February 2025
  1. Bizimana, P. C., Zhang, Z., Asim, M., El-Latif, A. A. A., & Hammad, M. (2024). Learning-based techniques for heart disease prediction: a survey of models and performance metrics. Multimedia Tools and Applications, 83(13), 39867–39921. [Google Scholar]
  2. Manikandan, G., Pragadeesh, B., Manojkumar, V., Karthikeyan, A. L., Manikandan, R., & Gandomi, A. H. (2024). Classification models combined with Boruta feature selection for heart disease prediction. Informatics in Medicine Un- locked, 44, 101442. [CrossRef] [Google Scholar]
  3. Murthy, M. S. N., Vinutna, P. N. S. S., Kumar, P. A., Shravani, P., & Brahmaji, P. (2024). Predicting Heart Disease Cases through Unsupervised Approaches. G. V. P. College of Engineering (A), Journal of Scientific Computing, 13(7), 1–5. DOI: 10.10089.JSC.2024.V13I7.285311.3000. [Google Scholar]
  4. Nanehkaran, Y. A., Licai, Z., Chen, J., Jamel, A. A., Shengnan, Z., Navaei, Y. D., & Aghbolagh, M. A. (2022). Anomaly Detection in Heart Disease Using a Density- Based Unsupervised Approach. Wireless Communications and Mobile Computing, 2022(1), 6913043. [Google Scholar]
  5. Nouraei, H., & Rabkin, S. W. (2022). Comparison of unsupervised machine learning approaches for cluster analysis to define subgroups of heart failure with preserved ejection fraction with different outcomes. Bioengineering, 9(4), 175. [CrossRef] [Google Scholar]
  6. N. Sabri et al., “Heart Inspect: Heart Disease Prediction of an Individual Using Naïve Bayes Algorithm,” 2023 IEEE 11th Conference on Systems, Process Control (ICSPC), Malacca, Malaysia, 2023, pp. 350–354, DOI: 10.1109/ICSPC59664.2023.10420149. [CrossRef] [Google Scholar]
  7. Ogunpola, A., Saeed, F., Basurra, S., Albarrak, A. M., & Qasem, S. N. (2024). Machine learning-based predictive models for detection of cardiovascular diseases. Diagnostics, 14(2), 144. [CrossRef] [PubMed] [Google Scholar]
  8. Radwan, M., Mohamed Abdelrahman, N., Wael Kamal, H., Khaled Abdelmonem Elewa, A., & Moataz Mohamed, A. (2023). ML Heart Disease Prediction: heart disease prediction using machine learning. Journal of Computing and Communication, 2(1), 50–65. [CrossRef] [Google Scholar]
  9. Segar, M. W., Patel, K. V., Ayers, C., Basit, M., Tang, W. W., Willett, D., … & Pandey, A. (2020). Phenomapping of patients with heart failure with preserved ejection fraction using machine learning-based unsupervised cluster analysis. European journal of heart failure, 22(1), 148–158. [CrossRef] [Google Scholar]
  10. Radwan, M., Mohamed Abdelrahman, N., Wael Kamal, H., Khaled Abdelmonem Elewa, A., & Moataz Mohamed, A. (2023). ML Heart Disease Prediction: heart disease prediction using machine learning. Journal of Computing and Communication, 2(1), 50–65. [CrossRef] [Google Scholar]
  11. A. Bhowmick, K. D. Mahato, C. Azad and U. Kumar, “Heart Disease Prediction Using Different Machine Learning Algorithms,” 2022 IEEE World Conference on Applied Intelligence and Computing (AIC), Sonbhadra, India, 2022, pp. 60–65, DOI: 10.1109/AIC55036.2022.9848885. [Google Scholar]
  12. A. R. Panda, M. K. Mishra, M. Kumar Gourisaria, S. Pal, P. K. Pattnaik and S.K. Swain, “Heart Disease Prediction: A Comparative Analysis of Machine Learning Algorithms,” 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON), Bengaluru, India, 2024, pp. 1–6, DOI: 10.1109/NMITCON62075.2024.10698898. [Google Scholar]
  13. Jindal, H., Agrawal, S., Khera, R., Jain, R., & Nagrath, P. (2021). Heart disease prediction using machine learning algorithms. In IOP conference series: materials science and engineering (Vol. 1022, No. 1, p. 012072). IOP Publishing. [CrossRef] [MathSciNet] [Google Scholar]
  14. Singh, A., & Kumar, R. (2020, February). Heart disease prediction using machine learning algorithms. In 2020 international conference on electrical and electronics engineering (ICE3) (pp. 452–457). IEEE. [CrossRef] [Google Scholar]
  15. S. Upadhyay, A. Dwivedi, A. Verma and V. Tiwari, “Heart Disease Prediction Model using various Supervised Learning Algorithm,” 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT), Bhopal, India, 2023, pp. 197–201, DOI: 10.1109/CSNT57126.2023.10134595. [Google Scholar]
  16. Vayadande, K., Golawar, R., Khairnar, S., Dhiwar, A., Wakchoure, S., Bhoite, S., & Khadke, D. (2022, May). Heart disease prediction using machine learning and deep learning algorithms. In 2022 international conference on computational intelligence and sustainable engineering solutions (CISES) (pp. 393–401). IEEE. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.