Open Access
E3S Web Conf.
Volume 351, 2022
10th International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES’2022)
Article Number 01037
Number of page(s) 5
Published online 24 May 2022
  1. [Google Scholar]
  2. [Google Scholar]
  3. Charlotte Andersson, Matthew Nayor, Connie W. Tsao, Daniel Levy, Ramachandran S. Vasan, Framingham Heart Study: JACC Focus Seminar, 1/8, Journal of the American College of Cardiology, Volume 77, Issue 21, Pages 2680–2692 (2021). [CrossRef] [PubMed] [Google Scholar]
  4. Manhar, M. A., Soesanti, I., & Setiawan, N. A.; A Improving Feature Selection on Heart Disease Dataset With Boruta Approach. Journal FORTEI-JEERI, 1(1),41–48(2020) [Google Scholar]
  5. Kursa, Miron B., Jankowski, Aleksander, and Rudnicki, Witold R. ‘Boruta - A System for Feature Selection’: pp. 271–285. 1 Jan. (2010), [Google Scholar]
  6. Arul Jothi, K., Subburam, S., Umadevi, V., & Hemavathy, K. Heart disease prediction system using machine learning. Materials Today: Proceedings. (2021) [Google Scholar]
  7. J. Thomas and R. T. Princy, “Human heart disease prediction system using data mining techniques,” 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), pp. 1–5, DOI: 10.1109/ICCPCT.2016.7530265. (2016) [Google Scholar]
  8. Khemphila and V. Boonjing, “Comparing performances of logistic regression, decision trees, and neural networks for classifying heart disease patients,” 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM), pp. 193–198, DOI: 10.1109/CISIM.2010.5643666. (2010), [CrossRef] [Google Scholar]
  9. last accessed 2021/04/21. [Google Scholar]
  10. Gupta, N., Ahuja, N., Malhotra, S., Bala, A., & Kaur, G. Intelligent heart disease prediction in cloud environment through ensembling. Expert Systems, 34(3), e12207. DOI:10.1111/exsy. 12207. (2017) [CrossRef] [Google Scholar]

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