Robust Heart Disease Prognosis: Integrating Extended Isolation Forest Outlier Detection with Advanced Prediction Models

Author:

Javid Irfan,Hassan Norlida,Ghazali Rozaida,Hassim Yana Mazwin Mohmad,Batool Tuba,Husaini Noor Aida,Jafri Syed Irteza Hussain

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Harvard Medical School. *roughout life, heart attacks are twice more common in men than women (2020). https://www.health.harvard.edu/heart-health/throughout-life-heartattacks are twice as common in men than women

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3. Shalev-Shwartz, S., Ben-David, S.: Understanding machine learning, From 4eory to Algorithms, Cambridge University Press, Cambridge, UK (2020)

4. Melillo, P., De Luca, N., Bracale, M., Pecchia, L.: Classification tree for risk assessment in patients suffering from congestive heart failure via long-term heart rate variability. IEEE J. Biomed. Health Inform. 17(3), 727–733 (2013)

5. Al Rahhal, M.M., Bazi, Y., AlHichri, H., Alajlan, N., Melgani, F., Yager, R.R.: Deep learning approach for active classification of electrocardiogram signals. Inform. Sci. 345, 340–354 (2016). https://doi.org/10.1016/j.ins.2016.01.082

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