Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models

Fatih Üçkardeş; Ercan Çil; Fahrettin Kaya; Hakan Sezgin Sayiner; Önder Yumrutaş

doi:10.51539/biotech.1739101

Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models

Abstract

The aim of study was aimed to predict the prognostic factors that cause mortality related to the Covid 19 with machine and ensemble learning model. Patient information was collected from the Adıyaman Education and Research Hospital between 01 January 2020 and 31 December 2021.Totally, 487 patients were included in the study. Random Forest (rf), Support Vector Machine with a Radial Basis Kernel Function (svmRadial), C5.0, Ranger and Gradient Boosting Machine (Gbm) models and the ensemble model were used as machine learning models. Ibreakdown plot was used to individualize the results. According to the machine classification criteria, although all models performed strongly, the Gbm model had the highest classification criteria. Consequently, it is thought that it may play an important role not only for Covid 19, but also for the classification of other diseases, making individual risk estimations and creating patient-specific personal treatment programs.

Keywords

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Details

Primary Language

English

Subjects

Clinical Sciences (Other)

Journal Section

Research Article

Authors

Fatih Üçkardeş
0000-0003-0677-7606
Türkiye

Ercan Çil
0000-0002-8981-4232
Türkiye

Fahrettin Kaya
0000-0003-1666-4859
Türkiye

Hakan Sezgin Sayiner
Türkiye

Önder Yumrutaş ^*
Türkiye

Publication Date

December 29, 2025

Submission Date

July 10, 2025

Acceptance Date

September 7, 2025

Published in Issue

Year 2025 Volume: 6 Number: 2

DOI

https://doi.org/10.51539/biotech.1739101

IZ

https://izlik.org/JA54AP69JJ

Cite

RIS / Bibtex

APA

Üçkardeş, F., Çil, E., Kaya, F., Sayiner, H. S., & Yumrutaş, Ö. (2025). Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models. Bulletin of Biotechnology, 6(2), 46-52. https://doi.org/10.51539/biotech.1739101

AMA

1.Üçkardeş F, Çil E, Kaya F, Sayiner HS, Yumrutaş Ö. Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models. Bull. Biotechnol. 2025;6(2):46-52. doi:10.51539/biotech.1739101

Chicago

Üçkardeş, Fatih, Ercan Çil, Fahrettin Kaya, Hakan Sezgin Sayiner, and Önder Yumrutaş. 2025. “Prediction of Factors Causing Death in Covid 19 Patients With Machine and Ensemble Learning Models”. Bulletin of Biotechnology 6 (2): 46-52. https://doi.org/10.51539/biotech.1739101.

EndNote

Üçkardeş F, Çil E, Kaya F, Sayiner HS, Yumrutaş Ö (December 1, 2025) Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models. Bulletin of Biotechnology 6 2 46–52.

IEEE

[1]F. Üçkardeş, E. Çil, F. Kaya, H. S. Sayiner, and Ö. Yumrutaş, “Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models”, Bull. Biotechnol., vol. 6, no. 2, pp. 46–52, Dec. 2025, doi: 10.51539/biotech.1739101.

ISNAD

Üçkardeş, Fatih - Çil, Ercan - Kaya, Fahrettin - Sayiner, Hakan Sezgin - Yumrutaş, Önder. “Prediction of Factors Causing Death in Covid 19 Patients With Machine and Ensemble Learning Models”. Bulletin of Biotechnology 6/2 (December 1, 2025): 46-52. https://doi.org/10.51539/biotech.1739101.

JAMA

1.Üçkardeş F, Çil E, Kaya F, Sayiner HS, Yumrutaş Ö. Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models. Bull. Biotechnol. 2025;6:46–52.

MLA

Üçkardeş, Fatih, et al. “Prediction of Factors Causing Death in Covid 19 Patients With Machine and Ensemble Learning Models”. Bulletin of Biotechnology, vol. 6, no. 2, Dec. 2025, pp. 46-52, doi:10.51539/biotech.1739101.

Vancouver

1.Fatih Üçkardeş, Ercan Çil, Fahrettin Kaya, Hakan Sezgin Sayiner, Önder Yumrutaş. Prediction of factors causing death in Covid 19 patients with machine and ensemble learning models. Bull. Biotechnol. 2025 Dec. 1;6(2):46-52. doi:10.51539/biotech.1739101