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Dergiler / Bulletin of Biotechnology / 2025 / Volume: 6 Issue: 2

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

Fatih Üçkardeş(ADIYAMAN UNIVERSITY)0000-0003-0677-7606
Ercan Çil(ADIYAMAN UNIVERSITY)0000-0002-8981-4232
Fahrettin Kaya(KAHRAMANMARAS SUTCU IMAM UNIVERSITY)0000-0003-1666-4859
Hakan Sezgin Sayiner(ADIYAMAN UNIVERSITY)
Önder Yumrutaş(ADIYAMAN ÜNİVERSİTESİ)
Sayfa
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Yayın Tarihi
2025-12-29
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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.

📌 3 Maddede Bu Makale

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Amaç & Hipotez: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.
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Temel Bulgular & Veri: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.
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Sonuç & Katkı: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.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2020 Verileri
⚙️Değişkenler:Personalized medicine · Ensemble learning · machine learning

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.

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Bu Makaleye Atıf Yap

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, Volume: 6 Issue: 2. https://doi.org/10.51539/biotech.1739101

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