Machine Learning to Predict Disease Severity and Progression in Hospitalized COVID-19 Patients Using Laboratory Data on Admission

Background: Herein, we aimed to develop and test machine learning (ML) models to predict disease severity and/or progression in hospitalized COVID-19 patients through baseline laboratory features.Methods: In this retrospective study of hospitalized COVID-19 patients admitted to a tertiary care cente...

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Ngā kaituhi matua:	Gökhan Tazegül, Volkan Aydın, Elif Tükenmez Tigen, Buket Erturk Sengel, Kübra Köksal, Buket Doğan, Sait Karakurt, Zehra Aysun Altıkardeş, Lütfiye Mülazimoğlu, Ali Serdar Fak, Abdulsamet Aktaş, Uluhan Sili, Abidin Gündoğdu, Fethi Gül, Sena Tokay Tarhan, Emel Eryüksel, Mümine Topçu, Berrin Aysevinç, Songül Çeçen Düzel, Tuba Güçtekin, Derya Kocakaya, Beste Ozben, Halil Atas, Kürşat Tigen, Ahmet Altuğ Çinçin, Bülent Mutlu, Alper Kepez, Mehmet Baran Balcan, Ayla Erdoğan, Emre Çapar, Ömer Ataç, Beliz Bilgili, İsmail Cinel, Ahmet Akıcı, Haner Direskeneli
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	Nizameddin KOCA 2024-10-01
Rangatū:	Turkish Journal of Internal Medicine
Urunga tuihono:	https://dergipark.org.tr/en/download/article-file/4010075
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