A novel survival algorithm in covid-19 intensive care patients: The classification and regression tree (crt) method

dc.contributor.author	Dağıstanlı, S.
dc.contributor.author	Sönmez, S.
dc.contributor.author	Ünsel, M.
dc.contributor.author	Bozdağ, E.
dc.contributor.author	Kocataş, A.
dc.contributor.author	Boşat, M.
dc.contributor.author	Yurtseven, E.
dc.contributor.author	Çalışkan, Z.
dc.contributor.author	Günver, M.G.
dc.date.accessioned	2021-12-21T08:40:34Z
dc.date.available	2021-12-21T08:40:34Z
dc.date.issued	2021
dc.identifier.issn	16806905
dc.identifier.uri	https://doi.org/10.4314/ahs.v21i3.16
dc.identifier.uri	http://dspace.yeniyuzyil.edu.tr:8080/xmlui/handle/20.500.12629/1079
dc.description.abstract	Background/aim: The present study aimed to create a decision tree for the identification of clinical, laboratory and radiological data of individuals with COVID-19 diagnosis or suspicion of Covid-19 in the Intensive Care Units of a Training and Research H
dc.language.iso	English
dc.publisher	Makerere University, Medical School
dc.rights	All Open Access, Gold
dc.title	A novel survival algorithm in covid-19 intensive care patients: The classification and regression tree (crt) method
dc.type	Article
dc.relation.journal	African Health Sciences
dc.identifier.issue	3
dc.identifier.startpage	1083
dc.identifier.endpage	1092
dc.identifier.volume	21
dc.identifier.doi	10.4314/ahs.v21i3.16
dc.relation.issue	3
dc.relation.volume	21