Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges

Development and evaluation of regression tree models for predicting in-hospital mortality of a national registry of COVID-19 patients over six pandemic surges

Abstract Background Objective prognostic information is essential for good clinical decision making. In case of unknown diseases, scarcity of evidence and limited tacit knowledge prevent obtaining this information. Prediction models can be useful, but need to be not only evaluated on how well they p...

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Bibliographic Details
Main Authors: M. C. Schut, D. A. Dongelmans, D. W. de Lange, S. Brinkman, Dutch COVID-19 Research Consortium, N. F. de Keizer, A. Abu-Hanna
Format: Article
Language:English
Published: BMC 2024-01-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Decision rules
Decision and regression trees
Prediction model
Intensive care
COVID-19
In-hospital mortality
Online Access:https://doi.org/10.1186/s12911-023-02401-2

Internet

https://doi.org/10.1186/s12911-023-02401-2

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