Random forest machine learning method outperforms prehospital National Early Warning Score for predicting one-day mortality: A retrospective study

The National Early Warning Score (NEWS) is a validated method for predicting clinical deterioration in hospital wards, but its performance in prehospital settings remains controversial. Modern machine learning models may outperform traditional statistical analyses for predicting short-term mortality...

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Bibliographic Details
Published in:	Resuscitation plus Vol. 4; p. 100046
Main Authors:	Pirneskoski, Jussi, Tamminen, Joonas, Kallonen, Antti, Nurmi, Jouni, Kuisma, Markku, Olkkola, Klaus T., Hoppu, Sanna
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier B.V 01.12.2020 Elsevier
Subjects:	Cardiac arrest prevention Clinical Paper Early warning score Emergency Emergency medical services Machine learning National Early Warning Score NEWS Prehospital Random forest Early warning score Cardiac arrest prevention NEWS Machine learning Random forest National Early Warning Score Emergency medical services Prehospital
ISSN:	2666-5204, 2666-5204
Online Access:	Get full text
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