Predicting in-hospital mortality in adult non-traumatic emergency department patients: a retrospective comparison of the Modified Early Warning Score (MEWS) and machine learning approach

Background A feasible and accurate risk prediction systems for emergency department (ED) patients is urgently required. The Modified Early Warning Score (MEWS) is a wide-used tool to predict clinical outcomes in ED. Literatures showed that machine learning (ML) had better predictability in specific...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Kuan-Han Wu, Fu-Jen Cheng, Hsiang-Ling Tai, Jui-Cheng Wang, Yii-Ting Huang, Chih-Min Su, Yun-Nan Chang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	PeerJ Inc. 2021-08-01
Schriftenreihe:	PeerJ
Schlagworte:	Mortality prediction MEWS Machine learning
Online-Zugang:	https://peerj.com/articles/11988.pdf
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