Machine learning model predicts short-term mortality among prehospital patients: A prospective development study from Finland

AIM: To show whether adding blood glucose to the National Early Warning Score (NEWS) parameters in a machine learning model predicts 30-day mortality more precisely than the standard NEWS in a prehospital setting. METHODS: In this study, vital sign data prospectively collected from 3632 unselected p...

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Detalles Bibliográficos
Autores principales: Tamminen, Joonas, Kallonen, Antti, Hoppu, Sanna, Kalliomäki, Jari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Clinical Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244527/
https://www.ncbi.nlm.nih.gov/pubmed/34223354
http://dx.doi.org/10.1016/j.resplu.2021.100089

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8244527/
https://www.ncbi.nlm.nih.gov/pubmed/34223354
http://dx.doi.org/10.1016/j.resplu.2021.100089

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