Emergency department triage prediction of clinical outcomes using machine learning models

BACKGROUND: Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional appr...

Descripción completa

Detalles Bibliográficos
Autores principales: Raita, Yoshihiko, Goto, Tadahiro, Faridi, Mohammad Kamal, Brown, David F. M., Camargo, Carlos A., Hasegawa, Kohei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387562/
https://www.ncbi.nlm.nih.gov/pubmed/30795786
http://dx.doi.org/10.1186/s13054-019-2351-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387562/
https://www.ncbi.nlm.nih.gov/pubmed/30795786
http://dx.doi.org/10.1186/s13054-019-2351-7

Ejemplares similares