Risk of mortality and cardiopulmonary arrest in critical patients presenting to the emergency department using machine learning and natural language processing

Emergency department triage is the first point in time when a patient’s acuity level is determined. The time to assign a priority at triage is short and it is vital to accurately stratify patients at this stage, since under-triage can lead to increased morbidity, mortality and costs. Our aim was to...

Description complète

Enregistré dans:
Détails bibliographiques
Publié dans:PLoS One
Auteurs principaux: Fernandes, Marta, Mendes, Rúben, Vieira, Susana M., Leite, Francisca, Palos, Carlos, Johnson, Alistair, Finkelstein, Stan, Horng, Steven, Celi, Leo Anthony
Format: Artigo
Langue:Inglês
Publié: Public Library of Science 2020
Sujets:
Research Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7117713/
https://ncbi.nlm.nih.gov/pubmed/32240233
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0230876
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires