Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study
Dublin Core
Title
Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study
Description
Overcrowding in emergency departments (ED) is a major public health issue, leading to increased workload and exhaustion for the teams, resulting poor outcomes. It seems interesting to be able to predict the admissions of patients in the ED.
Creator
Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan & Laure Abensur Vuillaume
Source
https://link.springer.com/article/10.1186/s12873-024-01141-4
Publisher
https://link.springer.com/journal/12873
Date
06 january 2025
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan & Laure Abensur Vuillaume , “Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study,” Repository Horizon University Indonesia, accessed June 19, 2025, https://repository.horizon.ac.id/items/show/9530.