Development of a machine-learning algorithm to predict in-hospital cardiac arrest for emergency department patients using a nationwide database

In this retrospective observational study, we aimed to develop a machine-learning model using data obtained at the prehospital stage to predict in-hospital cardiac arrest in the emergency department (ED) of patients transferred via emergency medical services. The dataset was constructed by attaching...

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Detalles Bibliográficos
Autores principales: Kim, Ji Hoon, Choi, Arom, Kim, Min Joung, Hyun, Heejung, Kim, Sunhee, Chang, Hyuk-Jae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758227/
https://www.ncbi.nlm.nih.gov/pubmed/36526686
http://dx.doi.org/10.1038/s41598-022-26167-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758227/
https://www.ncbi.nlm.nih.gov/pubmed/36526686
http://dx.doi.org/10.1038/s41598-022-26167-1

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