Real-time machine learning model to predict in-hospital cardiac arrest using heart rate variability in ICU

Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU) allows prompt interventions to improve patient outcomes. We developed and validated a machine learning-based real-time model for in-hospital cardiac arrest predictions using electrocardiogram (ECG)-based heart...

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Detalles Bibliográficos
Autores principales: Lee, Hyeonhoon, Yang, Hyun-Lim, Ryu, Ho Geol, Jung, Chul-Woo, Cho, Youn Joung, Yoon, Soo Bin, Yoon, Hyun-Kyu, Lee, Hyung-Chul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665411/
https://www.ncbi.nlm.nih.gov/pubmed/37993540
http://dx.doi.org/10.1038/s41746-023-00960-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665411/
https://www.ncbi.nlm.nih.gov/pubmed/37993540
http://dx.doi.org/10.1038/s41746-023-00960-2

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