A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest

Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of-hospital cardiac arrest (OHCA) cases. Predicting whether a patient in PEA will convert to return of spontaneous circ...

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Detalles Bibliográficos
Autores principales: Urteaga, Jon, Aramendi, Elisabete, Elola, Andoni, Irusta, Unai, Idris, Ahamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307658/
https://www.ncbi.nlm.nih.gov/pubmed/34209405
http://dx.doi.org/10.3390/e23070847

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307658/
https://www.ncbi.nlm.nih.gov/pubmed/34209405
http://dx.doi.org/10.3390/e23070847

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