Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial

IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation. OBJECTIVE: To examine how a machine learning model trained to identify OHCA and a...

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Detalles Bibliográficos
Autores principales: Blomberg, Stig Nikolaj, Christensen, Helle Collatz, Lippert, Freddy, Ersbøll, Annette Kjær, Torp-Petersen, Christian, Sayre, Michael R., Kudenchuk, Peter J., Folke, Fredrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788469/
https://www.ncbi.nlm.nih.gov/pubmed/33404620
http://dx.doi.org/10.1001/jamanetworkopen.2020.32320

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788469/
https://www.ncbi.nlm.nih.gov/pubmed/33404620
http://dx.doi.org/10.1001/jamanetworkopen.2020.32320

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