Cargando…
Machine learning-based analysis of regional differences in out-of-hospital cardiopulmonary arrest outcomes and resuscitation interventions in Japan
Refining out-of-hospital cardiopulmonary arrest (OHCA) resuscitation protocols for local emergency practices is vital. The lack of comprehensive evaluation methods for individualized protocols impedes targeted improvements. Thus, we employed machine learning to assess emergency medical service (EMS)...
Autores principales: | Kawai, Yasuyuki, Yamamoto, Koji, Miyazaki, Keita, Asai, Hideki, Fukushima, Hidetada |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518013/ https://www.ncbi.nlm.nih.gov/pubmed/37741881 http://dx.doi.org/10.1038/s41598-023-43210-x |
Ejemplares similares
-
Visual assessment of interactions among resuscitation activity factors in out-of-hospital cardiopulmonary arrest using a machine learning model
por: Kawai, Yasuyuki, et al.
Publicado: (2022) -
Explainable artificial intelligence-based prediction of poor neurological outcome from head computed tomography in the immediate post-resuscitation phase
por: Kawai, Yasuyuki, et al.
Publicado: (2023) -
Association of multiple rib fractures with the frequency of pneumonia in the post-resuscitation period
por: Kawai, Yasuyuki, et al.
Publicado: (2022) -
Performance review of regional emergency medical service pre‐arrival cardiopulmonary resuscitation with or without dispatcher instruction: a population‐based observational study
por: Fukushima, Hidetada, et al.
Publicado: (2017) -
Quality of dispatch‐assisted cardiopulmonary resuscitation by lay rescuers following a standard protocol in Japan: an observational simulation study
por: Asai, Hideki, et al.
Publicado: (2017)