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Deep learning for EEG-based prognostication after cardiac arrest: from current research to future clinical applications
Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic encephalopathy. Electroencephalography (EEG) is routinely used to assess neural functions in comatose patients. Currently, EEG-ba...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408678/ https://www.ncbi.nlm.nih.gov/pubmed/37560450 http://dx.doi.org/10.3389/fneur.2023.1183810 |