Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients

OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral ischemia (DCI). The ability to accurately predict survival for SAH patients during the hospital course would provide valuable information for healthcare...

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Detalles Bibliográficos
Autores principales: Yu, Duo, Williams, George W., Aguilar, David, Yamal, José‐Miguel, Maroufy, Vahed, Wang, Xueying, Zhang, Chenguang, Huang, Yuefan, Gu, Yuxuan, Talebi, Yashar, Wu, Hulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664270/
https://www.ncbi.nlm.nih.gov/pubmed/32990362
http://dx.doi.org/10.1002/acn3.51208

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664270/
https://www.ncbi.nlm.nih.gov/pubmed/32990362
http://dx.doi.org/10.1002/acn3.51208

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