Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER

AIMS: Coagulation abnormality is one of the primary concerns for patients with spontaneous intracerebral hemorrhage admitted to ER. Conventional laboratory indicators require hours for coagulopathy diagnosis, which brings difficulties for appropriate intervention within the optimal window. This stud...

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Detalles Bibliográficos
Autores principales: Zhu, Fengping, Pan, Zhiguang, Tang, Ying, Fu, Pengfei, Cheng, Sijie, Hou, Wenzhong, Zhang, Qi, Huang, Hong, Sun, Yirui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804781/
https://www.ncbi.nlm.nih.gov/pubmed/33249760
http://dx.doi.org/10.1111/cns.13509

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804781/
https://www.ncbi.nlm.nih.gov/pubmed/33249760
http://dx.doi.org/10.1111/cns.13509

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