A Machine Learning–Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization

Acute traumatic coagulopathy (ATC) is an extremely common but silent murderer; this condition presents early after trauma and impacts approximately 30% of severely injured patients who are admitted to emergency departments (EDs). Given that conventional coagulation indicators usually require more th...

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Detalles Bibliográficos
Autores principales: Li, Kaiyuan, Wu, Huitao, Pan, Fei, Chen, Li, Feng, Cong, Liu, Yihao, Hui, Hui, Cai, Xiaoyu, Che, Hebin, Ma, Yulong, Li, Tanshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7098202/
https://www.ncbi.nlm.nih.gov/pubmed/31908189
http://dx.doi.org/10.1177/1076029619897827

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7098202/
https://www.ncbi.nlm.nih.gov/pubmed/31908189
http://dx.doi.org/10.1177/1076029619897827

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