Early triage of critically ill COVID-19 patients using deep learning

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness ba...

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Detalles Bibliográficos
Autores principales: Liang, Wenhua, Yao, Jianhua, Chen, Ailan, Lv, Qingquan, Zanin, Mark, Liu, Jun, Wong, SookSan, Li, Yimin, Lu, Jiatao, Liang, Hengrui, Chen, Guoqiang, Guo, Haiyan, Guo, Jun, Zhou, Rong, Ou, Limin, Zhou, Niyun, Chen, Hanbo, Yang, Fan, Han, Xiao, Huan, Wenjing, Tang, Weimin, Guan, Weijie, Chen, Zisheng, Zhao, Yi, Sang, Ling, Xu, Yuanda, Wang, Wei, Li, Shiyue, Lu, Ligong, Zhang, Nuofu, Zhong, Nanshan, Huang, Junzhou, He, Jianxing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363899/
https://www.ncbi.nlm.nih.gov/pubmed/32669540
http://dx.doi.org/10.1038/s41467-020-17280-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363899/
https://www.ncbi.nlm.nih.gov/pubmed/32669540
http://dx.doi.org/10.1038/s41467-020-17280-8

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