Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Addendum: Early triage of critically ill COVID-19 patients using deep learning
por: Liang, Wenhua, et al.
Publicado: (2021) -
Artificial intelligence for stepwise diagnosis and monitoring of COVID-19
por: Liang, Hengrui, et al.
Publicado: (2022) -
Attention should be paid to venous thromboembolism prophylaxis in the management of COVID-19
por: Wang, Tao, et al.
Publicado: (2020) -
Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China
por: Liang, Wenhua, et al.
Publicado: (2020) -
An annual review of the remarkable advances in lung cancer clinical research in 2019
por: Cheng, Bo, et al.
Publicado: (2020)