Nature Communications (Jul 2020)
Early triage of critically ill COVID-19 patients using deep learning
- Wenhua Liang,
- Jianhua Yao,
- Ailan Chen,
- Qingquan Lv,
- Mark Zanin,
- Jun Liu,
- SookSan Wong,
- Yimin Li,
- Jiatao Lu,
- Hengrui Liang,
- Guoqiang Chen,
- Haiyan Guo,
- Jun Guo,
- Rong Zhou,
- Limin Ou,
- Niyun Zhou,
- Hanbo Chen,
- Fan Yang,
- Xiao Han,
- Wenjing Huan,
- Weimin Tang,
- Weijie Guan,
- Zisheng Chen,
- Yi Zhao,
- Ling Sang,
- Yuanda Xu,
- Wei Wang,
- Shiyue Li,
- Ligong Lu,
- Nuofu Zhang,
- Nanshan Zhong,
- Junzhou Huang,
- Jianxing He
Affiliations
- Wenhua Liang
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Jianhua Yao
- Tencent AI Lab
- Ailan Chen
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Qingquan Lv
- Hankou Hospital
- Mark Zanin
- School of Public Health, The University of Hong Kong
- Jun Liu
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- SookSan Wong
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Yimin Li
- Department of Intensive Care Unit, The First Affiliated Hospital of Guangzhou Medical University
- Jiatao Lu
- Hankou Hospital
- Hengrui Liang
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Guoqiang Chen
- Foshan Hospital
- Haiyan Guo
- Foshan Hospital
- Jun Guo
- Daye Hospital
- Rong Zhou
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Limin Ou
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Niyun Zhou
- Tencent AI Lab
- Hanbo Chen
- Tencent AI Lab
- Fan Yang
- Tencent AI Lab
- Xiao Han
- Tencent AI Lab
- Wenjing Huan
- Tencent Healthcare
- Weimin Tang
- Tencent Healthcare
- Weijie Guan
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Zisheng Chen
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Yi Zhao
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Ling Sang
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Yuanda Xu
- Department of Intensive Care Unit, The First Affiliated Hospital of Guangzhou Medical University
- Wei Wang
- Department of Thoracic Surgery, The First Affiliated Hospital of Guangzhou Medical University
- Shiyue Li
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Ligong Lu
- Zhuhai People Hospital
- Nuofu Zhang
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Nanshan Zhong
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- Junzhou Huang
- Tencent AI Lab
- Jianxing He
- China State Key Laboratory of Respiratory Disease and National Clinical Research Center for Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University
- DOI
- https://doi.org/10.1038/s41467-020-17280-8
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 7
Abstract
The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern and early assessment would be vital. Here, the authors show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission.
