Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning.

Journal: BMC medical informatics and decision making
Published Date: Feb 8, 2021

Abstract

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident.

Authors

  • Chenxi Sun
    School of Electronics Engineering and Computer Science, Peking University, Beijing, People's Republic of China.
  • Shenda Hong
    National Institute of Health Data Science at Peking University, Peking University, 100871 Beijing, China.
  • Moxian Song
    School of Electronics Engineering and Computer Science, Peking University, Beijing, People's Republic of China.
  • Hongyan Li
    Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China.
  • Zhenjie Wang
    Department of Information Engineering and Automation, Hebei College of Industry and Technology, Shijiazhuang, China.

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