A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study.

Journal: IEEE journal of biomedical and health informatics
Published Date: Jul 27, 2021

Abstract

OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed.

Authors

  • Siwen Wang
    College of Science, Huazhong Agricultural University, Wuhan 430070, P.R. China.
  • Di Dong
    The Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Liang Li
    School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China.
  • Hailin Li
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Yan Bai
    Department of Radiology, Henan Provincial People's Hospital, China.
  • Yahua Hu
  • Yuanyi Huang
  • Xiangrong Yu
  • Sibin Liu
  • Xiaoming Qiu
    Dept of Radiology, Huangshi Central Hospital, Affiliated Hospital of Hubei Polytechnic University, Edong Healthcare Group, Huangshi, China.
  • Ligong Lu
    Zhuhai People Hospital, Zhuhai, China.
  • Meiyun Wang
  • Yunfei Zha
    Department of Radiology, Department of Infection Prevention and Control, Renmin Hospital, Wuhan University, Wuhan, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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