Learning From Past Respiratory Infections to Predict COVID-19 Outcomes: Retrospective Study.

Journal: Journal of medical Internet research
Published Date: Feb 22, 2021

Abstract

BACKGROUND: For the clinical care of patients with well-established diseases, randomized trials, literature, and research are supplemented with clinical judgment to understand disease prognosis and inform treatment choices. In the void created by a lack of clinical experience with COVID-19, artificial intelligence (AI) may be an important tool to bolster clinical judgment and decision making. However, a lack of clinical data restricts the design and development of such AI tools, particularly in preparation for an impending crisis or pandemic.

Authors

  • Shengtian Sang
    School of Computer Science and Technology, Dalian University of Technology, Dalian, China. sangst@mail.dlut.edu.cn.
  • Ran Sun
    Department of Medicine, Stanford University, Stanford, California, USA.
  • Jean Coquet
    Department of Medicine, Stanford University, Stanford, CA, USA.
  • Harris Carmichael
    Intermountain Health, Salt Lake City, UT, United States.
  • Tina Seto
    Stanford University, School of Medicine, Stanford, CA.
  • Tina Hernandez-Boussard
    Stanford Center for Biomedical Informatics Research, Stanford, California 94305, USA.

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