ConceptWAS: A high-throughput method for early identification of COVID-19 presenting symptoms and characteristics from clinical notes.

Journal: Journal of biomedical informatics
Published Date: May 1, 2021

Abstract

OBJECTIVE: Identifying symptoms and characteristics highly specific to coronavirus disease 2019 (COVID-19) would improve the clinical and public health response to this pandemic challenge. Here, we describe a high-throughput approach - Concept-Wide Association Study (ConceptWAS) - that systematically scans a disease's clinical manifestations from clinical notes. We used this method to identify symptoms specific to COVID-19 early in the course of the pandemic.

Authors

  • Juan Zhao
    Hefei University, Hefei, China.
  • Monika E Grabowska
    Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, TN, USA.
  • Vern Eric Kerchberger
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Division of Allergy, Pulmonary & Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Joshua C Smith
    Vanderbilt University Medical Center, Nashville, TN.
  • H Nur Eken
    Vanderbilt University School of Medicine, Nashville, TN, USA.
  • QiPing Feng
    Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA.
  • Josh F Peterson
    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
  • S Trent Rosenbloom
    Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee.
  • Kevin B Johnson
    Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, United States.
  • Wei-Qi Wei
    Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, USA.

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