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Machine learning in COVID-19: Assessing immunopathology and genetics for tailored care and optimised resource usage

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Known Financial Commitments (USD)

    $1,176,000

  • Funder

    UFM Denmark

  • Principal Investigator

    Clinical Associate Professor PhD Sisse Rye Ostrowski

  • Research Location

    Denmark

  • Lead Research Institution

    Rigshospitalet, Copenhagen University

  • Research Priority Alignment

    N/A

  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    Digital Health

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

The project applies AI to predict disease course of COVID-19 patients. Based on data from electronic health records, genetic analyses (whole genome sequencing) and detailed analyses of the immune system, the project will develop a model that can predict patient disease course, including need for intensive care and/or ventilator treatment. Hereby, the project will promote rapid risk stratification of patients admitted with COVID- 19, allowing for early tailored care. This may both improve patient outcome including survival, and optimise resource usage. Furthermore, the project will reveal the significance of genetics and immunopathology for COVID-19, supporting identification of novel targets and treatments.