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AI-empowered Real-time COVID-19 Symptom Monitoring and Prediction among Senior Residents

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Funder

    Roche Holding AG (Roche)

  • Principal Investigator

    Samira Rahimi

  • Research Location

    Canada

  • Lead Research Institution

    McGill University

  • Research Priority Alignment

    N/A

  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    N/A

  • Study Type

    Clinical

  • Clinical Trial Details

    Not applicable

  • Broad Policy Alignment

    Pending

  • Age Group

    Adults (18 and older)Older adults (65 and older)

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

Long-term care (LTC) homes are being disproportionately affected by COVID-19. This project will implement proven remote monitoring technology empowered with Artificial Intelligence to track, monitor and predict senior residents' symptoms. The detection and prediction of asymptomatic changes will facilitate rapid isolation and can save thousands of lives. The technology will alert the providers when COVID-19 symptoms are identified/predicted and monitor any decompensation. This project will monitor 60 senior residents in two LTC homes (Toronto and Montreal) and then scale up for the entire LTC homes, and intends to protect LTC home staff and frail residents from exposure to COVID-19 by enabling remote monitoring.