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Development and Deployment of Artificial Intelligence (AI) Driven Methods to Enable Chest X-ray Radiography as an Alternative Diagnostic Method for COVID-19 Pneumonia

  • Funded by National Institutes of Health (NIH)
  • Total publications:0 publications

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • Start & end year

    2020
    2021

  • Known Financial Commitments (USD)

    $605,070

  • Funder

    National Institutes of Health (NIH)

  • Principal Investigator

    GUANG-HONG CHEN

  • Research Location

    United States of America

  • Lead Research Institution

    UNIVERSITY OF WISCONSIN-MADISON

  • Research Priority Alignment

    N/A

  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Diagnostics

  • Special Interest Tags

    Innovation

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

ABSTRACT In this competitive revision, within the same scope of developing and deploying algorithms to make a quantum leap in clinical diagnosis as that in our current U01EB021183, we would like to revise the original aims to add a new Aim to leverage our expertise in the areas of algorithm development and clinical translation to make immediate contributions to combat the COVID-19 pandemic. Specifically, we propose to develop and deploy artificial intelligence (AI) methods to enable chest x-ray radiography (CXR) as an alternative diagnostic tool to diagnose COVID-19 pneumonia, to rapidly triage patients for appropriate treatment, to monitor the treatment response in a contained environment, and to optimize the distribution of the limited medical resources during thecurrent COVID-19 crisis.