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-19Start & end year
20202021Known Financial Commitments (USD)
$605,070Funder
National Institutes of Health (NIH)Principal Investigator
GUANG-HONG CHENResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF WISCONSIN-MADISONResearch 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.