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 the current COVID-19 crisis.

Public Health Relevance

In this project, our overarching objective is to develop automated artificial intelligence (AI)-based algorithms to help radiologists to differentiate COVID-19 related pneumonia from other non-COVID-19 related pneumonia using CXR images. The advantages of the proposed AI equipped CXR technique include: i) widely available, ii) inexpensive, iii) excellent coronavirus exposure profile for patient, technologist, and equipment, and iv) rapid and automated DL interpretation, which is effectively instantaneous.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01EB021183-04S1
Application #
10156179
Study Section
Program Officer
Shabestari, Behrouz
Project Start
2020-07-21
Project End
2021-07-20
Budget Start
2020-07-21
Budget End
2021-07-20
Support Year
4
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of Wisconsin Madison
Department
Physics
Type
Schools of Medicine
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
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