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

> **NIH NIH U01** · UNIVERSITY OF WISCONSIN-MADISON · 2020 · $605,070

## 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 the
current COVID-19 crisis.

## Key facts

- **NIH application ID:** 10156179
- **Project number:** 3U01EB021183-04S1
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** Guang-Hong Chen
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $605,070
- **Award type:** 3
- **Project period:** 2020-07-21 → 2022-07-20

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10156179

## Citation

> US National Institutes of Health, RePORTER application 10156179, Development and Deployment of Artificial Intelligence (AI) Driven Methods to Enable Chest X-ray Radiography as an Alternative Diagnostic Method for COVID-19 Pneumonia (3U01EB021183-04S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10156179. Licensed CC0.

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