Improving tuberculosis screening using AI-assisted digital X-rays
Official title: Optimizing Implementation of Digital X-ray with Computer-Aided Detection for Community-Based Tuberculosis Screening
Funded at Johns Hopkins University · NIH-10949957 · Data updated 2026-11-12
This study is looking at how to use digital X-ray technology and smart computer tools to make it easier and faster to find tuberculosis in communities in sub-Saharan Africa, helping people get diagnosed and treated sooner.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Johns Hopkins University NIH-funded |
| Lab location | 1 site (Baltimore, United States) |
| Project start | August 29, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $198,720 |
| NIH project number | 1K23AI185268-01 |
| Project ID | NIH-10949957 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals living in high-risk areas of sub-Saharan Africa who may be exposed to tuberculosis.
✕Less likely to help
Patients who do not reside in high-risk regions for tuberculosis or those who are not at risk for the disease may not benefit from this research.
What this research studies
This research focuses on enhancing tuberculosis (TB) screening in communities by utilizing digital X-ray technology combined with computer-aided detection (CAD). The study aims to optimize how these AI systems are implemented in sub-Saharan Africa, where TB is prevalent and qualified readers for X-rays are scarce. By evaluating different screening strategies, the research seeks to improve early diagnosis rates and ensure that high-risk populations receive timely treatment. Patients will benefit from a more efficient screening process that leverages advanced technology to identify TB cases more accurately.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate TB diagnoses, significantly reducing the burden of the disease in affected communities.
How similar studies have gone: Previous research has shown promise in using AI for medical imaging, indicating that this approach could be effective for TB screening as well.
Where this research is happening
-
Johns Hopkins University
Baltimore, United States Active
Researchers
- Principal investigator: Sung, Joowhan — Johns Hopkins University
- Study coordinator: Sung, Joowhan
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.