Using AI to analyze lung sounds for better diagnosis of tuberculosis in children
Official title: Automated lung sound analysis to improve the clinical diagnosis of pulmonary tuberculosis in children
Funded at University of California, San Francisco · NIH-10930100 · Data updated 2026-11-12
This study is testing a new way to help doctors diagnose tuberculosis (TB) in kids by using an AI program that listens to their lung sounds with a digital stethoscope, making it easier and more accurate to find out if they have TB without needing invasive tests.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project start | September 15, 2023 |
| Project end | August 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $604,832 |
| NIH project number | 5R01HL169449-02 |
| Project ID | NIH-10930100 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children under 21 years old who are being evaluated for pulmonary tuberculosis.
✕Less likely to help
Patients who are not being evaluated for tuberculosis or are over 21 years old may not benefit from this research.
What this research studies
This research aims to improve the diagnosis of pulmonary tuberculosis (TB) in children by using an artificial intelligence (AI) algorithm that analyzes lung sounds collected through a digital stethoscope. Traditional methods for diagnosing TB in children can be invasive and often yield unreliable results, especially in low-resource settings. By leveraging existing patient data and advanced AI technology, the study seeks to enhance the accuracy of TB treatment decision algorithms, potentially leading to faster and more reliable diagnoses for affected children.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of tuberculosis in children, ultimately reducing mortality rates.
How similar studies have gone: Previous research has shown promise in using AI for medical diagnostics, indicating that this approach could be effective, though it is still relatively novel in the context of childhood tuberculosis.
Where this research is happening
-
University of California, San Francisco
San Francisco, United States Active
Researchers
- Principal investigator: Jaganath, Devan — University of California, San Francisco
- Study coordinator: Jaganath, Devan
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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.