AI to find and monitor aortic valve narrowing (aortic stenosis)
Official title: Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS Study
Funded at Yale University · NIH-11173796 · Data updated 2026-11-12
This project uses AI on a single-lead ECG followed by AI-powered handheld ultrasound to find and track aortic valve narrowing in older adults.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $764,192 |
| NIH project number | 5R01AG089981-02 |
| Project ID | NIH-11173796 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults aged 65 and older, especially those with symptoms like shortness of breath, fainting, or known risk factors for valve disease.
✕Less likely to help
People who are much younger, already have a replaced aortic valve, or cannot undergo ECG or handheld ultrasound imaging may not benefit from this screening approach.
What this research studies
If you take part, you would first have a quick, one-lead ECG that an AI checks for signs of advanced aortic stenosis. If that screen is positive, a second step uses a handheld ultrasound device with AI to automatically image and diagnose valve narrowing without needing a heart imaging expert. The team will run this two-step approach across several hospitals in a randomized trial to see how well it finds people with treatable valve disease and helps guide follow-up. The aim is to make detection and personalized monitoring more convenient so problems can be treated sooner.
Why it matters
Potential benefit: Could allow earlier, easier detection and monitoring of advanced aortic stenosis so patients receive timely treatment and potentially avoid disability.
How similar studies have gone: Earlier work shows AI applied to ECGs can sensitively flag advanced aortic stenosis and AI-enhanced handheld ultrasound can diagnose it, but combining these tools in a multicenter randomized trial is a novel step.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Khera, Rohan — Yale University
- Study coordinator: Khera, Rohan
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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.