AI-powered screening and monitoring for aortic stenosis in older adults
Official title: Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS Study
Funded at Yale University · NIH-11395442 · Data updated 2026-11-12
A powerful new AI-based approach uses a simple heart rhythm test and a hand-held ultrasound to detect and monitor advanced aortic valve narrowing in people aged 65 and older.
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 | 2026 |
| Award (this year) | $829,328 |
| NIH project number | 5R01AG089981-03 |
| Project ID | NIH-11395442 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults aged 65 and older, especially those undergoing routine evaluation or with suspected or known aortic valve disease.
✕Less likely to help
Patients without or with very early-stage disease may not experience direct benefit from the screening strategy.
What this research studies
This project aims to transform how aortic stenosis is detected and followed by using artificial intelligence to read 1-lead ECGs and a handheld ultrasound to identify advanced disease. It plans a multicenter pragmatic randomized trial to test a two-step screening process driven by AI, with the goal of catching advanced AS earlier and tracking its progression. Participants will be adults 65 and older who may undergo routine screening or follow-up for valve disease, with ongoing monitoring to tailor care. The study leverages real-world clinical settings to determine how well this AI-guided strategy works in everyday practice.
Why it matters
Potential benefit: If successful, this approach could enable earlier, easier detection and more personalized monitoring of aortic stenosis, potentially improving outcomes.
How similar studies have gone: Previous work suggests AI-ECG and AI-enhanced ultrasound can improve detection, but this two-stage pragmatic trial is a novel combination.
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.