Using AI to improve detection and monitoring of aortic stenosis
Official title: Deep learning enhanced detection and personalized monitoring of aortic stenosis - The DETECT-AS Study
Funded at Yale University · NIH-10944019 · Data updated 2026-11-12
This study is exploring how artificial intelligence can help doctors find and keep track of aortic stenosis, a heart condition that mainly affects older adults, by using easy-to-use tools like simple heart tests and handheld ultrasounds to spot serious cases more accurately and quickly.
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 | 2024 |
| Award (this year) | $813,824 |
| NIH project number | 1R01AG089981-01 |
| Project ID | NIH-10944019 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are older adults, particularly those aged 65 and over, who may be at risk for aortic stenosis.
✕Less likely to help
Patients under the age of 21 or those without aortic stenosis may not benefit from this research.
What this research studies
This research investigates how artificial intelligence can enhance the detection and monitoring of aortic stenosis, a condition that narrows the aortic valve and primarily affects older adults. The study employs a two-stage screening approach using AI models applied to simple electrocardiograms and handheld ultrasound devices to identify advanced cases of the disease. By automating the diagnosis process, the research aims to improve the accuracy and efficiency of identifying patients who need treatment. This innovative strategy could lead to better management of aortic stenosis and improved patient outcomes.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnosis of aortic stenosis, ultimately improving treatment outcomes for patients.
How similar studies have gone: Other research has shown promise in using AI for cardiovascular conditions, indicating that this approach could be effective in improving patient care.
Where this research is happening
-
Yale University
New Haven, United States Active
Researchers
- Principal investigator: Khera, Rohan — Yale University
- Study coordinator: Khera, Rohan
Related research
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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.