AI-powered ultrasound tool to help diagnose PCOS
Official title: Artificial intelligence for the automated detection of polycystic ovary syndrome on ultrasonography
Funded at Cornell University · NIH-11378391 · Data updated 2026-11-12
A new AI-based tool uses ultrasound images to help doctors reliably identify polycystic ovary syndrome (PCOS) in reproductive-age women.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cornell University NIH-funded |
| Lab location | 1 site (Ithaca, United States) |
| Project start | August 1, 2025 |
| Project end | July 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $208,000 |
| NIH project number | 5R21HD116139-02 |
| Project ID | NIH-11378391 on NIH RePORTER |
Who could benefit from this research
✓Could help
Women of reproductive age who are evaluated for PCOS and undergo ovarian ultrasound.
✕Less likely to help
Patients who do not have PCOS or whose condition cannot be diagnosed with ultrasound-based AI may not benefit.
What this research studies
This project aims to create an AI model that analyzes ultrasound images of the ovaries to detect PCOS and combines imaging with clinical and lab data to improve diagnostic accuracy. It builds on existing ultrasound criteria and works toward more consistent results across clinicians. The work focuses on deep-learning methods that can be integrated into clinical practice to support timely diagnosis and treatment for women with PCOS.
Why it matters
Potential benefit: If successful, the tool could speed up accurate PCOS diagnosis and help patients receive appropriate care sooner.
How similar studies have gone: Prior work suggests AI can improve imaging-based diagnosis, but broader validation in PCOS is needed, making this approach promising but exploratory.
Where this research is happening
-
Cornell University
Ithaca, United States Active
Researchers
- Principal investigator: Lujan, Marla E — Cornell University
- Study coordinator: Lujan, Marla E
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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.