AI tool to standardize how uveitis is measured
Official title: A generalizable deep learning platform for unifying quantification of experimental autoimmune uveitis
Funded at University of Miami School of Medicine · NIH-11469605 · Data updated 2026-11-12
This project builds an AI platform to consistently measure signs of posterior uveitis in lab models so researchers can compare and improve treatments for people with uveitis.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Miami School of Medicine NIH-funded |
| Lab location | 1 site (Coral Gables, United States) |
| Project start | February 1, 2025 |
| Project end | January 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $191,875 |
| NIH project number | 7R21EY036199-02 |
| Project ID | NIH-11469605 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with posterior uveitis or related inflammatory eye conditions are the group most likely to benefit from improvements in how preclinical models are measured.
✕Less likely to help
Patients needing immediate new therapies or those with non-inflammatory eye conditions are unlikely to see direct benefits in the short term since this work focuses on animal-model measurement tools.
What this research studies
Researchers will train deep learning models on images and data from experimental autoimmune uveitis (EAU), an animal model that mirrors key features of human posterior uveitis. They will use modern self-supervised learning and vision transformer techniques to teach the AI to recognize and quantify disease features. The platform is being designed to work across labs and reduce the variability that now occurs when different people score disease by eye. By standardizing measurements, the team hopes to make preclinical testing of new therapies more reliable and comparable.
Why it matters
Potential benefit: If successful, this could make preclinical testing more consistent and help speed development of better treatments for posterior uveitis.
How similar studies have gone: AI has shown success diagnosing clinical eye diseases, but applying self-supervised vision-transformer models to animal uveitis models is relatively new.
Where this research is happening
-
University of Miami School of Medicine
Coral Gables, United States Active
Researchers
- Principal investigator: Yousefi, Siamak — University of Miami School of Medicine
- Study coordinator: Yousefi, Siamak
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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.