Using AI on eye scans and genes to predict glaucoma risk
Predicting the risk of glaucoma from structural, functional, and genetic factors using artificial intelligence
This project uses artificial intelligence on eye scans, vision tests, and genetic information to find people most likely to develop or have worsening glaucoma.
Quick facts
| Grant type | R01 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 ID | NIH-11469603 on NIH RePORTER |
What this research studies
You may be asked to share eye imaging (like OCT and fundus photos), visual field test results, and a saliva or blood sample for genetic testing. Researchers will train AI algorithms to find patterns across these different types of data that signal higher risk of glaucoma onset or progression. They will test the models using existing clinical records and new participant data to check accuracy and consistency. The goal is a tool clinics can use to prioritize patients who need closer monitoring or earlier treatment to protect vision.
Who could benefit from this research
Good fit: Ideal candidates include adults with suspicious optic nerve appearance, early glaucoma, a family history of glaucoma, or older adults at higher risk for the disease.
Not a fit: People without available eye imaging or genetic information, or those whose vision loss is caused by other eye conditions, may not receive direct benefit from this work.
Why it matters
Potential benefit: If successful, this could help clinicians identify high-risk patients earlier so treatment or closer follow-up can prevent vision loss.
How similar studies have performed: Previous studies using AI on eye images have shown promise for detecting glaucoma, but combining imaging, visual field testing, and genetics is a relatively new approach.
Where this research is happening
Coral Gables, United States
- 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
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 below.