Using artificial intelligence to improve glaucoma screening
Official title: Validation and Implementation of an Artificial Intelligence Machine-to-Machine (M2M) Model for Glaucoma Screening
Funded at University of Miami School of Medicine · NIH-10973054 · Data updated 2026-11-12
This study is working on a new AI tool that helps doctors check for glaucoma using regular eye photos, making it easier and cheaper for people to get tested, especially those who might have trouble accessing traditional eye exams.
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 start | September 30, 2024 |
| Project end | July 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $628,531 |
| NIH project number | 1R01EY036593-01 |
| Project ID | NIH-10973054 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals at risk for glaucoma, particularly those who may have limited access to traditional diagnostic methods.
✕Less likely to help
Patients who have already been diagnosed with advanced glaucoma or those who do not have access to fundus photography may not benefit from this research.
What this research studies
This research focuses on developing an innovative artificial intelligence model to enhance the screening process for glaucoma, a leading cause of blindness. By utilizing deep learning algorithms, the study aims to analyze fundus photographs to provide accurate and objective assessments of glaucomatous damage, which are typically measured using more complex and expensive imaging technologies. The goal is to create a cost-effective and accessible screening method that can be implemented in various healthcare settings, particularly benefiting those who face barriers to traditional diagnostic services.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate detection of glaucoma, potentially preventing blindness in at-risk populations.
How similar studies have gone: Other research has shown promise in using artificial intelligence for medical imaging, indicating that this approach could be effective in improving glaucoma screening.
Where this research is happening
-
University of Miami School of Medicine
Coral Gables, United States Active
Researchers
- Principal investigator: Medeiros, Felipe — University of Miami School of Medicine
- Study coordinator: Medeiros, Felipe
Related research
Other NIH-funded projects on the same topics.
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Automated topographic test for glaucoma detection and progression
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Using AI on eye scans and genes to predict glaucoma risk
This project uses artificial intelligence on eye scans, vision tests, and genetic information to find people most likely to develop or have worsening glaucoma.
-
AI-based glaucoma screening in community health centers
A new, easy-to-use AI screening approach will be tested in federally funded health centers to help identify people at risk for glaucoma, especially in communities with higher risk.
-
Understanding how glaucoma genes control eye cell function
A long-term research project will study how genetic factors affect eye cells in adults with glaucoma to uncover new ideas for protecting vision.
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.