Improving fairness in AI algorithms for glaucoma treatment
Official title: Improving Fairness and Reducing Bias in Artificial Intelligence Algorithms for Glaucoma
Funded at Stanford University · NIH-11030044 · Data updated 2026-11-12
This study is working on smart computer programs that can help doctors predict which glaucoma patients might be at risk of losing their vision, especially focusing on making sure everyone gets fair treatment, no matter their background.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $654,455 |
| NIH project number | 1R01EY036893-01 |
| Project ID | NIH-11030044 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include glaucoma patients, particularly those from Black and Hispanic communities who are at higher risk for disease progression.
✕Less likely to help
Patients with early-stage glaucoma or those who do not belong to marginalized communities may not receive direct benefits from this research.
What this research studies
This research focuses on developing personalized prediction algorithms to better understand and manage glaucoma, a leading cause of irreversible blindness. By utilizing artificial intelligence techniques on electronic health records, the study aims to create high-performance predictive models that can identify patients at high risk for vision loss. A key aspect of this research is addressing algorithmic bias, particularly how it affects marginalized groups, to ensure equitable healthcare outcomes. The project will leverage data from the multicenter Sight Outcomes Research Collaborative to evaluate the fairness and effectiveness of these AI algorithms.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions and personalized treatment plans for glaucoma patients, ultimately reducing the risk of vision loss.
How similar studies have gone: Previous research has shown success in using AI for predictive modeling in healthcare, but addressing algorithmic bias in this context is a relatively novel approach.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Wang, Sophia Ying — Stanford University
- Study coordinator: Wang, Sophia Ying
Related research
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Using AI on eye scans and genes to predict glaucoma risk
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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.