Improving fairness in glaucoma risk estimation using artificial intelligence
Official title: Achieving Model Fairness on Automatic Primary Open-angle Glaucoma Screening
Funded at Weill Medical Coll of Cornell Univ · NIH-10726928 · Data updated 2026-11-12
This study is working on a new AI tool to help better predict the risk of glaucoma, especially for people in diverse communities like African and Hispanic Americans, so that everyone can get fairer and more accurate eye care.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Weill Medical Coll of Cornell Univ NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 30, 2023 |
| Project end | August 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $466,125 |
| NIH project number | 1R21EY035296-01 |
| Project ID | NIH-10726928 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals at risk for primary open-angle glaucoma, particularly those from African and Hispanic American backgrounds.
✕Less likely to help
Patients who do not have risk factors for primary open-angle glaucoma may not receive direct benefits from this research.
What this research studies
This research focuses on developing a new artificial intelligence model to better estimate the risk of primary open-angle glaucoma (POAG), particularly in diverse populations such as African and Hispanic Americans. The project aims to address potential biases in existing predictive models that may lead to unequal healthcare outcomes. By utilizing innovative methodologies, the researchers will validate their approach without relying on demographically balanced datasets, ensuring a more equitable assessment of glaucoma risk. Patients may benefit from improved screening processes that are fairer and more accurate.
Why it matters
Potential benefit: If successful, this research could lead to more accurate glaucoma risk assessments, ultimately preventing vision loss in at-risk populations.
How similar studies have gone: Other research has shown promise in using artificial intelligence to address biases in healthcare, making this approach both relevant and potentially impactful.
Where this research is happening
-
Weill Medical Coll of Cornell Univ
New York, United States Active
Researchers
- Principal investigator: Peng, Yifan — Weill Medical Coll of Cornell Univ
- Study coordinator: Peng, Yifan
Related research
Other NIH-funded projects on the same topics.
-
Improving glaucoma risk predictions using diverse genetic data
A glaucoma study uses genetic data from people of African, American, and European ancestry to build better risk scores and help with early detection.
-
Multimodal AI to predict glaucoma progression and guide care
A big-data AI tool uses eye images, scans, field tests, and health info to help predict who with open-angle glaucoma is at higher risk of vision loss so doctors can act sooner.
-
Replacing damaged eye drainage cells to treat glaucoma
This project is developing a cell-based treatment to replace lost drainage cells and help people with primary open-angle glaucoma keep eye pressure lower and protect vision.
-
Improving risk prediction for glaucoma in diverse populations
This study is looking to improve how we predict the risk of primary open-angle glaucoma in people of African ancestry, so that they can get better early diagnosis and treatment options based on their unique genetic background.
-
Using cell therapy to treat primary open angle glaucoma
This study is testing a new cell therapy to help people with primary open angle glaucoma by using special stem cells to improve eye function and lower pressure, which could help prevent vision loss when regular treatments aren't enough.
-
Better genetic risk prediction for open-angle glaucoma
This project will build more accurate genetic risk tools for people at risk of open-angle glaucoma by including more diverse ancestry groups in the analysis.
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.