AI tool to predict glaucoma progression and need for surgery
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical Intervention
This project uses artificial intelligence on eye scans and medical records to help identify people with glaucoma who may worsen or need surgery.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project ID | NIH-11180146 on NIH RePORTER |
What this research studies
Researchers will combine past clinical records, OCT optic nerve images, visual field tests, eye pressure, and corneal thickness to train deep learning models that predict fast vision loss and the future need for glaucoma surgery. The work uses data from long-running glaucoma cohorts (DIGS and ADAGES), including many participants of African descent, as well as patients managed at UCSD. The models merge multiple types of information so predictions are personalized rather than based on a single test. If my data are included, it could help the algorithm learn patterns that signal higher risk for vision loss or surgical intervention.
Who could benefit from this research
Good fit: Adults diagnosed with glaucoma who have OCT imaging, visual field tests, and electronic health records—especially those enrolled in DIGS/ADAGES or receiving care at UCSD—are the ideal candidates for this work.
Not a fit: Patients without recent imaging or visual field data, with rare atypical eye conditions, or unwilling to share medical records may not directly benefit from this specific project.
Why it matters
Potential benefit: If successful, this could help clinicians spot high-risk patients earlier and guide timelier monitoring or surgery to protect vision.
How similar studies have performed: Previous AI studies have shown promise using images or tests to detect glaucoma damage, but combining multiple data types to forecast rapid progression and surgical need is relatively new.
Where this research is happening
La Jolla, United States
- University of California, San Diego — La Jolla, United States (Active)
Researchers
- Principal investigator: Zangwill, Linda M — University of California, San Diego
- Study coordinator: Zangwill, Linda M
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.