AI to predict glaucoma progression and need for surgery

Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical Intervention

['FUNDING_R01'] · UNIVERSITY OF CALIFORNIA, SAN DIEGO · NIH-11415376

Using AI that looks at eye scans and medical records to predict which people with glaucoma may lose vision faster or need glaucoma surgery.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF CALIFORNIA, SAN DIEGO (nih funded)
Locations1 site (LA JOLLA, UNITED STATES)
Trial IDNIH-11415376 on ClinicalTrials.gov

What this research studies

This project combines eye imaging (optic nerve OCT), visual field tests, eye pressure and corneal thickness with electronic health record information to train deep-learning models. The researchers will use long-running glaucoma cohorts (DIGS and ADAGES) and clinical data from UCSD to build and test the models. One aim is to predict who is likely to need glaucoma surgery; the other aim is to predict who will have fast visual field loss. The goal is to make predictions from a patient's baseline data to help guide follow-up and treatment decisions.

Who could benefit from this research

Good fit: People with a diagnosis of glaucoma who have standard eye tests such as OCT imaging, visual field measurements, intraocular pressure records, and basic clinical records would be the ideal candidates for this work.

Not a fit: Patients without recent or reliable eye imaging, visual field tests, or clinical records are unlikely to benefit from the model's predictions.

Why it matters

Potential benefit: If successful, the tool could help doctors spot high-risk patients earlier so treatment or closer follow-up can be tailored to reduce vision loss.

How similar studies have performed: Earlier AI research has shown promise for detecting glaucoma and estimating progression risk, but using multimodal AI to predict surgical need is a newer approach and less established.

Where this research is happening

LA JOLLA, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.