Multimodal Artificial Intelligence Models Predicting Glaucoma Progression Using Electronic Health Records and Retinal Nerve Fiber Layer Scans
Prediction models that utilize the wealth of structured clinical and imaging data to predict glaucoma progression could form the basis of future clinical decision support tools to personalize glaucoma care.
Authors
- Sophia Ying Wang (ORCID: https://orcid.org/0000-0003-0916-9403)
- Robert T. Chang (ORCID: https://orcid.org/0000-0002-2950-7951)
- Isaac A. Bernstein (ORCID: https://orcid.org/0000-0003-2858-7483)
- Rohith Ravindranath (ORCID: https://orcid.org/0000-0003-3438-6047)
- Y Zhang (ORCID: https://orcid.org/0000-0001-7646-1581)
- Abigail Koornwinder
Institutions
- Smith-Kettlewell Eye Research Institute (US)
- Stanford University (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-03-28
- DOI
- https://doi.org/10.1167/tvst.14.3.27
- Citations
- 8
- Primary Topic
- Glaucoma and retinal disorders
- Type
- article
- Field-Weighted Citation Impact
- 13.66
Funders
- Research to Prevent Blindness
- American Glaucoma Society