Predicting progressive vision loss in glaucoma patients using functional principal component analysis and electronic health records
A novel modeling approach combining FPCA with clinical data from EHR was able to model longitudinal clinical trajectories of glaucoma patients. This method is well-suited for modeling longitudinal healthcare data, handling sparse and irregular observation schedules with a varying number of inputs.
Authors
- Sophia Ying Wang (ORCID: https://orcid.org/0000-0003-0916-9403)
- Cody Carroll (ORCID: https://orcid.org/0000-0003-3525-8653)
- Maxim Sivolella
- Rithvik Krishna Donnipadu
Institutions
- Smith-Kettlewell Eye Research Institute (US)
- University of San Francisco (US)
Publication Details
- Journal
- Frontiers in Ophthalmology
- Published
- 2025-11-19
- DOI
- https://doi.org/10.3389/fopht.2025.1632827
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Research to Prevent Blindness
- American Glaucoma Society