Multimodal AI-based modeling of glaucoma progression: a 3PM-guided approach integrating structural, functional, and vascular patterns
The proposed innovation utilizes multimodal predictive disease modeling that supports accurate risk stratification, personalized glaucoma management and individualized protection against disease progression. Successful clinical application requires initial profiling, regular model recalibration, and adaptive treatment strategies - altogether leading to improved visual outcomes in stratified patients and leveraging resources used.
Authors
- Oxana Ye. Rodionova (ORCID: https://orcid.org/0000-0002-0146-8284)
- Olga Golubnitschaja (ORCID: https://orcid.org/0000-0001-5427-2018)
- Н. И. Курышева (ORCID: https://orcid.org/0000-0002-2265-6671)
- Alexey L. Pomerantsev (ORCID: https://orcid.org/0000-0001-7402-4011)
- С. И. Пономарева (ORCID: https://orcid.org/0000-0002-4608-0136)
Institutions
- University of Bonn (DE)
- University Hospital Bonn (DE)
- Semenov Institute of Chemical Physics (RU)
- Federal Medical-Biological Agency (RU)
Publication Details
- Journal
- The EPMA Journal
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1007/s13167-025-00429-0
- Citations
- 2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.72