A Deep Learning Model Detects Glaucoma Based on an OCT Report, but Where Should the Clinician Look to Identify Glaucomatous Damage?
The DLM can tag eyes with glaucomatous damage, and the prototypical patterns overlaid on the reports might aid the clinician in identifying and understanding this damage.
Authors
- Ari Leshno (ORCID: https://orcid.org/0000-0002-8717-1659)
- Kaveri A. Thakoor (ORCID: https://orcid.org/0000-0001-5589-8151)
- Sol La Bruna (ORCID: https://orcid.org/0000-0003-2421-6001)
- Emmanouil Tsamis (ORCID: https://orcid.org/0000-0001-7418-1033)
- Grace Mao
- D. C. Hood
- Wai Tak Lau
- Tayna Gebhardt
- Arin L. Stowman
Institutions
- University of Pittsburgh (US)
- Columbia University Irving Medical Center (US)
- Sheba Medical Center (IL)
- Columbia University (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-10-16
- DOI
- https://doi.org/10.1167/tvst.14.10.23
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.36