A Pattern-Based OCT Metric for Glaucoma Detection
The new metric has the potential to improve the accuracy of referrals from primary care to specialist care via risk scores and calculators, as well as glaucoma definitions for clinical trials. The individual variables of this model may also aid clinical diagnosis.
Authors
- Mary K Durbin (ORCID: https://orcid.org/0000-0001-6789-940X)
- Donald C. Hood (ORCID: https://orcid.org/0000-0001-6717-4791)
- Chris Lee
- Sol La Bruna (ORCID: https://orcid.org/0000-0003-2421-6001)
- Emmanouil Tsamis (ORCID: https://orcid.org/0000-0001-7418-1033)
- Carlos Gustavo De Moraes (ORCID: https://orcid.org/0000-0002-5626-0894)
- Michael Chaglasian (ORCID: https://orcid.org/0000-0002-9319-2958)
- Yujia Wang (ORCID: https://orcid.org/0000-0002-5096-1147)
- Antonio Guzmán
- Tayna Gebhardt
- Arin L. Stowman
Institutions
- Columbia University Irving Medical Center (US)
- University of Pittsburgh Medical Center (US)
- Illinois College of Optometry (US)
- Columbia University (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1167/tvst.13.12.21
- Citations
- 4
- Primary Topic
- Glaucoma and retinal disorders
- Type
- article
- Field-Weighted Citation Impact
- 2.15
Funders
- Carl Zeiss Meditec AG
- Heidelberg Engineering
- National Institutes of Health
- Alcon Research Institute