Novel Artificial Intelligence–Based Quantification of Anterior Chamber Inflammation Using Vision Transformers
Our artificial intelligence algorithm objectively quantifies AC inflammation reliably over the time and could be used in the clinic as well as in clinical trials as an objective biomarker.
Authors
- William Rojas‐Carabali (ORCID: https://orcid.org/0000-0002-9976-8989)
- Nicholas Chieh Loh (ORCID: https://orcid.org/0000-0002-3177-176X)
- Atharva Hudlikar (ORCID: https://orcid.org/0000-0003-0151-2254)
- Bernett Teck Kwong Lee (ORCID: https://orcid.org/0000-0002-2709-1972)
- Carlos Cifuentes‐González (ORCID: https://orcid.org/0000-0002-2703-0977)
- Hnin Hnin Oo (ORCID: https://orcid.org/0000-0003-2440-5128)
- Xin Wei (ORCID: https://orcid.org/0000-0001-8865-1956)
- Rupesh Agrawal (ORCID: https://orcid.org/0000-0002-6662-5850)
- Alejandra de‐la‐Torre (ORCID: https://orcid.org/0000-0003-0684-1989)
- Joewee Boon
- Laura Gutiérrez-Sinisterra
- Choo Sheriel Shannon (ORCID: https://orcid.org/0009-0005-1820-0654)
- Laura Daniela Rodríguez-Camelo (ORCID: https://orcid.org/0009-0006-4646-6991)
- Leonid Shchurov
Institutions
- University of Technology Sydney (AU)
- National University of Singapore (SG)
- Nanyang Technological University (SG)
- Tan Tock Seng Hospital (SG)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- Universidad del Rosario (CO)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1167/tvst.14.5.31
- Citations
- 2
- Primary Topic
- Ocular Diseases and Behçet’s Syndrome
- Type
- article
- Field-Weighted Citation Impact
- 3.41
Funders
- Medical Research Council
- National Medical Research Council