Artificial Intelligence-Based Uveitis Diagnosis Through Retinal Vasculature Analysis: A Paradigm Shift in Ocular Tuberculosis
AI-based quantification of retinal vasculature parameters, particularly vein tortuosity, can differentiate confirmed ocular TB from QFT-positive uveitis and ocular toxoplasmosis. This approach shows promise for more precise diagnostic and therapeutic accuracy in ocular TB.
Authors
- P. Martin van Hagen (ORCID: https://orcid.org/0000-0003-0854-2368)
- Rina La Distia Nora (ORCID: https://orcid.org/0000-0002-7026-5341)
- Saskia M. Rombach (ORCID: https://orcid.org/0000-0003-1356-7033)
- Willem A. Dik (ORCID: https://orcid.org/0000-0001-5235-3156)
- Ikhwanuliman Putera (ORCID: https://orcid.org/0000-0002-9350-5133)
- Jose D. Vargas Quiros
Institutions
- Chulalongkorn University (TH)
- Erasmus MC (NL)
- University of Indonesia (ID)
- Rumah Sakit Umum Pusat Nasional Dr. Cipto Mangunkusumo (ID)
- Erasmus University Rotterdam (NL)
Publication Details
- Journal
- Ophthalmology and Therapy
- Published
- 2025-02-24
- DOI
- https://doi.org/10.1007/s40123-025-01103-4
- Citations
- 3
- Primary Topic
- Ocular Diseases and Behçet’s Syndrome
- Type
- article
- Field-Weighted Citation Impact
- 5.12
Funders
- Lembaga Pengelola Dana Pendidikan