Validation of the Eyerobo FC Portable Fundus Camera for Diabetic Retinopathy Screening Using Public Datasets and Deep Learning
The Eyerobo fundus camera demonstrates noninferior diagnostic performance (sensitivity 92.3%, specificity 94.2%, AUC 0.977) compared with desktop systems when evaluated with AI algorithms trained exclusively on desktop images. These findings support deploying portable AI-assisted screening in resource-constrained and point-of-care settings, with successful cross-domain transfer learning enabling algorithmic generalizability across imaging platforms.
Authors
- Mingxuan Zhang (ORCID: https://orcid.org/0009-0001-7302-5335)
- Muhammad Usama (ORCID: https://orcid.org/0000-0002-3834-2167)
- Shoukuan Liu (ORCID: https://orcid.org/0009-0004-9382-9500)
- Salissou Moutari
- Zhihui Zhang
- Emmanuel Eric Pazo
- Xiangying Liu
- Qinru Zhang
- Xinjun Ren
Institutions
- Queen's University Belfast (GB)
- Korea Advanced Institute of Science and Technology (KR)
- Tianjin Medical University Eye Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Ophthalmology and Therapy
- Published
- 2026-03-11
- DOI
- https://doi.org/10.1007/s40123-026-01353-w
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Tianjin Medical University
- Tianjin Medical University Eye Hospital