Synergistic AI-resident approach achieves superior diagnostic accuracy in tertiary ophthalmic care for glaucoma and retinal disease
AI outperformed first-year residents in key ophthalmic assessments. The synergistic use of AI and resident assessments showed potential for optimizing diagnostic accuracy, highlighting the value of AI as a supportive tool in ophthalmic practice, especially for early career clinicians.
Authors
- Damaris Hodelin-Fuentes (ORCID: https://orcid.org/0000-0003-2539-685X)
- Karen Janeth Arriozola-Rodríguez (ORCID: https://orcid.org/0000-0002-0440-5211)
- Dalia Camacho‐García‐Formentí (ORCID: https://orcid.org/0000-0001-7493-7507)
- Alejandro Noriega (ORCID: https://orcid.org/0000-0003-0106-392X)
- Hugo Valdez-Flores (ORCID: https://orcid.org/0000-0003-2093-9771)
- Curt Hartleben-Matkin (ORCID: https://orcid.org/0000-0002-3134-5162)
- Enrique Avalos-Ramirez
- Gabriela Baylón-Vázquez (ORCID: https://orcid.org/0000-0002-4027-4087)
Institutions
- Universidad Nuestra Señora de La Paz (BO)
- Ocular Proteomics (United States) (US)
- Hospital Oncológico Docente "Conrado Benítez García" (CU)
- Epidemic Intelligence Service (US)
Publication Details
- Journal
- Frontiers in Ophthalmology
- Published
- 2025-05-19
- DOI
- https://doi.org/10.3389/fopht.2025.1581212
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.36