Classification of Inherited Retinal Diseases Using Artificial Intelligence Models for Fundus Autofluorescence and Ultrawide Retinal Images.
AI trained on fundus images accurately identifies five inherited retinal diseases, potentially speeding diagnosis in eye care clinics.
This study adapted the RETFound foundation model and CNN architectures for classifying five inherited retinal diseases (Best disease, rod-cone dystrophy, Stargardt disease, choroideremia, and normal) from fundus autofluorescence and pseudocolour UWF images. ResNet18 achieved the best overall performance (F1 0.839), outperforming classical ML approaches, establishing a deployable framework for IRD triage in clinical eye care settings.
What the study was
- Study design
- retrospective_validation
- Category
- ai_ml_diagnostics_imaging
- Maturity
- Validated
- Journal
- J Ophthalmol
Why it surfaced
Rare hereditary diseases cause significant working-age blindness; AI-aided IRD classification using foundation models has direct clinical triage value; multimodal imaging approach adds robustness to the framework.
A plain-language summary of published research — not medical advice. Talk to a clinician about your own care.