Vision-based screening for diabetic retinopathy
Open question: can a smartphone camera + an on-device vision model flag early DR? Survey of published approaches, accuracy claims, and what remains a referral path to an ophthalmologist.
Diabetic retinopathy is the leading cause of preventable blindness in working-age adults. Early detection saves vision.
The current screening gap
Specialist eye exams reach a fraction of Indian diabetics. A scalable screen at the point-of-care (or at home, on a smartphone) could change outcomes.
Vision-AI approaches
Published systems use convolutional networks trained on fundus images to classify referable retinopathy. Reported sensitivity is high in controlled datasets. Real-world deployment faces image quality variance, lens reflections, and equipment access.
Where DiaCare may help (no guarantee)
Smartphone-attachment ophthalmoscopes are becoming cheaper. A future DiaCare integration could guide users through capture and surface "see a specialist within X weeks" recommendations. This is exploratory.