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DiabEye-Q: AI-driven longitudinal analysis of ophthalmoscopic images for early diabetes prediction in Qatari adults

Speaker
Dr. Zubair Shah
Event
International Conference on AI in Healthcare (AIiH 2025)
Date
8–10 September 2025
Place
Cambridge, United Kingdom
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Summary

Can a photograph of the back of the eye, taken years earlier, tell us who will develop type 2 diabetes? We analysed longitudinal retinal images and clinical records from 2,043 Qatar Biobank participants.

Fractal features from retinal images, fused with clinical data in an XGBoost and Vision Transformer pipeline, predicted future diabetes with 88% accuracy and 93% AUROC. Performance differed by age group, and the analysis pointed to higher susceptibility in men and older adults.

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