Deep Learning Prediction of Retinal Nerve Fiber Layer Thickness as a Novel Risk Biomarker for Glaucoma in Ocular Hypertension

Highlight

• A deep learning (machine-to-machine) model can accurately predict retinal nerve fiber layer (RNFL) thickness from optic disc photographs in ocular hypertension patients.
• Lower baseline predicted RNFL thickness significantly correlates with higher risk of developing primary open-angle glaucoma (POAG).
• Longitudinal decline in predicted RNFL thickness strongly predicts conversion to POAG, enhancing glaucoma risk monitoring.
• Incorporation of predicted RNFL thickness complements established clinical risk factors to improve risk stratification in glaucoma management.

Study Background and Disease Burden