Roland Scherer

Predicting Retinal Nerve Fiber Layer Thickness From Ocular Hypertension Treatment Study Optic Disc Photographs.

In this diagnostic study, baseline M2M-predicted RNFL thickness and longitudinal rate of change in predicted RNFL were putative risk factors for the development of glaucoma in patients with ocular hypertension.

Effect of Blood Pressure on Rates of Progression in Focal Ischemic vs. Generalized Cup Enlargement Glaucoma Phenotypes.

Lower systemic BP levels were associated with faster RNFL thinning in the FI optic disc phenotype but not in the GE phenotype.

Artificial Intelligence-Guided Endpoint Selection for Neuroprotection Trials in Glaucoma.

The artificial intelligence-based model identified the most vulnerable visual field locations from baseline data.

RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study.

The M2M model provided robust estimates of RNFL thickness from fundus photographs in a large population-based cohort.

Deep Learning-Predicted RNFL Loss and Incident Glaucoma in the Canadian Longitudinal Study on Aging.

Deep learning-predicted retinal nerve fiber layer loss from fundus photos correlates with meaningful structural change and predicts incident glaucoma. This offers a valuable tool for glaucoma risk stratification, particularly where OCT is unavailable.