Hemelings Ruben

Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning.

These results demonstrate the benefits of deep learning for automated glaucoma detection based on optic disc-centred fundus images.

Pointwise Visual Field Estimation From Optical Coherence Tomography in Glaucoma Using Deep Learning.

Deep learning can estimate global and pointwise VF sensitivities that fall almost entirely within the 90% test-retest confidence intervals of the 24-2 SS test.

A prototype protocol for evaluating the real-world data set using a structured electronic health record in glaucoma.

The developed structured data presentation enables comparisons between different population-based real-world glaucoma data sets and glaucoma clinics.