Shibata Naoto

Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

The previously developed deep residual learning algorithm achieved high diagnostic performance with different fundus cameras across multiple institutes, in particular when image augmentation was used.

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms.

Deep learning glaucoma detection can achieve high accuracy across diverse datasets with appropriate training strategies.