With the emergence of unmanned plane, autonomous vehicles, face recognition, and
language processing, the artificial intelligence (AI) has remarkably revolutionized our …

Artificial intelligence is a multidisciplinary and collaborative science, the ability of deep
learning for image feature extraction and processing gives it a unique advantage in dealing …

Purpose: Existing summary statistics based upon optical coherence tomographic (OCT)
scans and/or visual fields (VFs) are suboptimal for distinguishing between healthy and …

Purpose To differentiate the visual fields (VFs) of preperimetric open-angle glaucoma (OAG)
patients from the VFs of healthy eyes using a deep learning (DL) method. Design Cohort …

Artificial intelligence has the potential to revolutionize the screening, diagnosis, and
classification of glaucoma, both through the automated processing of large data sets, and by …

White‐on‐white standard automated perimetry (SAP) is widely used in clinical and research
settings for assessment of contrast sensitivity using incremental light stimuli across the visual …

Purpose To test the hypothesis that visual field (VF) progression can be predicted from
baseline and longitudinal optical coherence tomography (OCT) structural measurements …

This review presents and discusses the contribution of machine learning techniques for
diagnosis and disease monitoring in the context of clinical vision science. Many ocular …

A specific, sensitive, and intersubjectively verifiable definition of disease for clinical care and
research remains an important unmet need in the field of glaucoma. Using an iterative …

We hypothesize that artificial intelligence (AI) applied to relevant clinical testing in glaucoma
has the potential to enhance the ability to detect glaucoma. This premise was discussed at …