The simultaneous maturation of multiple digital and telecommunications technologies in
2020 has created an unprecedented opportunity for ophthalmology to adapt to new models …

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 …

Objective To assess whether machine learning algorithms (MLA) can predict eyes that will
undergo rapid glaucoma progression based on an initial visual field (VF) test. Design …

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Purpose Early-stage glaucoma diagnosis has been a challenging problem in
ophthalmology. The current state-of-the-art glaucoma diagnosis techniques do not …

Purpose To compare the ability of 10-2 visual field tests and central 12 locations of the 24-2
visual field test (C24-2) to detect central visual field progression in glaucoma eyes with early …

Visual field testing has played an essential role in the diagnosis and management of
glaucoma for more than a century. Methods to examine the visual field have been refined …

Purpose: We evaluated threshold saccadic vector optokinetic perimetry (SVOP) and
compared results to standard automated perimetry (SAP). Methods: A cross-sectional study …

Glaucoma poses a significant threat to public health worldwide, as it can result in irreversible
vision loss. Timely identification is vital for halting the progression of visual field …

Purpose To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous
functional loss. Design Retrospective, cross-sectional, longitudinal cohort study. Participants …