Glaucomatous visual field progression has both personal and societal costs and therefore
has a serious impact on quality of life. At the present time, intraocular pressure (IOP) is …

Clinicians who manage glaucoma patients carefully monitor the visual field to determine if
treatments are effective or interventions are needed. Visual field tests may reflect disease …

OBJECTIVE: To evaluate the performance of progression detection and the rate of change of
retinal nerve fiber layer (RNFL), neuroretinal rim, and visual field measurements in …

Purpose To identify visual field (VF) worsening from longitudinal OCT data using a gated
transformer network (GTN) and to examine how GTN performance varies for different …

Although deep learning architecture has been used to process sequential data, only a few
studies have explored the usefulness of deep learning algorithms to detect glaucoma …

Purpose: To compare global trend-based and point-wise event-based analysis for detecting
visual field progression in eyes with glaucoma. Methods: The study included a cohort of 367 …

Detecting glaucoma progression remains one of the most challenging aspects of glaucoma
management, since it can be hard to distinguish disease progression from exam variability …

Purpose: To develop an artificial neural network model incorporating both spatial and
ordinal approaches to predict glaucomatous visual field (VF) progression. Design: Cohort …

PURPOSE: To compare the results of Glaucoma Progression Analysis (GPA, Carl Zeiss
Meditec, Dublin, CA) to subjective expert consensus in the detection of glaucomatous visual …

Purpose: To investigate the suitability of the visual field index (VFI) in different degrees of
disease severity in glaucoma patients. Methods: In this cross-sectional study, we …