Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma.

ABSTRACT:

Purpose

To quantify the central visual field (VF) loss patterns in glaucoma using artificial intelligence.

Design

Retrospective study.

Participants

VFs of 8712 patients with 13 951 Humphrey 10-2 test results from 13 951 eyes for cross-sectional analyses, and 824 patients with at least 5 reliable 10-2 test results at 6-month intervals or more from 1191 eyes for longitudinal analyses.

Methods

Total deviation values were used to determine the central VF patterns using the most recent 10-2 test results. A 24-2 VF within a 3-month window of the 10-2 tests was used to stage eyes into mild, moderate, or severe functional loss using the Hodapp-Anderson-Parrish scale at baseline. Archetypal analysis was applied to determine the central VF patterns. Cross-validation was

SUBMITTER: Wang M 

PROVIDER: S-EPMC7246163 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature