Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.

ABSTRACT:

Purpose

To develop an artificial intelligence (AI) dashboard for monitoring glaucomatous functional loss.

Design

Retrospective, cross-sectional, longitudinal cohort study.

Participants

Of 31 591 visual fields (VFs) on 8077 subjects, 13 231 VFs from the most recent visit of each patient were included to develop the AI dashboard. Longitudinal VFs from 287 eyes with glaucoma were used to validate the models.

Method

We entered VF data from the most recent visit of glaucomatous and nonglaucomatous patients into a "pipeline" that included principal component analysis (PCA), manifold learning, and unsupervised clustering to identify eyes with similar global, hemifield, and local patterns of VF loss. We visualized the results on a map, which we refer to as an "AI-enabl

SUBMITTER: Yousefi S 

PROVIDER: S-EPMC7483368 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature