Deep Learning-Based Prediction of Glaucoma Severity and Progression Using Imo/TEMPO Screening Program.

ABSTRACT:

Purpose

To develop DeepISP, a deep learning model that predicts the comprehensive visual field (VF) information of the Humphrey visual field analyzer (HFA) based on rapid screening perimetry (Imo/TEMPO screening program [ISP]).

Design

A retrospective, cross-sectional, and longitudinal cohort database study.

Participants

One hundred eighty-seven actual ISPs from 112 patients who underwent both ISP and HFA 24-2 on the same day at the Jikei University School of Medicine Affiliated Hospital and 3470 synthesized ISPs from 883 patients who underwent VF measurements using HFA 24-2 and HFA 10-2 at 4 hospitals affiliated with Jikei University School of Medicine.

Methods

We developed 2 variants of multitask neural networks designed to predict both current VF parameters a

SUBMITTER: Sano K 

PROVIDER: S-EPMC12281144 | biostudies-literature | 2025 Nov-Dec

REPOSITORIES: biostudies-literature