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

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

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 datab...

Full description

Saved in:
Bibliographic Details
Main Authors: Kei Sano, MD, PhD, Euido Nishijima, MD, PhD, Shunsuke Sumi, MD, PhD, Takahiko Noro, MD, PhD, Shumpei Ogawa, MD, PhD, Yuka Igari, MD, Aiko Iwase, MD, PhD, Tadashi Nakano, MD, PhD
Format: Article
Language:English
Published: Elsevier 2025-11-01
Series:Ophthalmology Science
Subjects:
Glaucoma
Visual field
Perimetry
Screening
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914525001034
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items