A Hybrid Deep Learning–Based Approach for Visual Field Test Forecasting

A Hybrid Deep Learning–Based Approach for Visual Field Test Forecasting

Objective: Longitudinal assessment of visual field (VF) testing is essential in glaucoma management. Conventional VF forecasting methods require numerous prior tests, while deep learning techniques have shown promising results with fewer tests. This study introduces a hybrid deep learning framework...

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Bibliographic Details
Main Authors: Ashkan Abbasi, PhD, Sowjanya Gowrisankaran, PhD, Wei-Chun Lin, MD, PhD, Xubo Song, PhD, Bhavna Josephine Antony, PhD, Gadi Wollstein, MD, Joel S. Schuman, MD, Hiroshi Ishikawa, MD
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Ophthalmology Science
Subjects:
Pointwise visual field forecasting
Glaucoma progression prediction
Deep learning
Hybrid architecture
Spatial and temporal modeling
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914525001010
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http://www.sciencedirect.com/science/article/pii/S2666914525001010

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