Use of Artificial Intelligence in Forecasting Glaucoma Progression

Overview

Journal Taiwan J Ophthalmol

Specialty Ophthalmology

Date 2023 Jul 24

PMID 37484617

Authors

Sahil Thakur

Linh Le Dinh

Raghavan Lavanya

Ten Cheer Quek

Yong Liu

Ching-Yu Cheng

Affiliations

Soon will be listed here.

Abstract

Artificial intelligence (AI) has been widely used in ophthalmology for disease detection and monitoring progression. For glaucoma research, AI has been used to understand progression patterns and forecast disease trajectory based on analysis of clinical and imaging data. Techniques such as machine learning, natural language processing, and deep learning have been employed for this purpose. The results from studies using AI for forecasting glaucoma progression however vary considerably due to dataset constraints, lack of a standard progression definition and differences in methodology and approach. While glaucoma detection and screening have been the focus of most research that has been published in the last few years, in this narrative review we focus on studies that specifically address glaucoma progression. We also summarize the current evidence, highlight studies that have translational potential, and provide suggestions on how future research that addresses glaucoma progression can be improved.

Citing Articles

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