Work

A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation

Year: 2026

Type: review

Abstract: Glaucoma is the leading cause of irreversible blindness worldwide with heterogeneous progression rates. Artificial Intelligence (AI) may enable accurate progression predictions in clinical practice. We conducted a systematic review to survey quantitative AI performance and examine strengths and shortfalls in current AI approaches with future clinical implementation in mind. Two reviewers independently screened studies in English from MEDLINE, Embase, Web of Science, Cochrane CENTRAL and arXiv since 2014 and performed risk of bias assessment on eligible studies using QUADAS-2. 46 reports of 43 unique studies demonstrated moderate to good performance in predicting glaucoma conversion, biological deterioration and progression to surgery. Several challenges for clinical translation remain, including inconsistent reporting, limitations and heterogeneity in study design and poor AI generalisability and transparency. We encourage future studies to adopt robust study design and transparent reporting and propose the first glaucoma-specific list of recommended practices and reporting items for future clinical implementation.

Source: npj Digital Medicine

DOI: 10.1038/s41746-025-02321-7

Authors: Yichuan G. Liang, Leo Fan, Armando Teixeira-Pinto, Gerald Liew, Andrew J. R. White

Institutions: The University of Sydney, Westmead Institute for Medical Research, Westmead Hospital, Western Sydney Local Health District, Children's Hospital at Westmead

Language: English

Topic: Glaucoma and retinal disorders

Subfield: Ophthalmology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,090