Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care

Abstract There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We developed an automated retinal photography and AI-based screening system and prospectively assessed its accuracy, feasibility, and acceptability in A...

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Main Authors: Catherine L. Jan, Sanil Joseph, Algis J. Vingrys, Jacqueline Henwood, Zongyuan Ge, Randall S. Stafford, Mingguang He
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-025-01768-y
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author Catherine L. Jan
Sanil Joseph
Algis J. Vingrys
Jacqueline Henwood
Zongyuan Ge
Randall S. Stafford
Mingguang He
author_facet Catherine L. Jan
Sanil Joseph
Algis J. Vingrys
Jacqueline Henwood
Zongyuan Ge
Randall S. Stafford
Mingguang He
author_sort Catherine L. Jan
collection DOAJ
description Abstract There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We developed an automated retinal photography and AI-based screening system and prospectively assessed its accuracy, feasibility, and acceptability in Australian general practice (GP) clinics. Adults aged 50 years or older were recruited during routine GP visits, with retinal images captured using an automated fundus camera and analysed by the AI system for glaucoma risk classification. Of 414 participants, 277 (66.9%) had analysable images, with a total of 483 eyes included. The AI system achieved an AUROC of 0.80, sensitivity of 65.0%, and specificity of 94.6%. Among 161 previously undiagnosed patients, 18 (11.2%) were identified as referable glaucoma. Patient feedback was positive, and clinic staff supported AI-assisted screening to enhance glaucoma care. Despite challenges such as lower sensitivity and image acquisition limitations, the system shows promise for opportunistic screening in primary care settings.
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institution Kabale University
issn 2398-6352
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series npj Digital Medicine
spelling doaj-art-01415a8fb563414ab0fb17efe0d2debe2025-08-20T04:01:36ZengNature Portfolionpj Digital Medicine2398-63522025-07-01811810.1038/s41746-025-01768-yProspective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary careCatherine L. Jan0Sanil Joseph1Algis J. Vingrys2Jacqueline Henwood3Zongyuan Ge4Randall S. Stafford5Mingguang He6Centre for Eye Research Australia, Royal Victorian Eye and Ear HospitalCentre for Eye Research Australia, Royal Victorian Eye and Ear HospitalDepartment of Optometry and Vision Sciences, The University of MelbourneCentre for Eye Research Australia, Royal Victorian Eye and Ear HospitalThe AIM for Health Lab, Faculty of IT, Monash UniversityStanford Prevention Research Center, Stanford University School of MedicineCentre for Eye Research Australia, Royal Victorian Eye and Ear HospitalAbstract There are no prospective clinical studies evaluating artificial intelligence implementation for glaucoma detection in real-world settings. We developed an automated retinal photography and AI-based screening system and prospectively assessed its accuracy, feasibility, and acceptability in Australian general practice (GP) clinics. Adults aged 50 years or older were recruited during routine GP visits, with retinal images captured using an automated fundus camera and analysed by the AI system for glaucoma risk classification. Of 414 participants, 277 (66.9%) had analysable images, with a total of 483 eyes included. The AI system achieved an AUROC of 0.80, sensitivity of 65.0%, and specificity of 94.6%. Among 161 previously undiagnosed patients, 18 (11.2%) were identified as referable glaucoma. Patient feedback was positive, and clinic staff supported AI-assisted screening to enhance glaucoma care. Despite challenges such as lower sensitivity and image acquisition limitations, the system shows promise for opportunistic screening in primary care settings.https://doi.org/10.1038/s41746-025-01768-y
spellingShingle Catherine L. Jan
Sanil Joseph
Algis J. Vingrys
Jacqueline Henwood
Zongyuan Ge
Randall S. Stafford
Mingguang He
Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
npj Digital Medicine
title Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
title_full Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
title_fullStr Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
title_full_unstemmed Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
title_short Prospective pragmatic trial of automated retinal photography and AI glaucoma screening in Australian primary care
title_sort prospective pragmatic trial of automated retinal photography and ai glaucoma screening in australian primary care
url https://doi.org/10.1038/s41746-025-01768-y
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