Clinically aligned artificial intelligence for glaucoma diagnosis: enhancing retinal nerve fibre layer…

AI / informaticsEye (London, England)· Jul 2026

Clinically aligned artificial intelligence for glaucoma diagnosis: enhancing retinal nerve fibre layer interpretation from fundus images.

Shang-Lin Chung, Jehn-Yu Huang, Yi-Ching Shao … Chia-En Lien

RetinaAI / informaticsDiagnosisQ1IF 3.3

Artificial intelligence system correctly flags most fundus photos needing glaucoma specialist referral

Clinically aligned artificial intelligence for glaucoma diagnosis: enhancing retinal nerve fibre layer interpretation from fundus images.

Shang-Lin Chung … Chia-En Lien

Eye (London, England) · Jul 2026 · Q1 in Ophthalmology

Purpose

This study aimed to develop an interpretable artificial intelligence (artificial intelligence) screening system that replicates a specialist's evaluation of fundus photographs.

Methods

A total of 773 fundus images from the independent test cohort were annotated by three fellowship-trained glaucoma specialists, followed by repeated consensus meetings to improve annotation consistency.

n = 773 fundus images

Results

correctly identifies about 9 in 10 patients who truly needed specialist referral

Sensitivity 0.90 (95% CI 0.87 to 0.94)

null 0

0.87

0.94

CI excludes the null - significant

More results

The final independent test cohort comprised 268 referral and 481 non-referral cases, providing a basis for evaluation.

The system captured complementary aspects of glaucomatous optic neuropathy that are often missed by single-feature approaches.

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Conclusion · 1 of 2

Consensus-based annotation, combined with lesion-level modelling, enhances alignment with clinical reasoning.

Conclusion · 2 of 2

By providing an explicit referral rationale, the system fosters trust in artificial intelligence-assisted glaucoma screening and facilitates adoption in clinical settings.

Clinically aligned artificial intelligence for glaucoma diagnosis: enhancing retinal nerve fibre layer interpretation from fundus images.

Clinically aligned artificial intelligence for glaucoma diagnosis: enhancing retinal nerve fibre layer interpretation from fundus images.

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