AI assistant boosts eye doctor accuracy in retinal disease diagnosis?

NCT ID NCT07318428

Completed Diagnosis Sponsor: Inje University Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tested whether an AI tool can help eye doctors diagnose four common retinal diseases (diabetic retinopathy, age-related macular degeneration, retinal vein occlusion, and glaucoma) more accurately and quickly. Ten doctors from five hospitals read fundus images both with and without AI assistance. The goal was to see if the AI improves diagnostic sensitivity, specificity, and reading time.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance: VUNO Med-Fundus AI (AI-based fundus image interpretation software)
What this could lead to: If successful, this could show that AI helps eye doctors diagnose common retinal diseases more accurately and quickly, potentially improving routine eye care.
What could go wrong: This is a small, early-stage study with only 10 readers, so results may not apply broadly. The AI only provides findings, not diagnoses, so its real-world benefit is still uncertain.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

age-related macular degeneration borderline glaucoma diabetic retinopathy glaucoma macular degeneration ocular hypertension retinal vein occlusion

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

Dong-A University Hospital

Busan, 49201, South Korea
Inje University Busan Paik Hospital

Busan, 47392, South Korea
Kosin University Gospel Hospital

Busan, 49267, South Korea
Pusan National University Hospital

Busan, 49241, South Korea
Pusan National University Yangsan Hospital

Yangsan, 50612, South Korea

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