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AI assistant boosts eye doctor accuracy in retinal disease diagnosis?

NCT ID NCT07318428

Diagnosis Sponsor: Inje University Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

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.

Study facts

What this study's own registry entry says, in plain language.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

10 people

The number who actually took part.

Started

Feb 2026

Finished

May 2026

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Ten readers will be recruited from five participating hospital sites, consisting of: * Five ophthalmologists within three years of board certification * Five ophthalmology residents Ophthalmologists and residents of any age, sex, race, or ethnicity may participate as study readers. All readers must meet the following inclusion criteria: * Licensed physicians qualified to interpret fundus images. * Ophthalmologists within three years of board certification, or ophthalmology residents with no restriction on clinical experience. * Able and willing to complete both the unassisted and AI-assisted reading sessions. * Able to provide informed consent for participation in the reader study. * Affiliated with one of the participating clinical sites.

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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.

Age-related macular degeneration Diabetic retinopathy Glaucoma Glaucoma, suspect Retinal vein occlusion

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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