AI eye doctor: could software catch diabetic blindness sooner?
NCT ID NCT07758582
First seen Aug 11, 2026 · Last updated Aug 12, 2026 · Updated 1 time
Summary
This trial evaluates an artificial intelligence system designed to automatically detect signs of diabetic retinopathy in retinal photographs. Researchers will compare the AI's performance against experienced ophthalmologists using a large set of eye images from adults with the condition. The goal is to see if the AI can accurately identify the disease and its severity, potentially offering a faster, more accessible screening tool.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- Active substance
- Artificial intelligence software analyzing retinal photographs
- What this could lead to
- If successful, this AI could help doctors detect diabetic retinopathy earlier and more accurately, potentially preventing vision loss.
- What could go wrong
- The AI may not be as accurate as experienced eye doctors, and its performance could vary across different image qualities or patient groups.
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.
- Participants
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About 2,000 people
The number the study aims to enrol. It can still change while the study runs.
- Started
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May 2026
- Expected to finish
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Apr 2027
An estimate. End dates often move.
- Lead sponsor
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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.
Who is studied
Participants that are able to provide consent for their fundus photograph to be recorded
- Ages
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18 years and older
- Sex
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Anyone
- Healthy volunteers
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Accepted
You do not need to have the condition being studied to take part.
Show the full entry requirements Hide 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.
Inclusion Criteria Age ≥18 years Availability of a high-resolution color fundus photograph Confirmed diagnosis established by an ophthalmology specialist Exclusion Criteria Poor-quality retinal images Concomitant ocular diseases that interfere with image interpretation
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
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The places running it
1 site. The list below names each one and where it is.
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The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
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A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
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University Hospital of Alexandroupolis
RECRUITINGAlexandroupoli, Greece
More trials for these conditions
Other studies related to the condition(s) this trial covers.
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- Eye scans as a window to the body: study probes retinal imaging across diseases
- Can a new gel make eye injections less painful?
- Can eye scans reveal hidden clues about diabetes damage?
- AI could predict which eye treatments work best for Diabetes-Related vision loss
- New eye drug aims to restore vision in Diabetes-Related swelling