AI-assisted retinal photo screening for adults with diabetes
Official title: Clinical Efficacy of Implementing an AI-Driven Software as a Medical Device (SaMD) for Funduscopy Analysis in Patients With Diabetes Mellitus: A Randomized Controlled Trial Protocol
Run by VUNO Inc. · NCT07378956 · Data updated 2026-11-12
This will test whether adding the VUNO Med®-Fundus AI tool to routine retinal photo screening helps adults with type 2 diabetes get more accurate referrals for diabetic retinopathy.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 19 Years and up |
| Sex | All |
| Enrollment | 340 (estimated) |
| Sponsor | VUNO Inc. Industry-sponsored |
| Locations | 1 site (Incheon, Gyeonggi-do) |
| Status | Recruiting |
| Started | April 7, 2026 |
| Main results expected | August 31, 2027 |
| Study ends | August 31, 2027 |
| Registry record updated | April 13, 2026 |
| Trial ID | NCT07378956 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults (19 years or older) with documented type 2 diabetes who can provide written informed consent and do not already have diagnosed diabetic retinopathy.
✕Probably not a fit
People with a prior diagnosis of diabetic retinopathy, type 1 diabetes, recent ocular surgery, pregnancy, or those unable to undergo fundus photography are unlikely to benefit from this screening approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
The trial compares outcomes for adults with type 2 diabetes who receive fundus photography with VUNO Med®-Fundus AI assistance versus usual clinical care without AI. Participants are enrolled at Inha University Hospital and assigned to either an AI-assisted screening pathway or a control pathway, with the primary outcome being the true referral rate for diabetic retinopathy. Key exclusions include a prior diagnosis of diabetic retinopathy, ophthalmic surgery within six months, type 1 diabetes, and pregnancy. The intervention is an AI-SaMD that analyzes fundus photographs and flags images that may require ophthalmology referral.
Why it matters
Potential benefit: If effective, the AI could increase correct referrals and help detect sight-threatening diabetic retinopathy earlier in people with type 2 diabetes.
How similar studies have gone: Other AI systems for fundus photo screening have shown strong sensitivity and improved referral workflows in prior trials and regulatory approvals, although implementation results vary by clinical setting.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults aged 19 years or older. * A documented diagnosis of type 2 diabetes mellitus. * Ability to communicate adequately and provide written informed consent for participation in the study. Exclusion Criteria: * A prior diagnosis of diabetic retinopathy at the time of screening. * A history of ophthalmic surgery within 6 months prior to the screening date. * A diagnosis of type 1 diabetes mellitus. * Pregnancy at the time of screening. * Any condition that, in the opinion of the investigator, would make participation in the study infeasible or inappropriate.
Where it's running
-
Inha University Hospital
Incheon, Gyeonggi-do, South Korea Recruiting
Study contacts
- Study coordinator: Hee Jun Park
- Email: heejun.park@vuno.co
- Phone: 82-10-7101-2844
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.