Clinical Efficacy of Implementing an AI-SaMD for Funduscopy Analysis in Patients With Diabetes Mellitus
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
VUNO Inc.
340 participants
Apr 7, 2026
INTERVENTIONAL
Conditions
Summary
The objective of this study is to investigate the efficacy of implementing the AI-SaMD(VUNO Med®-Fundus AI™) alongside routine clinical practice for the detection of diabetic retinopathy.
Eligibility
Inclusion Criteria3
- 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 Criteria5
- 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.
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Interventions
VUNO Med®-Fundus AI™ is an artificial intelligence-based fundus image detection and diagnostic support software. The software automatically identifies abnormal retinal findings and provides information on the type and location of detected abnormalities to aid clinical decision-making.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07378956