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Clinical Efficacy of Implementing an AI-SaMD for Funduscopy Analysis in Patients With Diabetes Mellitus

NCT07378956 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 340

Last updated 2026-04-13

No results posted yet for this study

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.

Conditions

  • Diabetic Retinopathy (DR)
  • Diabete Mellitus
  • Fundus Photography

Interventions

DEVICE

VUNO Med®-Fundus AI™

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.

Sponsors & Collaborators

  • VUNO Inc.

    lead INDUSTRY

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
19 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-04-07
Primary Completion
2027-08-31
Completion
2027-08-31

Countries

  • South Korea

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07378956 on ClinicalTrials.gov