Validation of the Artificial Intelligence Subsystem of the DDART Medical Device for the Automated Detection of Lesions Compatible With Diabetic Retinopathy in a Random Sample of Retinal Fundus Photographs

NCT07758582 | Recruiting

• 1 other identifier: 17745/01-04-2026
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

To validate the artificial intelligence subsystem of the DDART medical device for the automated detection of lesions compatible with diabetic retinopathy in a random sample of retinal fundus photographs. Secondary Objectives To determine the sensitivity and specificity of the artificial intelligence subsystem for the detection of diabetic retinopathy. To estimate the overall diagnostic accuracy and the area under the receiver operating characteristic (ROC) curve (AUC). To compare the performance of the algorithm with that of experienced ophthalmologists. To evaluate the ability of the model to distinguish between different stages of disease severity

Conditions

Diabetic Retinopathy

Outcome Measures

Primary Outcomes (1)

• Validation the artificial intelligence subsystem of the DDART medical device for the automated detection of lesions compatible with diabetic retinopathy in a random sample of retinal fundus photographs.

  1 year

Study Arms (1)

Participants from outpatient clinics

Diagnostic Test: Color retinal fundus photograph

Interventions

Color retinal fundus photograph DIAGNOSTIC_TEST

Diagnostic Test: color fundus photograph Description: Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.

Participants from outpatient clinics

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Participants that are able to provide consent for their fundus photograph to be recorded

Sponsors & Collaborators

• Democritus University of Thrace: lead

Study Sites (1)

University Hospital of Alexandroupolis

Alexandroupoli, Greece

RECRUITING

MeSH Terms

Conditions

Diabetic Retinopathy

Condition Hierarchy (Ancestors)

Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications; Diabetes Mellitus; Endocrine System Diseases

Central Study Contacts

Georgios Labiris

CONTACT

+302551030990; glampiri@med.duth.gr

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Democritus University of Thrace

Study Record Dates

• First Submitted: August 6, 2026
• First Posted: August 11, 2026
• Study Start: May 21, 2026
• Primary Completion (Estimated): April 19, 2027
• Study Completion (Estimated): April 19, 2027
• Last Updated: August 11, 2026

Record last verified: 2026-08

Locations

GR (1)