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

Sponsor
Democritus University of Thrace
Study ID
NCT07758582
Status
Recruiting
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Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Accepted

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.

Study Details

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

Key Dates

First listed
Aug 11, 2026
Start date
May 21, 2026
Status verified
Aug 2026
Primary completion
Apr 19, 2027
Completion
Apr 19, 2027

Study Design

Enrollment
2,000 participants (estimated)

Arms

  • Arm: Participants from outpatient clinics

Primary Outcome Measure

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. [ Time Frame: 1 year ]

Central Contacts

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