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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
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
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
2000
Start Date
2026-05-21
Completion Date
2027-04-19
Last Updated
2026-08-11
Healthy Volunteers
Yes
Conditions
Interventions
Color retinal fundus photograph
Diagnostic Test: color fundus photograph Description: Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.
Locations (1)
University Hospital of Alexandroupolis
Alexandroupoli, Greece