An observational study in Diabetic Retinopathy, sponsored by Democritus University of Thrace. Recruiting at 1 site in Greece. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-08-11.
Sponsored by Democritus University of Thrace · Observational
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
778 studies on the registry are indexed under Diabetic Retinopathy; 142 are open to participants now.
This study's planned enrollment of 2,000 is above the median of 172 across 263 observational studies indexed under Diabetic Retinopathy.
Browse Diabetic Retinopathy studies →Democritus University of Thrace is the lead sponsor of 70 studies on the registry; 8 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Participants that are able to provide consent for their fundus photograph to be recorded
Inclusion Criteria Age ≥18 years Availability of a high-resolution color fundus photograph Confirmed diagnosis established by an ophthalmology specialist Exclusion Criteria Poor-quality retinal images Concomitant ocular diseases that interfere with image interpretation
Diagnostic Test: Color retinal fundus photograph
Diagnostic Test: color fundus photograph Description: Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.
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
Plan to share: Undecided
No publications or documents are linked to this record.
Started May 2026 (actual). Primary completion is estimated for Apr 2027, 10 months after the start.
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Democritus University of Thrace