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

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

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Key information

Conditions

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

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University Hospital of Alexandroupolis

Alexandroupoli, Greece

Location status: Recruiting

Location contact

Georgios Labiris

CONTACT

[email protected]

+302551030990

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

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.

Primary outcomes

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

Study contacts

Contact information is provided by the study sponsor or research team.

Georgios Labiris

CONTACT

[email protected]

+302551030990

Sponsors and collaborators

Lead sponsor

Democritus University of Thrace

Other

Registry information

Important dates

Study start: 2026
Primary completion: 2027
Study completion: 2027
First posted: Aug 11, 2026
Registry last updated: Aug 11, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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