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RecruitingNCT07758569Updated Aug 11, 2026

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

An observational study in Glaucoma, 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

From the registry’s dates

  • Started Apr 2026; still recruiting 6 months later.
Study type
Observational
Model
Cohort
Time perspective
Cross-sectional
Enrollment
2,000
Ages
18 Years and older
Sex
All
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Study summary

Primary Objective

To validate the artificial intelligence subsystem of the DDART medical device for the automated detection of lesions compatible with glaucoma in a random sample of retinal fundus photographs.

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Conditions studied

  • Glaucoma

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03

In context

Glaucoma

1,419 studies on the registry are indexed under Glaucoma; 223 are open to participants now.

This study's planned enrollment of 2,000 is above the median of 101 across 385 observational studies indexed under Glaucoma.

Browse Glaucoma studies →

Lead sponsor

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.

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Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

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

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Age ≥18 years. Availability of a high-resolution color fundus photograph. Confirmed diagnosis established by a specialist.

Exclusion criteria

Exclusion Criteria:

  • Poor-quality images. Coexisting ocular diseases that interfere with image interpretation.
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Study design

Observational model
Cohort
Time perspective
Cross-sectional
Enrollment
2,000 participants (estimated)
Patient registry
No

Interventions

  • Diagnostic testcolor fundus photograph

    Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.

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What researchers measure

Primary outcomes

  1. Validation of the sensitivity and specificity of the artificial intelligence subsystem for AMD detection

    Time frame: 1 year

  2. Validation of the sensitivity and specificity of the artificial intelligence subsystem for diabetic retinopathy detection

    Time frame: 1 year

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Study locations

1 of 1 sites recruiting
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References and documents

Individual participant data

Plan to share: Undecided

No publications or documents are linked to this record.

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Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Aug 11, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT07758569
Lead sponsor
Democritus University of Thrace
Responsible party
Georgios Labiris (Democritus University of Thrace, Democritus University of Thrace) — Principal investigator
First posted
Aug 11, 2026
Start date
Apr 21, 2026
Primary completion
Apr 19, 2027 (estimated)
Completion
Apr 19, 2027 (estimated)
Last update
Aug 11, 2026

Study contacts

Georgios Labiris
Contact
glampiri@med.duth.gr
+302551030990

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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