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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Georgios Labiris
- Phone Number: +302551030990
- Email: glampiri@med.duth.gr
Study Locations
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Alexandroupoli, Greece
- Recruiting
- University Hospital of Alexandroupolis
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Contact:
- Georgios Labiris
- Phone Number: +302551030990
- Email: glampiri@med.duth.gr
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
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Participants from outpatient clinics
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Diagnostic Test: color fundus photograph Description: Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
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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
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1 year
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Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 17745/01-04-2026
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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