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E-CLAIR: Efficiency and Cost-effectiveness of Artificial Intelligence Based Diabetic Retinopathy Screening in Flanders

NCT05391659 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1200

Last updated 2022-05-26

No results posted yet for this study

Summary

To evaluate the efficiency and cost-effectiveness of an artificial intelligence based diabetic retinopathy screening program in Flanders

Conditions

Interventions

DEVICE

deep learning

a form of artificial intelligence (AI), has been introduced for automated analysis of images

DIAGNOSTIC_TEST

remote grading of fundus images

referrable cases identified by DR AI tool will be remotely graded by a human

DIAGNOSTIC_TEST

gold standard

examination by ophthalmologist

Sponsors & Collaborators

  • Universitaire Ziekenhuizen KU Leuven

    lead OTHER

Principal Investigators

  • Julie Jacob, MD PhD · Universitaire Ziekenhuizen KU Leuven

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-06-17
Primary Completion
2022-11-01
Completion
2022-12-01

Countries

  • Belgium

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05391659 on ClinicalTrials.gov