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Glaucoma Screening Using Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program

NCT07243665 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1040

Last updated 2026-01-29

No results posted yet for this study

Summary

Glaucoma is major cause of irreversible blindness and is characterized by optic nerve damage and visual field loss. Screening for glaucoma is challenging due to lack of a simple, accurate, cost-efficient and standardized process. Artificial intelligence, (AI) especially deep learning (DL) algorithms have potential to automate glaucoma detection, but have to be evaluated in real world settings, before public deployment. This study aims to evaluate the screening accuracy of a DL algorithm for glaucoma detection using colour fundus photographs (CFP) in a pragmatic randomised control trial (RCT). The algorithm will be tested in 1040 eligible patients with diabetes, recruited from the Diabetes \& Metabolism Centre's clinics under the Singapore Integrated Diabetic Retinopathy Program (SiDRP) and randomized to 2 arms: AI-assisted model vs current standard of care (grader assessment). The performance of both arms will be compared to performance of study ophthalmologist in diagnosing glaucoma. We hypothesize that the DL model has better screening performance in detecting glaucoma in the community, compared to the current practice method.

Conditions

Interventions

DIAGNOSTIC_TEST

Artificial Intelligence model to detect glaucoma

A Vision Transformer model to detect glaucoma from fundus photos

OTHER

No intervention

Control group with current practice model by human graders

Sponsors & Collaborators

  • Singapore General Hospital

    collaborator OTHER

  • SingHealth Polyclinics

    collaborator OTHER

  • Singapore Eye Research Institute

    lead OTHER

Principal Investigators

  • Ching-Yu Cheng, MD, PhD · Singapore Eye Research Institute

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
21 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-11-17
Primary Completion
2026-08-31
Completion
2027-03-31

Countries

  • Singapore

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 NCT07243665 on ClinicalTrials.gov