Using artificial intelligence to screen for glaucoma in people with diabetes
Tests an artificial intelligence tool for spotting glaucoma in adults with diabetes.
Plain-language title generated from the registry record
Registry title: Glaucoma Screening Using Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program
Key facts
- Where
- Singapore, SingaporeSee the site
Where in Singapore
- Singapore National Eye CentreSingapore, SingaporeTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Singapore Eye Research Institute
- Trial code
- NCT07243665
- Record updated
- 29 January 2026
- Original description
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.Read full original descriptionShow less
A Pragmatic Randomized Controlled Trial of a New Artificial Intelligence-Assisted Clinical Model in Opportunistic Screening for Glaucoma in the Singapore Integrated Diabetic Retinopathy Program
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.
Inclusion: Aged 21 years old and above, with diabetes, including type 1 and type 2,; Retinal photos of the patients can be taken with the fundus camera in the clinics, regardless of photos' quality, and; They are willing and capable of providing a written informed consent form.
Exclusion: Patients who have difficulty in having retinal photos taken or have difficulties in completing the ocular examination protocols according to investigator's decision; Any other contraindication(s) as indicated by the endocrinologists responsible for the patients; -.