ArticleDiabetic medicine : a journal of the British Diabetic Association2021
THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.
Article in Diabetic medicine : a journal of the British Diabetic Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 19 citations in OpenAlex.
- Retinal BioAge is associated with indicators of cardiovascular-kidney-metabolic syndrome in UK and US populations.Scientific reports · 2026Article
- How early can we detect diabetic retinopathy? A narrative review of imaging tools for structural assessment of the retina.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2025Review
- Mapping and Summarizing the Research on AI Systems for Automating Medical History Taking and Triage: Scoping Review.Journal of medical Internet research · 2025Article
- Blood Pressure Predicted From Artificial Intelligence Analysis of Retinal Images Correlates With Future Cardiovascular Events.JACC. Advances · 2024Article
- Development and validation of a deep-learning model to predict 10-year atherosclerotic cardiovascular disease risk from retinal images using the UK Biobank and EyePACS 10K datasets.Cardiovascular digital health journal · 2024Article
- A multi-centre prospective evaluation of THEIA™ to detect diabetic retinopathy (DR) and diabetic macular oedema (DMO) in the New Zealand screening program.Eye (London, England) · 2023Article
- Article
- THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.Diabetic medicine : a journal of the British Diabetic Association · 2021Article
- Barriers and Enablers Influencing the Implementation of Artificial Intelligence for Diabetic Retinopathy Screening in Clinical Practice: A Scoping Review.Clinical & experimental ophthalmologyArticle
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Authors and funding
7 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within the New Zealand national diabetic retinopathy screening programme.
methodsThe THEIA™ artificial intelligence system for retinopathy and maculopathy screening, was developed at Toku Eyes using routinely collected retinal screening datasets from two of the largest district health boards in Auckland, New Zealand: the Auckland District Health Board and the Counties Manukau District Health Board. All retinal images from consecutive individuals receiving retinal screening between January 2009 and December 2018 were used. Images were labelled as non-sight-threatening, potentially referable or sight-threatening for New Zealand implementation, or as referable (potentially referable + sight-threatening)/non-referable (non-sight-threatening) for global comparison.
resultsData from 32 354 unique people with diabetes (63 843 when including multiple visits) were available, of which 95-97%, 0.9-2.4% and 1.1-3.1% were categorized as non-sight-threatening, potentially referable and sight-threatening, respectively. Using the referable/non-referable categories, THEIA achieved overall sensitivity of 94% (95% CI 92-95) in the Auckland District Health Board and 95% (95% CI 92-97) in the Counties Manukau District Health Board datasets, while preserving specificity of 63% (95% CI 62-64) for the Auckland District Health Board and 61% (95% CI 60-62) for the Counties Manukau District Health Board. Implementing THEIA into a New Zealand national diabetic screening programme could significantly reduce the manual grading load.
conclusionTHEIA, an artificial intelligence tool to assist in clinical decision-making, tailored to the needs of the New Zealand national diabetic screening programme, delivered high sensitivity for detecting referable retinopathy within the multi-ethnic New Zealand population with diabetes.
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