ReviewJournal of diabetes science and technology2016
Retinal Imaging Techniques for Diabetic Retinopathy Screening.
Review in Journal of diabetes science and technology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 8 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
63 citing papers in PubMed, 8 syntheses or guidelines pooled it.
- Prevalence of vision impairment among patients with diabetes mellitus in sub-Saharan Africa: A systematic review and meta-analysis.PloS one · 2025Pooled it
- In-depth analysis of research hotspots and emerging trends in AI for retinal diseases over the past decade.Frontiers in medicine · 2024Pooled it
- Accuracy of artificial intelligence model for infectious keratitis classification: a systematic review and meta-analysis.Frontiers in public health · 2023Pooled it
- Five regions, five retinopathy screening programmes: a systematic review of how Portugal addresses the challenge.BMC health services research · 2021Pooled it
- Assessment of retinal neurodegeneration with spectral-domain optical coherence tomography: a systematic review and meta-analysis.Eye (London, England) · 2021Pooled it
- Use of Smartphones to Detect Diabetic Retinopathy: Scoping Review and Meta-Analysis of Diagnostic Test Accuracy Studies.Journal of medical Internet research · 2020Pooled it
- Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application.Current diabetes reports · 2019Pooled it
- Action on diabetic macular oedema: achieving optimal patient management in treating visual impairment due to diabetic eye disease.Eye (London, England) · 2017Guideline
- Prognostic value of expanded-field OCT angiography in visual acuity outcomes for non-proliferative diabetic retinopathy.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Article
- Deep Learning Prediction of Retinal Thickness from Near-Infrared Fundus Photography: Toward Decentralized Quantitative Assessment of Diabetic Macular Edema.Journal of personalized medicine · 2026Article
- Deep learning strategies for estimating retinal thickness from fundus images: a comparative study with multi-device data.Scientific reports · 2026Article
- Customizing AI-based screening with real-world data: Practical insights from diabetic retinopathy.Acta ophthalmologica · 2026Observational
- Nailfold Capillaroscopy: A Non-Invasive Tool for Early Detection of Microvascular Alterations in Children with Type 1 Diabetes MellitusJournal of clinical research in pediatric endocrinology · 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
- Forecasting the diabetic retinopathy progression using generative adversarial networks.Communications medicine · 2025Article
- Liquid Biopsy Combined with Multi-Omics Approaches in Diagnosis, Management, and Progression of Diabetic Retinopathy.Biomedicines · 2025Review
- Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study.BMJ open ophthalmology · 2025Article
- Use of artificial intelligence with retinal imaging in screening for diabetes-associated complications: systematic review.EClinicalMedicine · 2025Review
- A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.Scientific reports · 2024Article
- The use of artificial intelligence to assess diabetic eye disease among the Greenlandic population.International journal of circumpolar health · 2024Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Due to the increasing prevalence of diabetes mellitus, demand for diabetic retinopathy (DR) screening platforms is steeply increasing. Early detection and treatment of DR are key public health interventions that can greatly reduce the likelihood of vision loss. Current DR screening programs typically employ retinal fundus photography, which relies on skilled readers for manual DR assessment. However, this is labor-intensive and suffers from inconsistency across sites. Hence, there has been a recent proliferation of automated retinal image analysis software that may potentially alleviate this burden cost-effectively. Furthermore, current screening programs based on 2-dimensional fundus photography do not effectively screen for diabetic macular edema (DME). Optical coherence tomography is becoming increasingly recognized as the reference standard for DME assessment and can potentially provide a cost-effective solution for improving DME detection in large-scale DR screening programs. Current screening techniques are also unable to image the peripheral retina and require pharmacological pupil dilation; ultra-widefield imaging and confocal scanning laser ophthalmoscopy, which address these drawbacks, possess great potential. In this review, we summarize the current DR screening methods using various retinal imaging techniques, and also outline future possibilities. Advances in retinal imaging techniques can potentially transform the management of patients with diabetes, providing savings in health care costs and resources.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.