ArticleBMJ open diabetes research & care2023
Artificial intelligence for diabetic retinopathy in low-income and middle-income countries: a scoping review.
Article in BMJ open diabetes research & care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 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.
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Who cites it
30 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Precision or Paradox? AI-Driven Adiposity Imaging in Women With Overweight and Obesity: A Systematic Review and Meta-Analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Pooled it
- Economic Evaluation of Diabetic Retinopathy Screening in Developing Countries: A Systematic Review.Korean journal of ophthalmology : KJO · 2025Pooled it
- Artificial Intelligence improves follow-up appointment uptake for diabetic retinal assessment: a systematic review and meta-analysis.Eye (London, England) · 2025Pooled it
- Using the Normalization Process Theory to study facilitators and barriers to sustainable implementation of artificial intelligence-based diabetic retinopathy screening in Rwanda.Dialogues in health · 2026Article
- Edge-Deployable Lightweight Deep Learning for Hypertensive Retinopathy Grading from En-Face OCT: A Patient-Level Feasibility Study.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial intelligence in diabetic retinopathy: from automated screening to risk-stratified care.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Diagnostic performance of an artificial intelligence software for diabetic retinopathy organised screening in a pilot study.Scientific reports · 2026Article
- An explainable ensemble for diabetic retinopathy grading with a novel confidence quality factor and configurable heatmaps.Medical & biological engineering & computing · 2026Article
- Article
- Dissemination and implementation science for global ophthalmology: closing the last-mile translational gap.Frontiers in public health · 2026Review
- Review
- Highly efficient homomorphic encryption-based federated learning for diabetic retinopathy classification.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Revolutionizing diabetic retinopathy screening and management: The role of artificial intelligence and machine learning.World journal of clinical cases · 2025Article
- A Future Picture: A Review of Current Generative Adversarial Neural Networks in Vitreoretinal Pathologies and Their Future Potentials.Biomedicines · 2025Review
- Artificial intelligence in proliferative diabetic retinopathy: advancing diagnosis, precision surgery, and anti-VEGF therapy optimization.Frontiers in medicine · 2025Review
- A panoramic perspective: application prospects and outlook of multimodal artificial intelligence in the management of diabetic retinopathy.Frontiers in public health · 2025Review
- Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.Annals of medicine · 2024Article
- Foundation model-driven distributed learning for enhanced retinal age prediction.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa.JMIR formative research · 2024Article
- Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population.Diabetology & metabolic syndrome · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Diabetic retinopathy (DR) is a leading cause of blindness globally. There is growing evidence to support the use of artificial intelligence (AI) in diabetic eye care, particularly for screening populations at risk of sight loss from DR in low-income and middle-income countries (LMICs) where resources are most stretched. However, implementation into clinical practice remains limited. We conducted a scoping review to identify what AI tools have been used for DR in LMICs and to report their performance and relevant characteristics. 81 articles were included. The reported sensitivities and specificities were generally high providing evidence to support use in clinical practice. However, the majority of studies focused on sensitivity and specificity only and there was limited information on cost, regulatory approvals and whether the use of AI improved health outcomes. Further research that goes beyond reporting sensitivities and specificities is needed prior to wider implementation.
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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.