ReviewIndian journal of ophthalmology2019
Artificial intelligence in diabetic retinopathy: A natural step to the future.
Review in Indian journal of ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis 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
51 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.Frontiers in endocrinology · 2023Pooled it
- Trial
- Dual-SwinOrd: A Dual-Head Swin Transformer with Semantic Prior Injection for Ordinal Diabetic Retinopathy Grading.Bioengineering (Basel, Switzerland) · 2026Article
- Diagnostic Accuracy and Real-Life Advantages of the MONA.health Artificial Intelligence Software in Screening for Diabetic Retinopathy and Maculopathy.Diagnostics (Basel, Switzerland) · 2026Article
- The Burden of Delayed Diabetic Retinopathy Management and Use of Artificial Intelligence-Driven Screening Tools: A Systematic Literature Review.Ophthalmology and therapy · 2026Review
- Artificial intelligence-based apps for screening and diagnosing diabetic retinopathy and common ocular disorders.World journal of methodology · 2025Review
- Assessing adoption of human and AI-enabled diabetic retinopathy screening in primary healthcare settings: findings from a pragmatic trial.Archives of public health = Archives belges de sante publique · 2025Article
- Artificial Intelligence in Ophthalmology: Practical Applications, Subspecialty Evidence and Real-World Deployment.Cureus · 2025Review
- Enhanced performance in automated diabetic retinopathy diagnosis achieved through Voronoi diagrams and artificial intelligence.Scientific reports · 2025Article
- Real-World Evaluation of AI-Driven Diabetic Retinopathy Screening in Public Health Settings: Validation and Implementation Study.JMIR medical informatics · 2025Article
- Artificial intelligence for advancing eye care in resource-poor settings: Assessing the predictive accuracy of an AI-model for diabetic retinopathy screening in India.Global epidemiology · 2025Article
- Application of Artificial Intelligence in Retinopathy of Prematurity From 2010 to 2023: A Bibliometric Analysis.Health science reports · 2025Article
- Review
- A Future Picture: A Review of Current Generative Adversarial Neural Networks in Vitreoretinal Pathologies and Their Future Potentials.Biomedicines · 2025Review
- Diabetic Retinopathy-A Review.Current diabetes reviews · 2025Review
- Detection Rate of Diabetic Retinopathy Before and After Implementation of Autonomous AI-based Fundus Photograph Analysis in a Resource-Limited Area in Belize.Clinical ophthalmology (Auckland, N.Z.) · 2025Article
- Nurse-Led Model in Diabetic Retinopathy Screening: An Exploratory Scoping Review of Nurses' Roles and Contributions.Clinical ophthalmology (Auckland, N.Z.) · 2025Review
- Artificial Intelligence in Medicine and Imaging Applications.Current pharmaceutical design · 2025Review
- Article
- Diabetic Retinopathy Features Segmentation without Coding Experience with Computer Vision Models YOLOv8 and YOLOv9.Vision (Basel, Switzerland) · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Use of artificial intelligence in medicine in an evolving technology which holds promise for mass screening and perhaps may even help in establishing an accurate diagnosis. The ability of complex computing is to perform pattern recognition by creating complex relationships based on input data and then comparing it with performance standards is a big step. Diabetic retinopathy is an ever-increasing problem. Early screening and timely treatment of the same can reduce the burden of sight threatening retinopathy. Any tool which can aid in quick screening of this disorder and minimize requirement of trained human resource for the same would probably be a boon for patients and ophthalmologists. In this review we discuss the current status of use of artificial intelligence in diabetic retinopathy and few other common retinal disorders.
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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.