ArticlePatterns (New York, N.Y.)2022
DeepDRiD: Diabetic Retinopathy-Grading and Image Quality Estimation Challenge.
Article in Patterns (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic accuracy and clinical performance of deep learning models for grading diabetic retinopathy: a systematic review and meta-analysis.Frontiers in endocrinology · 2026Pooled it
- The German National Cohort: Ophthalmic Assessment, Baseline Profile, and Potential for Artificial Intelligence-Based Eye Research.Ophthalmology science · 2026Article
- Comparative Analysis of CNN and Transformer Models for Multi-Class Diabetic Retinopathy Grading Using Fundus Images.Diagnostics (Basel, Switzerland) · 2026Article
- A Text-Guided Lesion Mining Vision-Language Ordinal Classification Framework for Diabetic Retinopathy Grading.Journal of imaging · 2026Article
- Multiscale feature fusion for few-shot medical image learning with fisher information-driven layer selection.Visual computing for industry, biomedicine, and art · 2026Article
- Comparative Analysis of General-Purpose vs. Domain-Specific Multimodal Models for Diabetic Retinopathy Classification.Diagnostics (Basel, Switzerland) · 2026Article
- A multimodal retinal image dataset for diabetic retinopathy detection using foundation models.Scientific data · 2026Article
- A large scale statistical analysis of quantum and classical neural networks in the medical domain.Scientific reports · 2026Article
- From discarding to leveraging: quality-aware collaborative learning for robust diabetic retinopathy grading.Frontiers in medicine · 2026Article
- Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging.IEEE access : practical innovations, open solutions · 2026Article
- Multimodal Deep Learning for Diabetic Retinopathy: A Survey.Journal of ophthalmology · 2026Review
- Article
- Artificial Intelligence in Ophthalmology: Practical Applications, Subspecialty Evidence and Real-World Deployment.Cureus · 2025Review
- Ultrawidefield-to-Conventional Fundus Image Translation with Scaled Feature Registration and Distorted Vessel Correction.Bioengineering (Basel, Switzerland) · 2025Article
- Vision-language foundation models for medical imaging: a review of current practices and innovations.Biomedical engineering letters · 2025Review
- Enhancing diagnostic accuracy in rare and common fundus diseases with a knowledge-rich vision-language model.Nature communications · 2025Article
- Ultra-wide-field fundus photography and AI-based screening and referral for multiple ocular fundus diseases.Cell reports. Medicine · 2025Article
- Enhanced hierarchical attention mechanism for mixed MIL in automatic Gleason grading and scoring.Scientific reports · 2025Article
- An inherently interpretable AI model improves screening speed and accuracy for early diabetic retinopathy.PLOS digital health · 2025Article
- A comprehensive and easy-to-use multi-domain multi-task medical imaging meta-dataset.Scientific data · 2025Article
Corrections and comments
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Authors and funding
26 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We described a challenge named "Diabetic Retinopathy (DR)-Grading and Image Quality Estimation Challenge" in conjunction with ISBI 2020 to hold three sub-challenges and develop deep learning models for DR image assessment and grading. The scientific community responded positively to the challenge, with 34 submissions from 574 registrations. In the challenge, we provided the DeepDRiD dataset containing 2,000 regular DR images (500 patients) and 256 ultra-widefield images (128 patients), both having DR quality and grading annotations. We discussed details of the top 3 algorithms in each sub-challenges. The weighted kappa for DR grading ranged from 0.93 to 0.82, and the accuracy for image quality evaluation ranged from 0.70 to 0.65. The results showed that image quality assessment can be used as a further target for exploration. We also have released the DeepDRiD dataset on GitHub to help develop automatic systems and improve human judgment in DR screening and diagnosis.
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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.