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Diabetic Retinopathy Grading

Grading the severity of diabetic retinopathy from (ophthalmic) fundus images

Papers

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Showing 21–30 of 44 papers

TitleStatusHype
Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus ImagesCode1
SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy GradingCode1
INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical ExamplesCode0
Identifying the key components in ResNet-50 for diabetic retinopathy grading from fundus images: a systematic investigationCode1
Semi-Supervised Auto-Encoder Graph Network for Diabetic Retinopathy Grading—0
A Multi-stage Transfer Learning Framework for Diabetic Retinopathy Grading on Small Data—0
Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction—0
Lesion-based Contrastive Learning for Diabetic Retinopathy Grading from Fundus ImagesCode1
On the Robustness of Pretraining and Self-Supervision for a Deep Learning-based Analysis of Diabetic Retinopathy—0
Lesion-Aware Transformers for Diabetic Retinopathy Grading—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IncRes-v2-FTCDWAUC0.99—Unverified
2InceptionV3 EnsembleAUC0.95—Unverified