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Diabetic Retinopathy Grading research benchmarks – Page 2 · SOTA2 Research

Diabetic Retinopathy Grading

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Eyepacs (held-out)

MedXAI (Fusion)

74.8Accuracy

5

Feb 26, 2026

0.864AUROC

4

Mar 20, 2026

0.807AUROC

4

Mar 20, 2026

0.903AUROC

4

Mar 20, 2026

94.8AUROC

4

Mar 20, 2026

EYEPACS Source Domain (Generalization to other domains)

62.5Accuracy

4

Feb 26, 2026

MESSIDOR2 Source Domain Generalization to other domains

MedXAI (Fusion)

65.5Accuracy

4

Feb 26, 2026

MESSIDOR Source Domain Generalization to other domains

0.671Accuracy

4

Feb 26, 2026

APTOS Source Domain Generalization to other domains

MedXAI (Fusion)

59.9Accuracy

4

Feb 26, 2026

Diabetic Retinopathy fundus images (test)

Ours: LQAP + EDL

87.6Accuracy

3

Feb 26, 2026

Messidor-2, IDRiD, Kaggle and local dataset (train)

Jagan Mohan et al.

98.6Accuracy

1

May 12, 2026

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