APTOS
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Anomaly Detection | APTOS (test) | I-AUROC100 | 78 | |
| Diabetic Retinopathy Diagnosis | APTOS 2019 (Population Shift) | AUC94.9 | 36 | |
| Medical Image Classification | APTOS 2019 (test) | Test Accuracy84.8 | 35 | |
| Diabetic Retinopathy (DR) grading | APTOS | Accuracy73.2 | 25 | |
| Diabetic Retinopathy grading | APTOS ESDG (test) | AUC70.6 | 24 | |
| Medical Image Classification | APTOS 2019 | Accuracy85.8 | 14 | |
| Medical Image Classification | APTOS | F1 Score72.47 | 12 | |
| Diabetic Retinopathy grading | Aptos (held-out) | Accuracy73.46 | 11 | |
| Diabetic Retinopathy Grading | APTOS (test) | Accuracy75.1 | 10 | |
| Out-of-Distribution Detection | APTOS Near-OOD 2019 (test) | AUROC74.2 | 10 | |
| Imbalanced Classification | APTOS (test) | Macro F173.02 | 10 | |
| Classification | APTOS | Accuracy93.43 | 9 | |
| Fundus image grading | APTOS Target-imbalanced | OA85 | 9 | |
| Fundus image grading | APTOS Sources-imbalanced | OA82.81 | 9 | |
| Ordinal Regression | APTOS (test) | Accuracy0.771 | 9 | |
| Continual Learning | APTOS (final stage) | Accuracy84.9 | 8 | |
| Medical Image Classification | APTOS Kaggle-EyePACS 2019 (test) | Accuracy70.9 | 7 | |
| Image Synthesis | APTOS | FID42.905 | 7 | |
| Diabetic Retinopathy Classification | APTOS | Accuracy75.1 | 6 | |
| Diabetic Retinopathy Classification | APTOS 2019 | AUROC0.949 | 6 | |
| Diabetic Retinopathy Classification | APTOS 2019 (test) | Accuracy97.8 | 5 | |
| Image Classification | APTOS Retinology Fundus | Accuracy93.43 | 4 | |
| Diabetic Retinopathy grading | APTOS | AUROC94.8 | 4 | |
| Diabetic Retinopathy grading | APTOS Source Domain Generalization to other domains | Accuracy59.9 | 4 |
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