HAM10000
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Skin lesion classification | HAM10000 (test) | Accuracy93.32 | 83 | |
| Medical Image Classification | HAM10000 | Accuracy83.4 | 39 | |
| Medical Image Segmentation | HAM10000 | mDSC0.9471 | 27 | |
| Image Denoising | HAM10000 (test) | SSIM0.95 | 20 | |
| Image Denoising | HAM10000 52 (test) | PSNR38.8 | 20 | |
| Medical Image Classification | HAM10000 (random) | Accuracy83.3 | 19 | |
| Attribution Analysis | HAM10000 | SEG-GRAD0.1726 | 13 | |
| Categorical skin lesion classification | HAM10000 original (test) | Accuracy0.8915 | 12 | |
| Medical Image Classification | HAM10000 D5 (test) | Accuracy99.8 | 12 | |
| Imbalanced Classification | HAM10000 (test) | Macro F1 Score81.97 | 10 | |
| Image Classification | HAM10000 | Accuracy82.8 | 10 | |
| Skin Cancer Classification | HAM10000 2018 | Group 0 Score71.2 | 9 | |
| Skin Lesion Classification | HAM10000 | Accuracy96.32 | 9 | |
| Skin lesion classification | HAM10000 (test) | AUC0.97 | 8 | |
| Classification | HAM10000 D5 | PGD Accuracy65.6 | 7 | |
| OOD Detection | HAM10000 (test) | AUC1 | 7 | |
| Classification | HAM10000 Linear Evaluation 100% ratio | Accuracy77.89 | 7 | |
| Classification | HAM10000 Linear Evaluation 10% ratio | Accuracy69.31 | 7 | |
| Classification | HAM10000 Linear Evaluation 1% ratio | Accuracy62.71 | 7 | |
| Image Segmentation | HAM10000 47 (test) | mIoU78.8 | 5 | |
| Skin Lesion Classification | HAM10000 1,000-image subset 1.0 | Accuracy78.5 | 4 | |
| Explanation Generation | HAM10000 | EE1 | 4 | |
| Fine-grained Image Classification | HAM10000 | Accuracy79.37 | 4 | |
| Identification of skin lesions | HAM10000 | Accuracy (%)85 | 3 | |
| Classification | Ham10000 (test) | Accuracy70.7 | 2 |
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