| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Medical Image Classification | MedMnist BloodMnist (test) | Accuracy99 | 65 | |
| Medical Image Classification | MedMNIST Breast (test) | Accuracy92.8 | 36 | |
| Medical Image Classification | MedMNIST Derma (test) | Accuracy84.1 | 36 | |
| Medical Image Classification | MedMNIST Pneumonia (test) | Accuracy96.2 | 36 | |
| 3D Image Classification | MedMNIST 3D v2 (test) | Organ Accuracy0.998 | 36 | |
| Medical Image Classification | MedMNIST OrganS (test) | Accuracy82.4 | 30 | |
| Supervised Learning | 3D MedMNIST | Top-1 Balanced Accuracy77.14 | 24 | |
| Supervised Learning | MedMNIST 2D | Top-1 Balanced Accuracy82.42 | 24 | |
| Medical Image Classification | MedMNIST DermaMNIST v2 (test) | Accuracy94.4 | 22 | |
| Image Classification | MedMNIST OrganAMNIST (test) | Accuracy97.62 | 22 | |
| Semi-supervised classification | MedMNIST Breast (10% train 90% test) | Accuracy85.7 | 20 | |
| Base-to-New Generalization | MedMNIST+ Base-to-New v2 | Base Accuracy57.84 | 20 | |
| Image Classification | MedMNIST 2D OrganAMNIST | Accuracy96.2 | 20 | |
| Image Classification | MedMNIST Sub | Final Epoch Accuracy73.61 | 18 | |
| Adversarial Attack | ChestMNIST (test) | KMRa0.03 | 15 | |
| Image Classification | MEDMNISTC (Dir(0.1)) | Accuracy66.97 | 13 | |
| Image Classification | MEDMNISTA Dir(0.5) | Accuracy41.22 | 13 | |
| Image Classification | MedMNIST | DermalMNIST Top-1 Accuracy82.1 | 13 | |
| Medical Image Classification | MedMNIST v2 (test) | Average Accuracy26.8 | 13 | |
| Image Classification | MedMNIST 2D OrganCMNIST | Accuracy94.4 | 12 | |
| Image Classification | MedMNIST BloodMNIST 2D | Accuracy98.7 | 12 | |
| Image Classification | MedMNIST PneumoniaMNIST 2D | Accuracy93.6 | 12 | |
| Image Classification | MedMNIST 2D OCTMNIST | Accuracy92.2 | 12 | |
| Image Classification | MedMNIST PathMNIST (test) | Accuracy86.63 | 12 | |
| Classification | MedMNIST3D Nodule (test) | Accuracy88.7 | 11 |