| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| 8-class classification | BloodMNIST | Accuracy99 | 33 | |
| Medical Image Classification | BloodMNIST | AUC100 | 18 | |
| Image Classification | BloodMNIST balanced (test) | Balanced Accuracy98.5 | 16 | |
| Federated Image Classification | BloodMNIST (test) | Average Global Accuracy64.5 | 12 | |
| Image Classification | BloodMNIST v2 (test) | AUC99.8 | 12 | |
| Classification | BloodMNIST v1 (test) | Accuracy96 | 12 | |
| Classification | BloodMNIST (test) | Coverage91.2 | 11 | |
| Medical Image Classification | BloodMNIST | Accuracy70.15 | 10 | |
| Image Classification | BloodMNIST 2-way sharded (test) | Test Accuracy91 | 9 | |
| Image Classification Calibration | BloodMNIST | NLL0.3119 | 9 | |
| Out-of-Distribution Detection | BloodMNIST | ID Accuracy90.21 | 8 | |
| Open-Set Recognition | BloodMNIST t=5 (test) | Accuracy98.5 | 8 | |
| Model Editing | bloodmnist | ΔACC (pp)3.27 | 6 | |
| Image Classification | BloodMNIST C | Accuracy77 | 6 | |
| Image Classification | BloodMNIST | Top-1 Accuracy96.23 | 4 | |
| Image Classification | BloodMNIST MedMNIST (test) | Accuracy95.01 | 2 | |
| Multi-Instance Learning Classification | BloodMNIST v2 (test) | Metric- | 0 |