ChestX-ray
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Multi-label Classification | ChestX-Ray14 (test) | AUROC (%)84.7 | 88 | |
| Thoracic Pathology Classification | ChestX-ray14 2017 (test) | Mean AUC81.77 | 29 | |
| Medical Image Re-identification | ChestX-Ray14 | Rank-1 Accuracy91.49 | 26 | |
| Medical Image Classification | ChestX-ray14 | Mean AUROC0.8274 | 18 | |
| Thoracic Disease Classification | ChestX-ray14 | Pneumothorax90.164 | 17 | |
| Disease Diagnosis | ChestX-ray14 (test) | Worst-case AUC0.776 | 14 | |
| Classification | ChestX-ray14 (test) | AUROC0.8361 | 10 | |
| Object Detection | ChestX-ray8 880 frontal-view subset | Atelectasis Score0.128 | 9 | |
| Medical Image Segmentation | ChestX-ray14 | mIoU76.5 | 9 | |
| Patient Verification | ChestX-ray14 (test) | AUC81.8 | 9 | |
| Localization | ChestX-ray14 1,000 samples (test) | mIoU26.3 | 8 | |
| Disease Classification | ChestX-Ray14 (val) | AUROC79.9 | 8 | |
| Classification | ChestX-ray14 Exp. (test) | F1 Score51.3 | 6 | |
| Membership Inference Attack | ChestX-ray8 | Accuracy69 | 6 | |
| Pneumonia Detection | ChestX-ray14 2017 (test) | F1 Score44.2 | 6 |
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