Image Classification
timm
ONNX
PyTorch
English
medical
histopathology
cancer-detection
binary-classification
efficientnet
int8
Eval Results (legacy)
Instructions to use AegisOSS/stage-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use AegisOSS/stage-1 with timm:
import timm model = timm.create_model("hf_hub:AegisOSS/stage-1", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "overall": { | |
| "accuracy": 0.9209183673469388, | |
| "recall_sensitivity": 0.9455605962410888, | |
| "precision": 0.8821039903264812, | |
| "f1_score": 0.9127306850172037, | |
| "specificity": 0.9017632241813602, | |
| "roc_auc": 0.9814147258032131, | |
| "missed_cancer_rate": 0.05443940375891121, | |
| "tp": 1459, | |
| "fp": 195, | |
| "tn": 1790, | |
| "fn": 84, | |
| "high_recall_threshold": 0.32, | |
| "high_recall_sensitivity": 0.9507453013609851, | |
| "high_recall_specificity": 0.8931989924433249, | |
| "high_recall_precision": 0.8737343656938654, | |
| "high_recall_target_met": true | |
| }, | |
| "per_dataset": { | |
| "breast_histopathology_patches": { | |
| "accuracy": 0.8708133971291866, | |
| "recall_sensitivity": 0.8201058201058201, | |
| "precision": 0.7673267326732673, | |
| "f1_score": 0.7928388746803069, | |
| "specificity": 0.8926940639269406, | |
| "roc_auc": 0.9370877727042111, | |
| "missed_cancer_rate": 0.17989417989417988, | |
| "tp": 155, | |
| "fp": 47, | |
| "tn": 391, | |
| "fn": 34, | |
| "high_recall_threshold": 0.09, | |
| "high_recall_sensitivity": 0.9523809523809523, | |
| "high_recall_specificity": 0.7465753424657534, | |
| "high_recall_precision": 0.6185567010309279, | |
| "high_recall_target_met": true | |
| }, | |
| "camelyon17_jxie": { | |
| "accuracy": 0.9612403100775194, | |
| "recall_sensitivity": 0.9617021276595744, | |
| "precision": 0.9338842975206612, | |
| "f1_score": 0.9475890985324947, | |
| "specificity": 0.9609756097560975, | |
| "roc_auc": 0.9960145303580695, | |
| "missed_cancer_rate": 0.03829787234042553, | |
| "tp": 226, | |
| "fp": 16, | |
| "tn": 394, | |
| "fn": 9, | |
| "high_recall_threshold": 0.54, | |
| "high_recall_sensitivity": 0.9531914893617022, | |
| "high_recall_specificity": 0.9804878048780488, | |
| "high_recall_precision": 0.9655172413793104, | |
| "high_recall_target_met": true | |
| }, | |
| "lc25000": { | |
| "accuracy": 0.9934426229508196, | |
| "recall_sensitivity": 0.989159891598916, | |
| "precision": 1.0, | |
| "f1_score": 0.9945504087193461, | |
| "specificity": 1.0, | |
| "roc_auc": 0.9978634641118196, | |
| "missed_cancer_rate": 0.01084010840108401, | |
| "tp": 365, | |
| "fp": 0, | |
| "tn": 241, | |
| "fn": 4, | |
| "high_recall_threshold": 0.99, | |
| "high_recall_sensitivity": 0.975609756097561, | |
| "high_recall_specificity": 1.0, | |
| "high_recall_precision": 1.0, | |
| "high_recall_target_met": true | |
| }, | |
| "camelyon17_djghosh": { | |
| "accuracy": 0.9875, | |
| "recall_sensitivity": 0.9822064056939501, | |
| "precision": 0.9928057553956835, | |
| "f1_score": 0.9874776386404294, | |
| "specificity": 0.992831541218638, | |
| "roc_auc": 0.9987499840559191, | |
| "missed_cancer_rate": 0.017793594306049824, | |
| "tp": 276, | |
| "fp": 2, | |
| "tn": 277, | |
| "fn": 5, | |
| "high_recall_threshold": 0.94, | |
| "high_recall_sensitivity": 0.9501779359430605, | |
| "high_recall_specificity": 0.996415770609319, | |
| "high_recall_precision": 0.996268656716418, | |
| "high_recall_target_met": true | |
| }, | |
| "skin_lesion_hm10000_binary_2k": { | |
| "accuracy": 0.8103448275862069, | |
| "recall_sensitivity": 0.925531914893617, | |
| "precision": 0.6718146718146718, | |
| "f1_score": 0.7785234899328859, | |
| "specificity": 0.7455089820359282, | |
| "roc_auc": 0.9201012867881259, | |
| "missed_cancer_rate": 0.07446808510638298, | |
| "tp": 174, | |
| "fp": 85, | |
| "tn": 249, | |
| "fn": 14, | |
| "high_recall_threshold": 0.19, | |
| "high_recall_sensitivity": 0.9521276595744681, | |
| "high_recall_specificity": 0.6586826347305389, | |
| "high_recall_precision": 0.6109215017064846, | |
| "high_recall_target_met": true | |
| }, | |
| "patch_camelyon": { | |
| "accuracy": 0.8882978723404256, | |
| "recall_sensitivity": 0.9359430604982206, | |
| "precision": 0.8538961038961039, | |
| "f1_score": 0.8930390492359932, | |
| "specificity": 0.8409893992932862, | |
| "roc_auc": 0.9655571344139431, | |
| "missed_cancer_rate": 0.06405693950177936, | |
| "tp": 263, | |
| "fp": 45, | |
| "tn": 238, | |
| "fn": 18, | |
| "high_recall_threshold": 0.21, | |
| "high_recall_sensitivity": 0.9501779359430605, | |
| "high_recall_specificity": 0.7879858657243817, | |
| "high_recall_precision": 0.8165137614678899, | |
| "high_recall_target_met": true | |
| } | |
| }, | |
| "threshold": 0.35, | |
| "split": "test" | |
| } |