Image Classification
PyTorch
timm
English
French
medical-imaging
histopathology
computational-pathology
breast-cancer
lymph-node
metastasis-detection
convnext
patchcamelyon
grad-cam
uncertainty
Instructions to use hakim78/Cancer_pathos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use hakim78/Cancer_pathos with timm:
import timm model = timm.create_model("hf-hub:hakim78/Cancer_pathos", pretrained=True) - Notebooks
- Google Colab
- Kaggle
Add v2 result: recap_table.csv
Browse files
results_v2/recap_table.csv
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metric,CV_mean_std,Test_TTA,Test_noTTA
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AUC,0.9975+/-0.0001,0.9979,0.9974
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Accuracy,0.9821+/-0.0008,0.9847,0.9827
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F1,0.9778+/-0.0010,0.9810,0.9787
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Brier,0.0212+/-0.0005,0.0172,0.0183
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Sensitivity,0.9753+/-0.0015,0.9794,0.9779
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Specificity,0.9867+/-0.0006,0.9882,0.9860
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