0-seg_train.ipynb
- Train the lung segmentation model1-seg_apply.py
- Create masks for a classification dataset via the segmentation model2-smooth_masks.py
- Postprocess the predicted lung masks to smooth them out3-create_chexpert.ipynb
- Create the binary classification version of CheXpert3-create_datasets.py
- Apply the smoothed masks and create train/val/test splits of classification dataset4-clf_train.ipynb
- Train the downstream classification model4-clf_train.py
- Train the downstream classification model5-eval.py
- Evaluate the trained classification models
-
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Evaluation of non-ROI masking to improve OOD generalization in chest x-ray disease classification
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basedrhys/non-roi-masking
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Evaluation of non-ROI masking to improve OOD generalization in chest x-ray disease classification
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