To run, first install the requirements for python3.8 in the requirements.txt.
Download MIMIC-CXR first (and Chexpert, covidx, and rsna for external validation).
Run preprocess_chexpert.ipynb, preprocess_covidx.ipynb, preprocess_rsna.ipynb. Adjust the base path at the start to your download location. The path for MIMIC-CXR also needs to be adapted in dataset_utils.pyin line 21 .
The eda.ipynb script can be used for some data exploration.
The contrastive_learning.ipynb notebook takes care of the contrastive learning. The sl.py fine-tunes the whole network. The scripts lin_probe_sklearn.pyand lin_probe_multi.py train linear probes on top of the CLIP features.
If you have trained all the models from the paper, the eval_cl.ipynb and eval_sl.ipynb notebooks will create all the plots and figures from the paper (except the text2image results).