Comments (3)
For the final SIP task it's not exactly possible. There is a lot of manual data engineering for extracting information from electronic health records that probably doesn't generalize between hospitals - you'll have to work with your IT department on that. We do provide a script for fine-tuning on the public X-ray data sets, which you can find here: https://github.com/facebookresearch/CovidPrognosis/tree/master/cp_examples/sip_finetune.
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@mmuckley Thank you for your comments! However, there is no IT department in our hospital, and I am working hard by myself. But I will try to make a data module..
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Hello @JihwanEom, I would be cautious working with EHR if you don't know someone with experience. There are quite a few gotchas, and it can be a little bit confusing.
That being said, for writing dataloaders the torchxrayvision
package has a lot of good examples for X-ray radiograph datasets to see how these things are structured.
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Related Issues (13)
- Inference result from last Linear Classifier of MIP Model HOT 2
- Missing keys error when loading pretrain model to train_sip.py HOT 2
- SIP Finetune on CheXpert - Validation sanity check error - target has to be an integer tensor HOT 6
- Transformer masking HOT 5
- Normalization during training HOT 4
- Transform for trainset and valset during pretraining HOT 1
- Number of epochs used for pre-training HOT 1
- release of pretrained model for MIP HOT 4
- Does this repository really reproduce provided research papers? HOT 1
- I cannot figure out the inputs to MIPModel HOT 4
- SUM Pooling causing multiplication of matrix with different shape HOT 2
- Run inference HOT 4
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