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License: Other
Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
License: Other
In the paper you used 687 manually annotated MIMIC-CXR reports to evaluate your models, since MIMIC-CXR is already publicly available, is it possible to release the study id and manual annotation of the said 687 reports?
Thanks!
In the paper, it is mentioned that the input token size is limited to 512 tokens, but it can be easily extended to work with longer reports. I was wondering how this would be done? Thanks.
Hi,
Assuming I own a NLP labeling function and I want to compare the performance of my model to CheXbert. Is there a way to get access to this CheXpert reports dataset?
All The Best,
Impression section has some problems that cannot be solved
Hello,
I'm trying to build the environment from the environment.yml you have in the repo but I'm getting the following.
Collecting package metadata (repodata.json): done
Solving environment: failed
ResolvePackageNotFound:
- pyzmq==18.1.1=py37he6710b0_0
- libgcc-ng==9.1.0=hdf63c60_0
- glib==2.63.1=h5a9c865_0
- gst-plugins-base==1.14.0=hbbd80ab_1
...
I think this is due to the fact that if they don't already exist in the conda environment ResolvePackageNotFound will throw this error similar to this post
I'm thinking you might need to move all dependancies to the pip section but I'm not positive. I'm attempting to setup on MacOS
Thanks,
Ryan
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