Create README.md
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README.md
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# CORe Model - BioBERT + Clinical Outcome Pre-Training
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## Model description
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The CORe (_Clinical Outcome Representations_) model is introduced in the paper [Clinical Outcome Predictions from Admission Notes using Self-Supervised Knowledge Integration](https://www.aclweb.org/anthology/2021.eacl-main.75.pdf).
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It is based on BioBERT and further pre-trained on clinical notes, disease descriptions and medical articles with a specialised _Clinical Outcome Pre-Training_ objective.
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#### How to use
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You can load the model via the transformers library:
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```
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("bvanaken/CORe-clinical-outcome-biobert-v1")
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model = AutoModel.from_pretrained("bvanaken/CORe-clinical-outcome-biobert-v1")
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```
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### BibTeX entry and citation info
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```bibtex
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@inproceedings{vanaken21,
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author = {Betty van Aken and
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Jens-Michalis Papaioannou and
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Manuel Mayrdorfer and
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Klemens Budde and
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Felix A. Gers and
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Alexander Löser},
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title = {Clinical Outcome Prediction from Admission Notes using Self-Supervised
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Knowledge Integration},
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booktitle = {Proceedings of the 16th Conference of the European Chapter of the
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Association for Computational Linguistics: Main Volume, {EACL} 2021,
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Online, April 19 - 23, 2021},
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publisher = {Association for Computational Linguistics},
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year = {2021},
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}
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```
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