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covid-radbert
StanfordAIMI/covid-radbert
covid-radbert is a text classification model from StanfordAIMI. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
COVID-RadBERT was trained to detect the presence or absence of COVID-19 within radiology reports, along an "uncertain" diagnostic when further medical tests are required.
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1.3 GB
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.bin433 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jul 19, 2022
- Updated
- Nov 19, 2022
- SHA
- 2be22e44
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Model card
From the Hugging Face model README
COVID-RadBERT was trained to detect the presence or absence of COVID-19 within radiology reports, along an "uncertain" diagnostic when further medical tests are required.
Citation
@article{chambon_cook_langlotz_2022,
title={Improved fine-tuning of in-domain transformer model for inferring COVID-19 presence in multi-institutional radiology reports},
DOI={10.1007/s10278-022-00714-8}, journal={Journal of Digital Imaging},
author={Chambon, Pierre and Cook, Tessa S. and Langlotz, Curtis P.},
year={2022}
}
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Jul 19, 2022
- Updated
- Nov 19, 2022