RadBERT was continuously pre-trained on radiology reports from a BioBERT initialization.
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}
}
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RadBERT huggingface.co is an AI model on huggingface.co that provides RadBERT's model effect (), which can be used instantly with this StanfordAIMI RadBERT model. huggingface.co supports a free trial of the RadBERT model, and also provides paid use of the RadBERT. Support call RadBERT model through api, including Node.js, Python, http.
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