A clinical specific BERT developed using a huge Japanese clinical text corpus

Generalized language models that are pre-trained with a large corpus have achieved great performance on natural language tasks. While many pre-trained transformers for English are published, few models are available for Japanese text, especially in clinical medicine. In this work, we demonstrate the...

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Detalles Bibliográficos
Autores principales: Kawazoe, Yoshimasa, Shibata, Daisaku, Shinohara, Emiko, Aramaki, Eiji, Ohe, Kazuhiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577751/
https://www.ncbi.nlm.nih.gov/pubmed/34752490
http://dx.doi.org/10.1371/journal.pone.0259763

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8577751/
https://www.ncbi.nlm.nih.gov/pubmed/34752490
http://dx.doi.org/10.1371/journal.pone.0259763

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