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Generating contextual embeddings for emergency department chief complaints
OBJECTIVE: We learn contextual embeddings for emergency department (ED) chief complaints using Bidirectional Encoder Representations from Transformers (BERT), a state-of-the-art language model, to derive a compact and computationally useful representation for free-text chief complaints. MATERIALS AN...
Autores principales: | Chang, David, Hong, Woo Suk, Taylor, Richard Andrew |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382638/ https://www.ncbi.nlm.nih.gov/pubmed/32734154 http://dx.doi.org/10.1093/jamiaopen/ooaa022 |
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