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...

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Detalles Bibliográficos
Autores principales: Chang, David, Hong, Woo Suk, Taylor, Richard Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Brief Communications
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

Internet

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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