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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...
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| Published in: | JAMIA Open |
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| Main Authors: | , , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
Oxford University Press
2020
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7382638/ https://ncbi.nlm.nih.gov/pubmed/32734154 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooaa022 |
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