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Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs)
We propose to use segment graph convolutional and recurrent neural networks (Seg-GCRNs), which use only word embedding and sentence syntactic dependencies, to classify relations from clinical notes without manual feature engineering. In this study, the relations between 2 medical concepts are classi...
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| Publicado no: | J Am Med Inform Assoc |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Oxford University Press
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6351971/ https://ncbi.nlm.nih.gov/pubmed/30590613 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocy157 |
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