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Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we present a new set of embeddings for medical concepts learned using an extremely large collection of multimodal medical data. Leaning on recen...
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| Publicado no: | Pac Symp Biocomput |
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| Main Authors: | , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6922053/ https://ncbi.nlm.nih.gov/pubmed/31797605 |
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