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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Detalles Bibliográficos
Autores principales: Beam, Andrew L., Kompa, Benjamin, Schmaltz, Allen, Fried, Inbar, Weber, Griffin, Palmer, Nathan, Shi, Xu, Cai, Tianxi, Kohane, Isaac S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6922053/
https://www.ncbi.nlm.nih.gov/pubmed/31797605

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6922053/
https://www.ncbi.nlm.nih.gov/pubmed/31797605

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