Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

The Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) is a heterogeneous knowledge network that integrates information from 29 public databases. Here, Nelson et al. extend SPOKE to embed clinical data from electronic health records to create medically meaningful barcodes for each medical...

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Detalles Bibliográficos
Autores principales:	Charlotte A. Nelson, Atul J. Butte, Sergio E. Baranzini
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/ec5f2e03ddca4481a742ae0cece62da4
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ec5f2e03ddca4481a742ae0cece62da4
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spelling	oai:doaj.org-article:ec5f2e03ddca4481a742ae0cece62da42021-12-02T16:57:31ZIntegrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings10.1038/s41467-019-11069-02041-1723https://doaj.org/article/ec5f2e03ddca4481a742ae0cece62da42019-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-11069-0https://doaj.org/toc/2041-1723The Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) is a heterogeneous knowledge network that integrates information from 29 public databases. Here, Nelson et al. extend SPOKE to embed clinical data from electronic health records to create medically meaningful barcodes for each medical variable.Charlotte A. NelsonAtul J. ButteSergio E. BaranziniNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-10 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Charlotte A. Nelson Atul J. Butte Sergio E. Baranzini Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
description	The Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) is a heterogeneous knowledge network that integrates information from 29 public databases. Here, Nelson et al. extend SPOKE to embed clinical data from electronic health records to create medically meaningful barcodes for each medical variable.
format	article
author	Charlotte A. Nelson Atul J. Butte Sergio E. Baranzini
author_facet	Charlotte A. Nelson Atul J. Butte Sergio E. Baranzini
author_sort	Charlotte A. Nelson
title	Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
title_short	Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
title_full	Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
title_fullStr	Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
title_full_unstemmed	Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
title_sort	integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/ec5f2e03ddca4481a742ae0cece62da4
work_keys_str_mv	AT charlotteanelson integratingbiomedicalresearchandelectronichealthrecordstocreateknowledgebasedbiologicallymeaningfulmachinereadableembeddings AT atuljbutte integratingbiomedicalresearchandelectronichealthrecordstocreateknowledgebasedbiologicallymeaningfulmachinereadableembeddings AT sergioebaranzini integratingbiomedicalresearchandelectronichealthrecordstocreateknowledgebasedbiologicallymeaningfulmachinereadableembeddings
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Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings

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