Ontology-driven weak supervision for clinical entity classification in electronic health records

In the electronic health record, using clinical notes to identify entities such as disorders and their temporality can inform many important analyses. Here, the authors present a framework for weakly supervised entity classification using medical ontologies and expert-generated rules.

Guardado en:

Detalles Bibliográficos
Autores principales:	Jason A. Fries, Ethan Steinberg, Saelig Khattar, Scott L. Fleming, Jose Posada, Alison Callahan, Nigam H. Shah
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/2f95d01741cc4c879cc47cb28144da3f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:2f95d01741cc4c879cc47cb28144da3f
record_format	dspace
spelling	oai:doaj.org-article:2f95d01741cc4c879cc47cb28144da3f2021-12-02T18:17:51ZOntology-driven weak supervision for clinical entity classification in electronic health records10.1038/s41467-021-22328-42041-1723https://doaj.org/article/2f95d01741cc4c879cc47cb28144da3f2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-22328-4https://doaj.org/toc/2041-1723In the electronic health record, using clinical notes to identify entities such as disorders and their temporality can inform many important analyses. Here, the authors present a framework for weakly supervised entity classification using medical ontologies and expert-generated rules.Jason A. FriesEthan SteinbergSaelig KhattarScott L. FlemingJose PosadaAlison CallahanNigam H. ShahNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jason A. Fries Ethan Steinberg Saelig Khattar Scott L. Fleming Jose Posada Alison Callahan Nigam H. Shah Ontology-driven weak supervision for clinical entity classification in electronic health records
description	In the electronic health record, using clinical notes to identify entities such as disorders and their temporality can inform many important analyses. Here, the authors present a framework for weakly supervised entity classification using medical ontologies and expert-generated rules.
format	article
author	Jason A. Fries Ethan Steinberg Saelig Khattar Scott L. Fleming Jose Posada Alison Callahan Nigam H. Shah
author_facet	Jason A. Fries Ethan Steinberg Saelig Khattar Scott L. Fleming Jose Posada Alison Callahan Nigam H. Shah
author_sort	Jason A. Fries
title	Ontology-driven weak supervision for clinical entity classification in electronic health records
title_short	Ontology-driven weak supervision for clinical entity classification in electronic health records
title_full	Ontology-driven weak supervision for clinical entity classification in electronic health records
title_fullStr	Ontology-driven weak supervision for clinical entity classification in electronic health records
title_full_unstemmed	Ontology-driven weak supervision for clinical entity classification in electronic health records
title_sort	ontology-driven weak supervision for clinical entity classification in electronic health records
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2f95d01741cc4c879cc47cb28144da3f
work_keys_str_mv	AT jasonafries ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT ethansteinberg ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT saeligkhattar ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT scottlfleming ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT joseposada ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT alisoncallahan ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords AT nigamhshah ontologydrivenweaksupervisionforclinicalentityclassificationinelectronichealthrecords
_version_	1718378265268191232

Ontology-driven weak supervision for clinical entity classification in electronic health records

Ejemplares similares