Cohort selection for clinical trials using deep learning models

Segura-Bedmar, Isabel; Ráez, Pablo

e-Archivo Home
→
Investigación
→
Departamentos
→
Departamento de Informática
→
Grupo Human Language and Accessibility Technologies (HULAT)
→
DI - LABDA - Artículos de Revistas
→
View Item

dc.contributor.author	Segura-Bedmar, Isabel
dc.contributor.author	Ráez, Pablo
dc.date.accessioned	2020-10-21T10:28:12Z
dc.date.available	2020-10-21T10:28:12Z
dc.date.issued	2019-11-01
dc.identifier.bibliographicCitation	Segura-Bedmar I, Raez P. Cohort selection for clinical trials using deep learning models. J Am Med Inform Assoc. 2019 Nov 1;26(11):1181-1188.
dc.identifier.issn	1067-5027
dc.identifier.uri	http://hdl.handle.net/10016/31254
dc.description.abstract	The goal of the 2018 n2c2 shared task on cohort selection for clinical trials (track 1) is to identify which patients meet the selection criteria for clinical trials. Cohort selection is a particularly demanding task to which natural language processing and deep learning can make a valuable contribution. Our goal is to evaluate several deep learning architectures to deal with this task.
dc.description.sponsorship	This work was supported by the Research Program of the Ministry of Economy and Competitiveness, Government of Spain, grant number TIN2017-87548-C2-1-R (DeepEMR project).
dc.language.iso	eng
dc.publisher	Oxford University Press
dc.rights	Copyright © The Author(s) 2019.
dc.rights	Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other	Cohort selection
dc.subject.other	Convolutional neural network
dc.subject.other	Deep learning
dc.subject.other	Multilabel text classification
dc.subject.other	Recurrent neural network
dc.title	Cohort selection for clinical trials using deep learning models
dc.type	article
dc.subject.eciencia	Informática
dc.identifier.doi	https://doi.org/10.1093/jamia/ocz139
dc.rights.accessRights	openAccess
dc.relation.projectID	Gobierno de España. TIN2017-87548-C2-1-R
dc.type.version	publishedVersion
dc.identifier.publicationfirstpage	1181
dc.identifier.publicationissue	11
dc.identifier.publicationlastpage	1188
dc.identifier.publicationtitle	JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
dc.identifier.publicationvolume	26
dc.identifier.uxxi	AR/0000023974
dc.contributor.funder	Ministerio de Economía y Competitividad (España)
dc.affiliation.dpto	UC3M. Departamento de Informática
dc.affiliation.grupoinv	UC3M. Grupo de Investigación: Human Language and Accessibility Technologies (HULAT)