Cohort selection for clinical trials using deep learning models

Segura-Bedmar, Isabel; Ráez, Pablo

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Cohort selection for clinical trials using deep learning models

Author(s): Segura-Bedmar, Isabel; Ráez, Pablo

Publisher: Oxford University Press

Issued date: 2019-11-01

Citation: 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.

ISSN: 1067-5027

DOI: https://doi.org/10.1093/jamia/ocz139

xmlui.dri2xhtml.METS-1.0.item-contributor-funder: Ministerio de Economía y Competitividad (España)

Sponsor: 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).

Project: Gobierno de España. TIN2017-87548-C2-1-R

Keywords: Cohort selection , Convolutional neural network , Deep learning , Multilabel text classification , Recurrent neural network

URI: http://hdl.handle.net/10016/31254

Rights: Copyright © The Author(s) 2019.
Atribución-NoComercial-SinDerivadas 3.0 España

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 de [+]

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