Automated detection of altered mental status in emergency department clinical notes: a deep learning approach

Automated detection of altered mental status in emergency department clinical notes: a deep learning approach

Abstract Background Machine learning has been used extensively in clinical text classification tasks. Deep learning approaches using word embeddings have been recently gaining momentum in biomedical applications. In an effort to automate the identification of altered mental status (AMS) in emergency...

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Bibliographic Details
Main Authors: Jihad S. Obeid, Erin R. Weeda, Andrew J. Matuskowitz, Kevin Gagnon, Tami Crawford, Christine M. Carr, Lewis J. Frey
Format: Article
Language:English
Published: BMC 2019-08-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Altered mental status
Machine learning
Deep learning
Word embedding
Pulmonary embolism
Decision support
Online Access:http://link.springer.com/article/10.1186/s12911-019-0894-9

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http://link.springer.com/article/10.1186/s12911-019-0894-9

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