Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.

Journal: Journal of the American Medical Informatics Association : JAMIA

Published Date: Jan 1, 2020

Abstract

OBJECTIVE: Identification of drugs, associated medication entities, and interactions among them are crucial to prevent unwanted effects of drug therapy, known as adverse drug events. This article describes our participation to the n2c2 shared-task in extracting relations between medication-related entities in electronic health records.

Authors

Fenia Christopoulou

National Centre for Text Mining, School of Computer Science, The University of Manchester, Manchester, United Kingdom.
Thy Thy Tran

National Centre for Text Mining, School of Computer Science, The University of Manchester, Manchester, United Kingdom.
Sunil Kumar Sahu

Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, India.
Makoto Miwa
Sophia Ananiadou

Keywords

Deep Learning Drug Interactions Drug-Related Side Effects and Adverse Reactions Electronic Health Records Humans Information Storage and Retrieval Natural Language Processing Neural Networks, Computer

External Resources

View on PubMed Access via DOI PubMed (31390003)

Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.

Abstract

Authors

Keywords

External Resources

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