Adverse drug event detection using natural language processing: A scoping review of supervised learning methods

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results for the purpose of ADE detection in the context of...

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Veröffentlicht in:	PloS one Jg. 18; H. 1; S. e0279842
Hauptverfasser:	Murphy, Rachel M., Klopotowska, Joanna E., de Keizer, Nicolette F., Jager, Kitty J., Leopold, Jan Hendrik, Dongelmans, Dave A., Abu-Hanna, Ameen, Schut, Martijn C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 03.01.2023 Public Library of Science (PLoS)
Schlagworte:	Adverse and side effects Annotations Artificial intelligence Automation Best practice Biology and Life Sciences Computational linguistics Computer and Information Sciences Computer science Conditional random fields Content analysis Context Drug-Related Side Effects and Adverse Reactions Drugs Electronic Health Records Electronic medical records Evaluation Hospitalization Hospitals Humans Information sources Language Language processing Long short-term memory Medicine and Health Sciences Monitoring Narratives Natural language interfaces Natural Language Processing Patient safety Performance prediction Pharmacovigilance Primary care Qualitative analysis Social Sciences Supervised learning Supervised Machine Learning Netherlands
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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