Semantic processing to identify adverse drug event information from black box warnings
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Updated: May 2, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Adam Culbertson1, Marcelo Fiszman1, Dongwook Shin1
1Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD.
Abstract:
We utilized a semantic natural language processing approach to extract adverse drug event information from FDA black box warnings. Overall performance was 90% precision, 51% recall, and 0.65 F-Score. Information extracted can be stored in a structured format and may be useful to support clinical decision support systems.
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