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Adverse drug event presentation and tracking (ADEPT): semiautomated, high throughput pharmacovigilance using real-world data

OBJECTIVE: To advance use of real-world data (RWD) for pharmacovigilance, we sought to integrate a high-sensitivity natural language processing (NLP) pipeline for detecting potential adverse drug events (ADEs) with easily interpretable output for high-efficiency human review and adjudication of true...

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Bibliographic Details
Published in:JAMIA Open
Main Authors: Geva, Alon, Stedman, Jason P, Manzi, Shannon F, Lin, Chen, Savova, Guergana K, Avillach, Paul, Mandl, Kenneth D
Format: Artigo
Language:Inglês
Published: Oxford University Press 2020
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Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC7660953/
https://ncbi.nlm.nih.gov/pubmed/33215076
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamiaopen/ooaa031
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