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...

Description complète

Enregistré dans:
Détails bibliographiques
Publié dans:JAMIA Open
Auteurs principaux: Geva, Alon, Stedman, Jason P, Manzi, Shannon F, Lin, Chen, Savova, Guergana K, Avillach, Paul, Mandl, Kenneth D
Format: Artigo
Langue:Inglês
Publié: Oxford University Press 2020
Sujets:
Research and Applications
Accès en ligne: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
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires