title: Grouping the pharmacovigilance terms with a hybrid approach.
abstract: Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs. It leads to the safety survey of pharmaceutical products. The pharmacovigilance process benefits from the traditional statistical approaches and also from the qualitative information on semantic relations between close ADR terms, such as SMQs or hierarchical levels of MedDRA. In this work, our objective is to detect the semantic relatedness between the ADR MedDRA terms. To achieve this, we combine two approaches: semantic similarity algorithms computed within structured resources and terminology structuring methods applied to a raw list of the MedDRA terms. We compare these methods between them and study their differences and complementarity. The results are evaluated against the gold standard manually compiled within the pharmacovigilance area and also with an expert. The combination of the methods leads to an improved recall.
authors.affiliation: Université Lille, France.
authors.forename: Marie
authors.initials: M
authors.lastname: Dupuch
authors.forename: Laëtitia
authors.initials: L
authors.lastname: Dupuch
authors.forename: Amandine
authors.initials: A
authors.lastname: Perinet
authors.forename: Thierry
authors.initials: T
authors.lastname: Hamon
authors.forename: Natalia
authors.initials: N
authors.lastname: Grabar
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D001185:Artificial Intelligence; D003628:Database Management Systems; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D005602:France / Q000453:epidemiology; D006801:Humans; D009323:Natural Language Processing; D060735:Pharmacovigilance; D018875:Vocabulary, Controlled