Discovering associations between adverse drug events using pattern structures and ontologies

Gabin Personeni 1, 2 Emmanuel Bresso 1 Marie-Dominique Devignes 2 Michel Dumontier 3, 4 Malika Smaïl-Tabbone 1 Adrien Coulet 1, 3
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 CAPSID - Computational Algorithms for Protein Structures and Interactions
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
3 BMIR - Stanford Center for BioMedical Informatics Research
4 Institute of Data Science, Maastricht University
Abstract : Background: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgroups of patients. Results: Because ADEs have complex manifestations, we use formal concept analysis and its pattern structures, a mathematical framework that allows generalization using domain knowledge formalized in medical ontologies. Results obtained with three different settings and two different datasets show that this approach is flexible and allows extraction of association rules at various levels of generalization. Conclusions: The chosen approach permits an expressive representation of a patient ADEs. Extracted association rules point to distinct ADEs that occur in a same group of patients, and could serve as a basis for a recommandation system. The proposed representation is flexible and can be extended to make use of additional ontologies and various patient records.
Keywords : Ontologies Association rules Adverse drug event Pharmacovigilance Patient data Pattern structures
Type de document :
Article dans une revue
Journal of Biomedical Semantics, BioMed Central, 2017, 93, pp.539 - 546. 〈10.1186/s13326-017-0137-x〉
Liste complète des métadonnées

Littérature citée [20 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01576341
Contributeur : Adrien Coulet <>
Soumis le : mardi 22 août 2017 - 22:59:06
Dernière modification le : samedi 24 février 2018 - 01:23:40

Fichier

s13326-017-0137-x.pdf
Fichiers éditeurs autorisés sur une archive ouverte

Identifiants

Collections

UNIV-LORRAINE | LORIA | LORIA-NLPKD | LORIA-AIS | INRIA2017 | INRIA

Citation

Gabin Personeni, Emmanuel Bresso, Marie-Dominique Devignes, Michel Dumontier, Malika Smaïl-Tabbone, et al.. Discovering associations between adverse drug events using pattern structures and ontologies. Journal of Biomedical Semantics, BioMed Central, 2017, 93, pp.539 - 546. 〈10.1186/s13326-017-0137-x〉. 〈hal-01576341〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

297

Téléchargements de fichiers

54

Contact


archive-ouverte@inria.fr