Name
Abstract | ||
|---|---|---|
In the context of PROTECT European project, we have developed an ontology of adverse drug reactions (OntoADR) based on the original MedDRA hierarchy and a query-based method to achieve automatic MedDRA terms groupings for improving pharmacovigilance signal detection. Those groupings were evaluated against standard handmade MedDRA groupings corresponding to first priority pharmacovigilance safety topics. Our results demonstrate that this automatic method allows catching most of the terms present in the reference groupings, and suggest that it could offer an important saving of time for the achievement of pharmacovigilance groupings. This paper describes the theoretical context of this work, the evaluation methodology, and presents the principal results. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3233/978-1-61499-101-4-73 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Pharmacovigilance,knowledge engineering,ontology,MedDRA terminology,SMQ,semantic reasoning. | Data mining,Ontology,MedDRA,Information retrieval,Mandatory reporting,Natural language processing,Artificial intelligence,Pharmacovigilance,Hierarchy,Medicine | Conference |
Volume | ISSN | Citations |
180 | 0926-9630 | 4 |
PageRank | References | Authors |
0.46 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gunnar Declerck | 1 | 11 | 5.00 |
| Cédric Bousquet | 2 | 109 | 22.59 |
| Marie-Christine Jaulent | 3 | 375 | 68.72 |