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Automatic creation and refinement of the clusters of pharmacovigilance terms

Published: 28 January 2012 Publication History

Abstract

Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs or biologics. The detection of adverse drug reactions is performed thanks to statistical algorithms and to groupings of ADR terms. Standardized MedDRA Queries (SMQs) are the groupings which become a standard for assisting the retrieval and evaluation of MedDRA-coded ADR reports all through the world. Currently 84 SMQs have been created manually by experts, while several important safety topics are not yet covered. Dependent on the context of their application, these SMQs show a high degree of sensitivity and often appear to be over-inclusive. For pharmacovigilance experts it represents an important and tedious filtering of data. The objective of this work is to propose an automatic method for assisting the creation of SMQs and also for the refinement of their organization further to the creation of smaller clusters of ADR terms. In this work we propose to exploit the semantic distance and clustering approaches. We perform several experiments and vary several parameters of the method.

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Cited By

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  • (2018)Semantic distance-based creation of clusters of pharmacovigilance terms and their evaluationJournal of Biomedical Informatics10.1016/j.jbi.2014.11.00754:C(174-185)Online publication date: 27-Dec-2018
  • (2013)Comparison of Clustering Approaches through Their Application to Pharmacovigilance TermsArtificial Intelligence in Medicine10.1007/978-3-642-38326-7_9(58-67)Online publication date: 2013

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cover image ACM Conferences
IHI '12: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
January 2012
914 pages
ISBN:9781450307819
DOI:10.1145/2110363
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 28 January 2012

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Author Tags

  1. clustering of terms
  2. meddra
  3. pharmacovigilance
  4. semantic distance

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IHI '12
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IHI '12: ACM International Health Informatics Symposium
January 28 - 30, 2012
Florida, Miami, USA

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Cited By

View all
  • (2018)Semantic distance-based creation of clusters of pharmacovigilance terms and their evaluationJournal of Biomedical Informatics10.1016/j.jbi.2014.11.00754:C(174-185)Online publication date: 27-Dec-2018
  • (2013)Comparison of Clustering Approaches through Their Application to Pharmacovigilance TermsArtificial Intelligence in Medicine10.1007/978-3-642-38326-7_9(58-67)Online publication date: 2013

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