Grouping pharmacovigilance terms with semantic distance

被引：4

作者：

Dupuch, Marie ^{[1
,2
]}

Lerch, Magnus ^{[3
]}

Jamet, Anne ^{[2
,4
]}

Jaulent, Marie-Christine ^{[1
,2
]}

Fescharek, Reinhard ^{[5
]}

Grabar, Natalia ^{[6
]}

机构：

[1] Univ Paris 06, F-75006 Paris, France

[2] INSERM, U872, Paris, France

[3] Consulting Coaching, Berlin, Germany

[4] HEGP, Paris, France

[5] CSL Behring GmbH, Marburg, Germany

[6] Univ Lille, CNRS UMR 8163 STL, Lille, France

来源：

USER CENTRED NETWORKED HEALTH CARE | 2011年 / 169卷

关键词：

Natural Language Processing; Medical informatics; Drug safety; Pharmacovigilance; Signal detection; Drug toxicity; Semantics; Terminology; SIGNAL GENERATION; MEDDRA;

D O I：

10.3233/978-1-60750-806-9-794

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs or biologics. Besides other methods, statistical algorithms are used to detect previously unknown ADRs, and it was noted that groupings of ADR terms can further improve safety signal detection. Standardised MedDRA Queries are developed to assist retrieval and evaluation of MedDRA-coded ADR reports. Dependent on the context of their application, different SMQs show varying degrees of specificity and sensitivity; some appear to be over-inclusive, some might miss relevant terms. Moreover, several important safety topics are not yet fully covered by SMQs. The objective of this work is to propose an automatic method for the creation of groupings of terms. This method is based on the application of the semantic distance between MedDRA terms. Several experiments are performed, showing a promising precision and an acceptable recall.

引用

页码：794 / 798

页数：5

共 18 条

[1] Measuring Semantic Similarity Between Biomedical Concepts Within Multiple Ontologies [J].