Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments

Rapid growth of online health social networks has enabled patients to communicate more easily with each other. This way of exchange of opinions and experiences has provided a rich source of information about drugs and their effectiveness and more importantly, their possible adverse reactions. We dev...

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Bibliographic Details
Published in:AMIA ... Annual Symposium proceedings 2011, Vol.2011, p.1019-1026
Main Authors: Nikfarjam, Azadeh, Gonzalez, Graciela H
Format: Article
Language:English
Subjects:
Algorithms
Data Mining - methods
Drug-Related Side Effects and Adverse Reactions
Humans
Natural Language Processing
Pattern Recognition, Automated - methods
Online Access:Get full text
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Summary:Rapid growth of online health social networks has enabled patients to communicate more easily with each other. This way of exchange of opinions and experiences has provided a rich source of information about drugs and their effectiveness and more importantly, their possible adverse reactions. We developed a system to automatically extract mentions of Adverse Drug Reactions (ADRs) from user reviews about drugs in social network websites by mining a set of language patterns. The system applied association rule mining on a set of annotated comments to extract the underlying patterns of colloquial expressions about adverse effects. The patterns were tested on a set of unseen comments to evaluate their performance. We reached to precision of 70.01% and recall of 66.32% and F-measure of 67.96%.
ISSN:1559-4076