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

Azadeh Nikfarjam, Graciela H. Gonzalez

Research output: Contribution to journalArticle

73 Citations (Scopus)

Abstract

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%.

Original languageEnglish (US)
Pages (from-to)1019-1026
Number of pages8
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume2011
StatePublished - 2011
Externally publishedYes

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Drug Users
Drug-Related Side Effects and Adverse Reactions
Social Support
Pharmaceutical Preparations
Language
Health
Growth

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments. / Nikfarjam, Azadeh; Gonzalez, Graciela H.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, Vol. 2011, 2011, p. 1019-1026.

Research output: Contribution to journalArticle

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