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

Azadeh Nikfarjam, Graciela H. Gonzalez

    Research output: Contribution to journalArticle

    81 Scopus citations

    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

    ASJC Scopus subject areas

    • Medicine(all)

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