title: Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments.
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%.
authors.affiliation: Biomedical Informatics Department, Arizona State University, Phoenix, AZ, USA.
authors.forename: Azadeh
authors.initials: A
authors.lastname: Nikfarjam
authors.forename: Graciela H
authors.initials: GH
authors.lastname: Gonzalez
mesh_terms: D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*