Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments
- PMID: 22195162
- PMCID: PMC3243273
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%.
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References
-
- Kongkaew C, Noyce PR, Ashcroft DM. Hospital admissions associated with adverse drug reactions: a systematic review of prospective observational studies. The Annals of pharmacotherapy. 2008;42(7):1017–25. - PubMed
-
- Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. Jama. 1998;279(15):1200. - PubMed
-
- Hooft CS van der, Sturkenboom MCJM, Grootheest K van, Kingma HJ, Stricker BHC. Adverse drug reaction-related hospitalisations: a nationwide study in The Netherlands. Drug Safety. 2006;29(2):161–168. - PubMed
-
- Leone R, Sottosanti L, Iorio ML, et al. Drug-related deaths: an analysis of the Italian spontaneous reporting database. Drug Safety. 2008;31(8):703–713. - PubMed
-
- Aramaki E, Miura Y, Tonoike M. Extraction of adverse drug effects from clinical records. Studies in health. 2010:739–743. - PubMed
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