Publication | Open Access
Pattern mining for extraction of mentions of Adverse Drug Reactions from user comments.
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Citations
11
References
2011
Year
EngineeringPattern DiscoveryPattern MiningAssociation Rule MiningDrug ClassCorpus LinguisticsText MiningAdverse Drug ReactionNatural Language ProcessingDrug HypersensitivityInformation RetrievalData ScienceData MiningAdverse EffectsToxicologyBiomedical Text MiningSocial Medium MiningKnowledge DiscoveryInformation ExtractionPharmacologyAdverse Drug ReactionsUser CommentsSocial Medium DataMedicineHealth InformaticsDrug Discovery
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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