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Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features
2015
JAMIA Journal of the American Medical Informatics Association
Objective Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques. However, the language in social media is highly informal, and userexpressed medical concepts are often nontechnical, descriptive, and challenging to extract. There has been limited progress in addressing these
doi:10.1093/jamia/ocu041
pmid:25755127
pmcid:PMC4457113
fatcat:wrekcivgkrf3rbbgl5mdym2c4y