Abstract
We automatically extract adverse drug reactions (ADRs) from consumer reviews provided on various drug social media sites to identify adverse reactions not reported by the United States Food and Drug Administration (FDA) but touted by consumers. We utilize various lexicons, identify patterns, and generate a synonym set that includes variations of medical terms. We identify “expected” and “unexpected” ADRs. Background (drug) language is utilized to evaluate the strength of the detected unexpected ADRs. Evaluation results for our synonym set and ADR extraction are promising.
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Yates, A., Goharian, N. (2013). ADRTrace: Detecting Expected and Unexpected Adverse Drug Reactions from User Reviews on Social Media Sites. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_92
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DOI: https://doi.org/10.1007/978-3-642-36973-5_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36972-8
Online ISBN: 978-3-642-36973-5
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