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ADRTrace: Detecting Expected and Unexpected Adverse Drug Reactions from User Reviews on Social Media Sites

  • Andrew Yates
  • Nazli Goharian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7814)

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.

Keywords

Unify Medical Language System User Review Drug Review Breast Cancer Drug Adverse Drug Reac 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andrew Yates
    • 1
  • Nazli Goharian
    • 1
  1. 1.Information Retrieval Laboratory, Department of Computer ScienceGeorgetown UniversityUSA

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