Development of an adverse drug reaction corpus from consumer health posts

Maryam Zolnoori, Timothy B. Patrick, Kin Wah Fung, Paul Fontelo, Anthony Faiola, Yi Shuan Shirley Wu, Kelly Xu, Jiaxi Zhu, Christina E. Eldredge

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


UWM-Adverse Drug Events Corpus (UWM-ADEC) is an annotated corpus that has been developed from consumer drug review posts in social media. In this corpus, we identified four types of Adverse Drug Reactions (ADRs) including physiological, psychological, cognitive, and functional problems. Additionally, we mapped the ADRs to corresponding concepts in Unified medical language Systems (UMLS). The quality of the corpus was measured using well-defined guidelines, double coding, high inter-annotator agreement, and final reviews by pharmacists and clinical terminologists. This corpus is a valuable source for research in the area of text mining and machine learning for ADRs identifications from consumer health posts, specifically for psychiatric medications.

Original languageEnglish
Pages (from-to)19-26
Number of pages8
JournalCEUR Workshop Proceedings
StatePublished - 2017
Event2nd Social Media Mining for Health Research and Applications Workshop, SMM4H 2017 - Washington, United States
Duration: Nov 4 2017 → …

ASJC Scopus subject areas

  • General Computer Science


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