Utilizing text mining on online medical forums to predict label change due to adverse drug reactions

Ronen Feldman, Oded Netzer, Aviv Peretz*, Binyamin Rosenfeld

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

We present an end-to-end text mining methodology for relation extraction of adverse drug reactions (ADRs) from medical forums on the Web. Our methodology is novel in that it combines three major characteristics: (i) an underlying concept of using a head-driven phrase structure grammar (HPSG) based parser; (ii) domain-specific relation patterns, the acquisition of which is done primarily using unsupervised methods applied to a large, unlabeled text corpus; and (iii) automated post-processing algorithms for enhancing the set of extracted relations. We empirically demonstrate the ability of our proposed approach to predict ADRs prior to their reporting by the Food and Drug Administration (FDA). Put differently, we put our approach to a predictive test by demonstrating that our methodology can credibly point to ADRs that were not uncovered in clinical trials for evaluating new drugs that come to market but were only reported later on by the FDA as a label change.

Original languageEnglish
Title of host publicationKDD 2015 - Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
PublisherAssociation for Computing Machinery
Pages1779-1788
Number of pages10
ISBN (Electronic)9781450336642
DOIs
StatePublished - 10 Aug 2015
Event21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2015 - Sydney, Australia
Duration: 10 Aug 201513 Aug 2015

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Volume2015-August

Conference

Conference21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2015
Country/TerritoryAustralia
CitySydney
Period10/08/1513/08/15

Bibliographical note

Publisher Copyright:
© 2015 ACM.

Keywords

  • Adverse drug reactions
  • Hpsg
  • Medical forums
  • Pharmaceutical drugs
  • Text mining

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