title: AERS spider: an online interactive tool to mine statistical associations in Adverse Event Reporting System.
abstract: BACKGROUND
  Exploration of the Adverse Event Reporting System (AERS) data by a wide scientific community is limited due to several factors. First, AERS data must be intensively preprocessed to be converted into analyzable format. Second, application of the currently accepted disproportional reporting measures results in false positive signals.
  
  
  METHODS
  We proposed a data mining strategy to improve hypothesis generation with respect to potential associations.
  
  
  RESULTS
  By numerous examples, we illustrate that our strategy controls the false positive signals. We implemented a free online tool, AERS spider (www.chemoprofiling.org/AERS).
  
  
  CONCLUSIONS
  We believe that AERS spider would be a valuable tool for drug safety experts.
authors.affiliation: Helmholtz Zentrum München GmbH, Department of Scientific Computing, Neuherberg, Germany.
authors.forename: Igor
authors.initials: I
authors.lastname: Grigoriev
authors.forename: Wolfgang
authors.initials: W
authors.lastname: zu Castell
authors.forename: Philipp
authors.initials: P
authors.lastname: Tsvetkov
authors.forename: Alexey V
authors.initials: AV
authors.lastname: Antonov
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems; D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual / Q000706:statistics & numerical data; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D009862:Online Systems; D017891:Pharmacoepidemiology / Q000379:methods; D014481:United States; D014486:United States Food and Drug Administration
keywords: AERS; FDA; data mining; pharmacoepidemiology; pharmacovigilance