Attributes for causal inference in electronic healthcare databases

Jenna Reps, Jonathan M. Garibaldi, Uwe Aickelin, Daniele Soria, Jack E. Gibson, Richard B. Hubbard

Research output: Journal PublicationArticlepeer-review

1 Citation (Scopus)


Side effects of prescription drugs present a serious issue. Existing algorithms that detect side effects generally require further analysis to confirm causality. In this paper we investigate attributes based on the Bradford-Hill causality criteria that could be used by a classifying algorithm to definitively identify side effects directly. We found that it would be advantageous to use attributes based on the association strength, temporality and specificity criteria.

Original languageEnglish
Article number6627871
Pages (from-to)548-549
Number of pages2
JournalProceedings of the IEEE Symposium on Computer-Based Medical Systems
Publication statusPublished - 2013
Externally publishedYes

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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