Conference Proceedings

Refining Adverse Drug Reactions using Association Rule Mining for Electronic Healthcare Data

Jenna M Reps, Uwe Aickelin, Jiangang Ma, Yanchun Zhang

2014 IEEE International Conference on Data Mining Workshop | IEEE | Published : 2014


Side effects of prescribed medications are a common occurrence. Electronic healthcare databases present the opportunity to identify new side effects efficiently but currently the methods are limited due to confounding (i.e. when an association between two variables is identified due to them both being associated to a third variable). In this paper we propose a proof of concept method that learns common associations and uses this knowledge to automatically refine side effect signals (i.e. exposure-outcome associations) by removing instances of the exposure-outcome associations that are caused by confounding. This leaves the signal instances that are most likely to correspond to true side ..

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University of Melbourne Researchers