Searching Adverse Drug Reaction Signal Pairs Using Mining Association

In this paper, propose an innovative data mining framework and apply it to mine potential causal associations in electronic patient data sets where the drug-related events of interest occur infrequently.Specifically, created a novel interestingness measure, exclusive causal-leverage, based on a computational, fuzzy recognition-primed decision (RPD) model that we previously developed. On the basis of this new measure, a data mining algorithm was developed to mine the causal relationship between drugs and their associated adverse drug reactions (ADRs). The exclusive causal-leverage was employed to rank the potential causal associations between each of the selected drugs. Algorithm could effectively make known ADRs rank high among all the symptoms in the database.