Detecting Adverse Drug Reactions Using Utility Pattern Growth and Mining Infrequent Casual Association

Abstract

The most important issues in drug safety is Adverse Drug Reaction (ADR). Many adverse drug reactions are not discovered during less pre marketing clinical trials. It is observed that the usage of drug after long term post marketing surveillance of drug. There are many adverse events that is used in the development of statistical in the detection of ADRs. In this proposed system an interactive system platform is introduced for detecting ADRs. An ADR data warehouse and innovative data mining techniques are integrated, the proposed system not only supports OLAP style multidimensional analysis of ADRs, it is also used in the discovery of associations between drugs, called a drug ADR association rule.