Causal Association Mining for Detection of Adverse Drug Reactions

Adverse drug reactions (ADRs) are the harmful reactions of the drugs caused to humans due to allergies, overdose, chemical reactions between two chemicals in the medicines, etc. To reduce these reactions is a very important task so as to save lives of the patients as ADRs are a serious topic nowadays [4]. Detecting such harmful effects as early as possible is a very important to prevent harmful consequences. Therefore, mining causal relationships between the drug related events is essential. A method for detecting the potential relationship between drug and ICD is done using causal association rules suitable for the frequent events[1]. Sometimes an infrequent nature of the drugs can cause tremendous harm especially in case of Type-2 diabetes. A new interestingness measure called as exclusive causal leverage can be used based on fuzzy Recognition Primed Decision model (RPD) [3]. On the basis of this measure the relationship between the drug and associated drug reactions can be mined.