Analysis of adverse reaction associated with dietary drug Orlistat using data mining algorithms

Abstract

Orlistat is a drug given for obesity and treat overweight children and adults. The aim of this work is to analyze the adverse reactions of the drug orlistat from the information available in Adverse Events Reporting System(AERS) using WEKA. The Hoeffding tree algorithm is the best method for inducing decision trees from continuous data streams using Hoeffding bounds and enhanced Hoeffding tree has been developed for analyzing and extracting information from the huge AERS database. The results obtained proved that frequent adverse effects like gastrointestinal disorders, respiratory infections etc were reported at alarming rate.