Agent based Enterological Disease Diagnosis System

Abstract

Decision tree learning algorithm is rules for classifying data using attributes and has been successfully used in decision support systems in capturing knowledge. The main task performed in this paper is using inductive methods to the given values of attributes of object to determine appropriate classification according to decision tree rules. Decision tree is mainly used for classification purposes. Decision tree is a classifier in the form of a tree structure. Rules can be easily extracted from the decision tree. This system acquires knowledge from the domain expert who has the special knowledge. System receives symptoms from the users and decides related disease. During these operations, this system uses agents capabilities. Agent can do different services: classification and testing. This system is used the symptoms to classify the disease with the help of ID3 algorithm. It will provide the accurate result to patients by combining the Lab results.