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Item

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Agent based Enterological Disease Diagnosis System

http://hdl.handle.net/20.500.12678/0000004015
dce682c4-bfd2-4e6b-855f-f05e8badbdb2
b1704bab-fbb5-4012-8628-0ea2c0086f2f
None
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55126.pdf 55126.pdf (702 Kb)
Publication type
Article
Upload type
Publication
Title
Title Agent based Enterological Disease Diagnosis System
Language en
Publication date 2009-12-30
Authors
Oo, Kyaw Khaing
Description
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.
Keywords
Enterological Disease, Expert System, Decision Tree Induction, ID3
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1726
Journal articles
Fourth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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