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Expert System Design to Predict Heart and Diabetes Diseases


Affiliations
1 Department of Computer Science and Engineering, Sjce, Mysore, India
 

The Objective of this paper is to design an expert system that predicts the heart disease and diabetes disease with reduced number of attribute using data mining technique. Classification of knowledge objects is a knowledge mining and knowledge management process used in grouping similar knowledge objects together. There are plenty of classification algorithms available in literature but decision tree is the most often used because of its ease of implementation and simpler to understand, when compared to other classification algorithms. There are many classifiers but we have used C4.5 for more accuracy and less run time. The decision tree algorithm has been applied on the knowledge of heart and diabetes disease to foretell whether diseases present or not. The Simulation result obtained from the model enables us to establish significant patterns and relationships between the medical factors and clinical factors.

Keywords

Data Mining, Artificial Intelligence, Decision Tree, Heart Disease, Diabetes, Classification, C4.5 Algorithm.
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  • Expert System Design to Predict Heart and Diabetes Diseases

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Authors

Shravan Kumar Uppin
Department of Computer Science and Engineering, Sjce, Mysore, India
M. A. Anusuya
Department of Computer Science and Engineering, Sjce, Mysore, India

Abstract


The Objective of this paper is to design an expert system that predicts the heart disease and diabetes disease with reduced number of attribute using data mining technique. Classification of knowledge objects is a knowledge mining and knowledge management process used in grouping similar knowledge objects together. There are plenty of classification algorithms available in literature but decision tree is the most often used because of its ease of implementation and simpler to understand, when compared to other classification algorithms. There are many classifiers but we have used C4.5 for more accuracy and less run time. The decision tree algorithm has been applied on the knowledge of heart and diabetes disease to foretell whether diseases present or not. The Simulation result obtained from the model enables us to establish significant patterns and relationships between the medical factors and clinical factors.

Keywords


Data Mining, Artificial Intelligence, Decision Tree, Heart Disease, Diabetes, Classification, C4.5 Algorithm.