Abstract
This is a general method that combines the soft computing techniques like genetic algorithms and fuzzy rule based expert system for effective heart disease diagnosis. It is very important to diagnose the disease in the early stage itself. Prompt and correct diagnosis of the disease by selecting the important and relevant features will help to discard irrelevant and unimportant ones. Genetic algorithms help in feature subset selection. After the subset selection the fuzzy rule based expert system provides the classificatory knowledge. The proposed system generates the rules from the instances and narrows down the limit of the rules using degree of the memberships. The system is designed in Matlab software. The system can be viewed as an alternative method for effective diagnosis of heart disease presence.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Ephzibah, E.P., Sundarapandian, V. (2012). A Fuzzy Rule Based Expert System for Effective Heart Disease Diagnosis. In: Meghanathan, N., Chaki, N., Nagamalai, D. (eds) Advances in Computer Science and Information Technology. Computer Science and Engineering. CCSIT 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 85. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27308-7_20
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DOI: https://doi.org/10.1007/978-3-642-27308-7_20
Publisher Name: Springer, Berlin, Heidelberg
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