Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II

Research Article

A Fuzzy Rule Based Expert System for Effective Heart Disease Diagnosis

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  • @INPROCEEDINGS{10.1007/978-3-642-27308-7_20,
        author={E. Ephzibah and V. Sundarapandian},
        title={A Fuzzy Rule Based Expert System for Effective Heart Disease Diagnosis},
        proceedings={Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II},
        proceedings_a={CCSIT PATR II},
        year={2012},
        month={11},
        keywords={Fuzzy rule based Expert system genetic algorithm heart disease diagnosis},
        doi={10.1007/978-3-642-27308-7_20}
    }
    
  • E. Ephzibah
    V. Sundarapandian
    Year: 2012
    A Fuzzy Rule Based Expert System for Effective Heart Disease Diagnosis
    CCSIT PATR II
    Springer
    DOI: 10.1007/978-3-642-27308-7_20
E. Ephzibah1,*, V. Sundarapandian2,*
  • 1: VIT University
  • 2: Vel Tech Dr. RR & Dr. SR Technical University
*Contact email: ep.ephzibah@vit.ac.in, sundarvtu@gmail.com

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.