sis 20(26): e3

Research Article

Diagnosis Heart Disease Using Mamdani Fuzzy Inference Expert System

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  • @ARTICLE{10.4108/eai.15-1-2020.162736,
        author={Iftikhar Naseer and Bilal Shoaib Khan and Shazia Saqib and Syed Nadeem Tahir and Sheraz Tariq and Muhammad Saleem Akhter},
        title={Diagnosis Heart Disease Using Mamdani Fuzzy Inference Expert System},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={7},
        number={26},
        publisher={EAI},
        journal_a={SIS},
        year={2020},
        month={1},
        keywords={DHD-MFI, CAD, ECG, BP, CP, Mamdani Inference},
        doi={10.4108/eai.15-1-2020.162736}
    }
    
  • Iftikhar Naseer
    Bilal Shoaib Khan
    Shazia Saqib
    Syed Nadeem Tahir
    Sheraz Tariq
    Muhammad Saleem Akhter
    Year: 2020
    Diagnosis Heart Disease Using Mamdani Fuzzy Inference Expert System
    SIS
    EAI
    DOI: 10.4108/eai.15-1-2020.162736
Iftikhar Naseer1,*, Bilal Shoaib Khan1, Shazia Saqib2, Syed Nadeem Tahir3, Sheraz Tariq1, Muhammad Saleem Akhter1
  • 1: Department of Computer Science, Minhaj University, Lahore, Pakistan
  • 2: Department of Computer Science, Lahore Garrison University, Lahore, Pakistan
  • 3: Ph.D. Scholar, IAS Department, University of the Punjab, Lahore, Pakistan
*Contact email: iftikharnaseer@gmail.com

Abstract

The death ratio caused by heart diseases is threating around the world. Efficient and accurate diagnosis through information technology can turn over this picture. This article proposed Diagnosis Heart Disease using Mamdani Fuzzy Inference (DHD-MFI) based expert system which intelligently diagnoses heart disease. In an explorative pattern, the current research has taken six conducive variables for the purpose of fuzzy logic technical enhancement in the diagnosis of heart disease. The input fields comprise of age, chest pain, electrocardiography, blood pressure systolic, diabetic and cholesterol are transmitted with the help of Fuzzy rules which are framed in the light of low, normal, high and very high intensity among the input variations. The single output is obtained as a clinical decision support system for the heart diagnosis by using the Mamdani Inference method. The proposed DHD-MFI based expert system gives 94% overall accuracy.