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Diagnosis of Heart Disease Using an Intelligent Method: A Hybrid ANN – GA Approach

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Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making (INFUS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1029))

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Abstract

Heart disease is the most important public health problem for many countries. Early diagnosis of heart disease is extremely crucial for the survival of the patient. At this point, classification algorithms are widely used for medical diagnosis. In this study, firstly, artificial neural network (ANN) with default parameters is used to diagnose heart disease. Then, a hybrid approach, combining artificial neural network (ANN) and genetic algorithm (GA), is proposed to improve classification accuracy. Finally, the effectiveness of the proposed approach is illustrated with ‘Cleveland’ dataset taken from UCI machine learning repository. Experimental results show that the proposed hybrid ANN - GA approach outperforms Naive Bayes, K- Nearest Neighbor and C4.5 algorithms in terms of accuracy rate, precision, recall and F-measure.

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Author information

Authors and Affiliations

  1. Istanbul University, Avcılar, 34320, Istanbul, Turkey

    Miray Akgül

  2. Istanbul University – Cerrahpasa, Avcılar, 34320, Istanbul, Turkey

    Özlen Erkal Sönmez & Tuncay Özcan

Authors
  1. Miray Akgül
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  2. Özlen Erkal Sönmez
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  3. Tuncay Özcan
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Corresponding author

Correspondence to Özlen Erkal Sönmez .

Editor information

Editors and Affiliations

  1. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Industrial Engineering Department, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  3. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Sezi Cevik Onar

  4. Management Faculty, Istanbul Technical University, İstanbul, Turkey

    Basar Oztaysi

  5. Industrial Engineering Department, Galatasaray University, Istanbul, Turkey

    A. Cagri Tolga

  6. Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Irem Ucal Sari

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Akgül, M., Sönmez, Ö.E., Özcan, T. (2020). Diagnosis of Heart Disease Using an Intelligent Method: A Hybrid ANN – GA Approach. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_147

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