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A Comparison of Artificial Intelligence Methods on Determining Coronary Artery Disease

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Advances in Information Technology (IAIT 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 114))

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Abstract

The aim of this study is to show a comparison of multi-layered perceptron neural network (MLPNN) and support vector machine (SVM) on determination of coronary artery disease existence upon exercise stress testing (EST) data. EST and coronary angiography were performed on 480 patients with acquiring 23 verifying features from each. The robustness of the proposed methods is examined using classification accuracy, k-fold cross-validation method and Cohen’s kappa coefficient. The obtained classification accuracies are approximately 78% and 79% for MLPNN and SVM respectively. Both MLPNN and SVM methods are rather satisfactory than human-based method looking to Cohen’s kappa coefficients. Besides, SVM is slightly better than MLPNN when looking to the diagnostic accuracy, average of sensitivity and specificity, and also Cohen’s kappa coefficient.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Selçuk University, 42075, Konya, Turkey

    İsmail Babaoğlu & Ömer Kaan Baykan

  2. Department of Cardiology, Selçuklu Faculty of Medicine, Selçuk University, 42075, Konya, Turkey

    Nazif Aygül

  3. Department of Cardiology, Meram Faculty of Medicine, Selçuk University, 42080, Konya, Turkey

    Kurtuluş Özdemir

  4. Department of Electrical and Electronics Engineering, Mevlana University, 42075, Konya, Turkey

    Mehmet Bayrak

Authors
  1. İsmail Babaoğlu
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  2. Ömer Kaan Baykan
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  3. Nazif Aygül
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  4. Kurtuluş Özdemir
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  5. Mehmet Bayrak
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Editors and Affiliations

  1. School of Information Technology, King Mongkut’s University of Technology, Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Borworn Papasratorn , Kittichai Lavangnananda , Wichian Chutimaskul  & Vajirasak Vanijja , ,  & 

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Babaoğlu, İ., Baykan, Ö.K., Aygül, N., Özdemir, K., Bayrak, M. (2010). A Comparison of Artificial Intelligence Methods on Determining Coronary Artery Disease. In: Papasratorn, B., Lavangnananda, K., Chutimaskul, W., Vanijja, V. (eds) Advances in Information Technology. IAIT 2010. Communications in Computer and Information Science, vol 114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16699-0_3

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  • DOI: https://doi.org/10.1007/978-3-642-16699-0_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16698-3

  • Online ISBN: 978-3-642-16699-0

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