Abstract
Artificial Neural Networks (ANNs) have been studied intensively in the field of computer science in recent years and have been shown to be a powerful tool for a variety of data-classification and pattern-recognition tasks. In this work, computerised diagnostic performance of hepatitis disease was investigated by various ANNs. Multilayer Perceptron, Radial Basis Function Neural Network, Conic Section Function Neural Network, Probabilistic Neural Network, and General Regression Neural Network structures have been used for this purpose. To determine diagnostic performance of networks for hepatitis disease, cross validation method and ROC analysis were applied.
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© 2006 Springer-Verlag Berlin Heidelberg
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Vural, R.A., Özyılmaz, L., Yıldırım, T. (2006). A Comparative Study on Computerised Diagnostic Performance of Hepatitis Disease Using ANNs. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_145
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DOI: https://doi.org/10.1007/978-3-540-37275-2_145
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37274-5
Online ISBN: 978-3-540-37275-2
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