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A Comparative Study on Computerised Diagnostic Performance of Hepatitis Disease Using ANNs

  • Revna Acar Vural
  • Lale Özyılmaz
  • Tülay Yıldırım
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

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.

Keywords

Radial Basis Function Receiver Operating Characteristic Analysis Radial Basis Function Neural Network Radial Basis Function Network Hide Unit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Revna Acar Vural
    • 1
  • Lale Özyılmaz
    • 1
  • Tülay Yıldırım
    • 1
  1. 1.Department of Electronics & Communications Eng., Yıldız Technical University, İstanbul 34349Turkey

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