Comparative study on computerised diagnostic performance of hepatitis disease using ANNs

Vural R., Ozyilmaz L., Yildirim T.

COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS, vol.4114, pp.1177-1182, 2006 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 4114
  • Publication Date: 2006
  • Journal Name: COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Page Numbers: pp.1177-1182
  • Yıldız Technical University Affiliated: Yes

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.