Medical application of information gain-based artificial immune recognition system (IG-AIRS): Classification of microorganism species

Kara S., Aksebzeci B. H., Kodaz H., Gunes S., Kaya E., Ozbilge H.

EXPERT SYSTEMS WITH APPLICATIONS, vol.36, no.3, pp.5168-5172, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 3
  • Publication Date: 2009
  • Doi Number: 10.1016/j.eswa.2008.06.029
  • Journal Name: EXPERT SYSTEMS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.5168-5172
  • Keywords: Artificial immune systems, Artificial immune recognition system, Information gain, Microorganism classification, Electronic nose, BACTERIA, IDENTIFICATION, DIAGNOSIS
  • Abdullah Gül University Affiliated: No

Abstract

In this paper, we have made medical application of a new artificial immune system named the information gain-based artificial immune recognition system (IG-AIRS) which is minimized the negative effects of taking into account all attributes in calculating Euclidean distance in shape-space representation which is used in many artificial immune systems. For medical data, microorganism dataset was applied in the performance analysis of our proposed system. Microorganism dataset was obtained using Cyranose 320 electronic nose. Our proposed system reached 92.35% classification accuracy with five-fold cross validation method. This result ensured that IG-AIRS would be helpful in classification of microorganism species based on laboratory tests, and would open the way to various microorganism species determine support by using electronic nose. (C) 2008 Elsevier Ltd. All rights reserved.