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

Authors :
Kara, Sadık
Aksebzeci, Bekir Hakan
Kodaz, Halife
Güneş, Salih
Kaya, Esma
Özbilge, Hatice
Source :
Expert Systems with Applications. Apr2009 Part 1, Vol. 36 Issue 3, p5168-5172. 5p.
Publication Year :
2009

Abstract

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. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
09574174
Volume :
36
Issue :
3
Database :
Academic Search Index
Journal :
Expert Systems with Applications
Publication Type :
Academic Journal
Accession number :
36300088
Full Text :
https://doi.org/10.1016/j.eswa.2008.06.029