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

Authors:
Sadık Kara;Bekir Hakan Aksebzeci;Halife Kodaz;Salih Güneş;Esma Kaya;Hatice Özbilge
Affiliations:
Fatih University, Department of Electrical & Electronics Engineering, 34500 İİstanbul, Turkey;Erciyes University, Department of Electrical & Electronics Engineering, 38039 Kayseri, Turkey;Selcuk University, Department of Computer Engineering, 42075 Konya, Turkey;Selcuk University, Department of Electrical & Electronics Engineering, 42075 Konya, Turkey;Erciyes University, Faculty of Pharmacy, 38039 Kayseri, Turkey;Erciyes University, Faculty of Pharmacy, 38039 Kayseri, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 6
Cited 2

Principles and practice of information theory

Principles and practice of information theory
Computer immunology

Communications of the ACM
Artificial Immune Systems: A New Computational Intelligence Paradigm

Artificial Immune Systems: A New Computational Intelligence Paradigm
Medical application of Artificial Immune Recognition System (AIRS): Diagnosis of atherosclerosis from carotid artery Doppler signals

Computers in Biology and Medicine
A study of cross-validation and bootstrap for accuracy estimation and model selection

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
The medical applications of attribute weighted artificial immune system (AWAIS): diagnosis of heart and diabetes diseases

ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems

A Survey of artificial immune applications

Artificial Intelligence Review
A modified artificial immune system based pattern recognition approach-An application to clinical diagnostics

Artificial Intelligence in Medicine

Quantified Score

Hi-index	12.05

Visualization

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.