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Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease

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Title: Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease
Authors: Kodaz, Halife1 hkodaz@selcuk.edu.tr, Özşen, Seral2 seral@selcuk.edu.tr, Arslan, Ahmet1 aarslan@selcuk.edu.tr, Güneş, Salih2 sgunes@selcuk.edu.tr
Source: Expert Systems with Applications. Mar2009 Part 2, Vol. 36 Issue 2, p3086-3092. 7p.
Subjects: Computer simulation of immune system, Thyroid diseases, Immunocomputers, Diagnosis, Immunology, Expert systems
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 minimizes 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, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress. [Copyright &y& Elsevier]
Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 35527929
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PubType: Academic Journal
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  Data: <searchLink fieldCode="AR" term="%22Kodaz%2C+Halife%22">Kodaz, Halife</searchLink><relatesTo>1</relatesTo><i> hkodaz@selcuk.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Özşen%2C+Seral%22">Özşen, Seral</searchLink><relatesTo>2</relatesTo><i> seral@selcuk.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Arslan%2C+Ahmet%22">Arslan, Ahmet</searchLink><relatesTo>1</relatesTo><i> aarslan@selcuk.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Güneş%2C+Salih%22">Güneş, Salih</searchLink><relatesTo>2</relatesTo><i> sgunes@selcuk.edu.tr</i>
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  Data: <searchLink fieldCode="JN" term="%22Expert+Systems+with+Applications%22">Expert Systems with Applications</searchLink>. Mar2009 Part 2, Vol. 36 Issue 2, p3086-3092. 7p.
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  Data: <searchLink fieldCode="DE" term="%22Computer+simulation+of+immune+system%22">Computer simulation of immune system</searchLink><br /><searchLink fieldCode="DE" term="%22Thyroid+diseases%22">Thyroid diseases</searchLink><br /><searchLink fieldCode="DE" term="%22Immunocomputers%22">Immunocomputers</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnosis%22">Diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Immunology%22">Immunology</searchLink><br /><searchLink fieldCode="DE" term="%22Expert+systems%22">Expert systems</searchLink>
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  Data: 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 minimizes 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, thyroid disease data set was applied in the performance analysis of our proposed system. Our proposed system reached 95.90% classification accuracy with 10-fold CV method. This result ensured that IG-AIRS would be helpful in diagnosing thyroid function based on laboratory tests, and would open the way to various ill diagnoses support by using the recent clinical examination data, and we are actually in progress. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Expert Systems with Applications is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.eswa.2008.01.026
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        Text: English
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      – SubjectFull: Computer simulation of immune system
        Type: general
      – SubjectFull: Thyroid diseases
        Type: general
      – SubjectFull: Immunocomputers
        Type: general
      – SubjectFull: Diagnosis
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              Text: Mar2009 Part 2
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