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Thyroid Disease Diagnosis Based on Genetic Algorithms Using PNN and SVM

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4 Author(s)
Saiti, F. ; Electr. Eng. Dept., K.N. Toosi Univ. of Technol., Tehran, Iran ; Naini, A.A. ; Shoorehdeli, M.A. ; Teshnehlab, M.

Thyroid gland produces thyroid hormones to help the regulation of the body's metabolism. The abnormalities of producing thyroid hormones are divided into two categories. Hypothyroidism which is related to production of insufficient thyroid hormone and hyperthyroidism related to production of excessive thyroid hormone. Separating these two diseases is very important for thyroid diagnosis. Therefore support vector machines and probabilistic neural network are proposed to classification. These methods rely mostly on powerful classification algorithms to deal with redundant and irrelevant features. In this paper feature selection is argued as an important problem via diagnosis and demonstrate that GAs provide a simple, general and powerful framework for selecting good subsets of features leading to improved diagnosis rates. Thyroid disease datasets are taken from UCI machine learning dataset.

Published in:

Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on

Date of Conference:

11-13 June 2009