Presentation	2005-07-30 Medical Image Recognition by self-selecting algorithm for optimum neural network architecture Tadashi Kondo,
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Abstract(in English)	In this study, medical image recognition by self-selecting algorithm for optimum neural network architecture is developed. This algorithm is call as the GMDH-type neural network with sigmoid functions. The GMDH-type neural network algorithm with sigmoid functions can automatically generate the optimum neural network architecture that fits the complexity of the nonlinear system. The structural parameters such as the number of the layers, the number of the neurons in the hidden layers, the useful input variables are automatically determined so as to minimize the error criterion defined as AIC (Akaike's information criterion). Therefore, it is very easy to apply the GMDH-type neural network with sigmoid functions to the medical image recognition.
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Keyword(in English)	GMDH / Neural Network / Medical Image Recognition
Paper #	MBE2005-52
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Conference Information
Committee	MBE
Conference Date	2005/7/23(1days)
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Paper Information
Registration To	ME and Bio Cybernetics (MBE)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Medical Image Recognition by self-selecting algorithm for optimum neural network architecture
Sub Title (in English)
Keyword(1)	GMDH
Keyword(2)	Neural Network
Keyword(3)	Medical Image Recognition
1st Author's Name	Tadashi Kondo
1st Author's Affiliation	University of Tokushima()
Date	2005-07-30
Paper #	MBE2005-52
Volume (vol)	vol.105
Number (no)	222
Page	pp.pp.-
#Pages	4
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