DocumentCode
2558150
Title
Prognosis of the sexually-precocious girl´s luteinizing hormone peak value with the neural network and ultrasonic
Author
Liang, Zhe-Hao ; Lu, Wei
Author_Institution
Dept. of Ultrasound, Univ. of Traditional Chinese Med., Hangzhou, China
fYear
2012
fDate
29-31 May 2012
Firstpage
444
Lastpage
448
Abstract
It aims at technologically forecasting the serum luteinizing hormone(LH) peak value by means of the artificial neural network combined with the ultrasound in the examination of exciting the gonadotropin releasing hormone(GnRH). In the process, 71 girls of the sexual precocity are selected to take the conventional ultrasonic testing on the uterus and ovary. And then, the uterus size, the ovary size and the inner diameter of the biggest ovarian follicle in the 61 of those selected girls are set to be the input variable while the LH peak value the output variable. And BP neural network is in formation, and another 10 girls are used as testing targets. As a result, the linear regression is used as a method to calculate the real value and the BP network forecasting value, showing that the correlation coefficient of the linear regression is 0.9485 and the slope is 0.9280. In conclusion, the LH peak value in the examination of GnRH can be predicted by using the ultrasound combined with the BP neural network.
Keywords
backpropagation; biology computing; biomedical ultrasonics; neural nets; BP network forecasting value; BP neural network; artificial neural network; correlation coefficient; gonadotropin releasing hormone; linear regression; ovarian follicle; ovary size; serum luteinizing hormone peak value; sexually-precocious girl; technological forecasting; ultrasonic testing; ultrasonics; ultrasound; uterus size; Acoustics; Biochemistry; Biological neural networks; Neurons; Testing; Ultrasonic imaging; neural network; serum luteinizing hormone peak value; ultrasound;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location
Chongqing
ISSN
2157-9555
Print_ISBN
978-1-4577-2130-4
Type
conf
DOI
10.1109/ICNC.2012.6234608
Filename
6234608
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