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首页> 外文会议>International Conference on Natural Computation >Prognosis of the sexually-precocious girl's luteinizing hormone peak value with the neural network and ultrasonic
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Prognosis of the sexually-precocious girl's luteinizing hormone peak value with the neural network and ultrasonic

机译：性急性女孩的预后与神经网络和超声波的素质化激素峰值

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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.
机译：它旨在通过人工神经网络与超声检查促进促进促性腺激素释放激素（GNRH）的超声波进行技术预测血清培氏素峰值（LH）峰值。在此过程中，选择了71个女孩的性预幂，以在子宫和卵巢上采取传统的超声波测试。然后，在那些选定的女孩的61中的子宫尺寸，卵巢大小和内径的最大卵巢卵泡的内径被设置为输入变量，而LH峰值输出变量。而BP神经网络正在形成，另外10名女孩用作测试目标。结果，线性回归用作计算实际值和BP网络预测值的方法，表明线性回归的相关系数为0.9485，斜率为0.9280。总之，通过使用超声组合与BP神经网络相结合，可以预测GNRH检查中的LH峰值。

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