基于BP神经网络的高血压中医证候与危险分层关系研究

Research on Relationship between the TCM Syndrome of Hypertension and Risk Stratification

目的:探讨基于共轭梯度算法的BP神经网络模型研究高血压中医证候与危险分层的关系。方法:基于MATLAB7.0环境,采用改进的共轭梯度(trainscg)学习算法,以高血压中医症状为输入,高血压危险分层为输出,建立结构为24-7-4的BP神经网络模型,使用120例样本进行训练,34例样本进行测试。结果:总体识别率为85.3%。结论:人工神经网络技术应用于高血压中医证候与危险分层关系研究具有方法学上的可行性。

Objective Explore BPNN based on conjugate gradient algorithm used to research relationship between the TCM syndrome of hypertension and risk stratification. Methods Based on MATLAB7.0 environment, BPNN model with the structure of 24-7-4 is developed using the improved conjugate gradient algorithm, with the TCM Syndrome of Hypertension as input and Risk Stratification as output. 120 samples are used to train the net, while the other 34 samples to test. Results the total accuracy rate of diagnosis is 85. 3%. Conclusion On the methodology it is feasible to use ANN research relationship between the TCM syndrome of hypertension and risk stratification.