罗悦, 刘玉楠, 林冰, 温川飙. 基于RBF神经网络的体检指标与中医体质关联性研究[J]. Digital Chinese Medicine, 2020, 3(1): 11-19. DOI: 10.1016/j.dcmed.2020.03.002
引用本文: 罗悦, 刘玉楠, 林冰, 温川飙. 基于RBF神经网络的体检指标与中医体质关联性研究[J]. Digital Chinese Medicine, 2020, 3(1): 11-19. DOI: 10.1016/j.dcmed.2020.03.002
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LUO Yue, LIU Yu-Nan, LIN Bing, WEN Chuan-Biao. Research on the Correlation Between Physical Examination Indexes and TCM Constitutions Using the RBF Neural Network[J]. Digital Chinese Medicine, 2020, 3(1): 11-19. DOI: 10.1016/j.dcmed.2020.03.002
Citation: LUO Yue, LIU Yu-Nan, LIN Bing, WEN Chuan-Biao. Research on the Correlation Between Physical Examination Indexes and TCM Constitutions Using the RBF Neural Network[J]. Digital Chinese Medicine, 2020, 3(1): 11-19. DOI: 10.1016/j.dcmed.2020.03.002
shu

基于RBF神经网络的体检指标与中医体质关联性研究

Research on the Correlation Between Physical Examination Indexes and TCM Constitutions Using the RBF Neural Network

    摘要
  • 摘要:
    目的采用RBF神经网络技术，构建体检指标与中医体质关联模型，研究二者关联性。
    方法对采集的650例体检者体检指标和中医体质类型原始数据进行数据清理、分类、整理，形成有效数据，并将其分为学习组和测试组。运用RBF神经网络技术和学习组有效样本，构建体检指标与中医体质关联模型，再运用测试组有效样本测试关联模型的正确率和误差。
    结果在所选取的样本中，血脂指标−中医体质关联模型最高正确率为80%；肾功指标−中医体质关联模型最高正确率为100%；血常规（男）指标−中医体质关联模型最高正确率为100%；血常规（女）指标−中医体质关联模型最高正确率为88.8%；尿常规指标−中医体质关联模型最高正确率为84.1%；输血全套体检指标−中医体质关联模型最高正确率为100%。
    结论对本论文所选取的样本，证明体检指标与中医体质有较强的关联性，将该关联模型用于中医体质辨识具有一定的可行性。

     

    Abstract:
    ObjectiveTo establish correlation models between various physical examination indexes and traditional Chinese medicine (TCM) constitutions, and explore their relationships based on the radial basis function (RBF) neural network.
    MethodsThe raw data of physical examination indexes and TMC constitutions of 650 subjects who underwent a physical examination were cleaned, classified and sorted, on the basis of which valid data were retrieved and categorized into a training dataset and a test dataset. Subsequently, the RBF neural network was applied to the valid samples in the training set to establish correlation models between various physical examination indexes and TCM constitutions. The accuracy and the error margin of the correlation model were then verified using the valid samples in the test set.
    ResultsOf all selected samples, the highest accuracy rates were 80% for the blood lipid index - TCM constitution model; 100% for the renal function index - TCM constitution model; 100% for the blood routine (male) index - TCM constitution model; 88.8% for the blood routine (female) index - TCM constitution model; 84.1% for the urine routine index - TCM constitution model; and 100% for the blood transfusion index - TCM constitution model.
    ConclusionsThe samples selected in this study suggested that there is a strong correlation between physical examination indexes and TCM constitutions, making it feasible to apply the established correlation models to TCM constitution identification.

     

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