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首页> 外文会议>2011 IEEE International Conference on Systems, Man, and Cybernetics >Sensitivity-based data selection for predicting individual's sub-health on TCM doctors' diagnosis
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Sensitivity-based data selection for predicting individual's sub-health on TCM doctors' diagnosis

机译：基于敏感性的数据选择可预测中医医生诊断的亚健康

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摘要

In this paper we propose an approach of predicting individual's sub-health based on the principle of TCM (Traditional Chinese medicine) as a preventive medicine. The object's vision features like features of tongue, eye and face are extracted for modeling a process of TCM doctor's diagnosis. As a consequence of the diversity and uncertainty of TCM doctors' diagnosis, the sensitivity is defined as a criterion to select the appropriate features from the derived features, and integrate the diagnosis data given by multiple doctors as training data for constructing the sub-health inference model. The experiment results show that the sensitivity-based feature selection and diagnosis data integration improve the model's inference performance on the accuracy, correlation and residual variance.
机译：在本文中，我们提出了一种基于中医作为预防医学原理的个人亚健康预测方法。提取对象的视觉特征，例如舌头，眼睛和面部特征，以模拟中医诊断过程。由于中医诊断的多样性和不确定性，敏感性被定义为从衍生特征中选择合适特征，并将多位医生给出的诊断数据作为训练数据来构建亚健康推断的标准。模型。实验结果表明，基于灵敏度的特征选择和诊断数据集成提高了模型在准确性，相关性和残差方差上的推理性能。

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