The autonomic nervous system (ANS) controls white blood cell (WBC) subsets;therefore, the status of ANS can be assessed by assaying WBCs. However, this requires invasive blood sampling, time, cost, and training. There...The autonomic nervous system (ANS) controls white blood cell (WBC) subsets;therefore, the status of ANS can be assessed by assaying WBCs. However, this requires invasive blood sampling, time, cost, and training. Therefore, this study focused on a traditional technique, tongue inspection, which is a simpler method. The purpose of this study was to investigate whether there is an association between the traditional method of tongue inspection and clinical assay of WBC subsets. Twenty-one female alopecia areata patients were divided into two age-matched groups: 1) alopecia areata totalis (AT);and 2) alopecia areata multiplex (AM). Images of patient tongues were captured by a digital camera and categorized before blood sampling. Finally, patients were divided into five groups (normal, Yin+, Yang–, Yin– and Yang+) based on the Eight Principles of traditional Chinese medicine (TCM). Concurrently, venous blood was obtained for WBC subsets. The absolute numbers of WBCs and granulocytes of the AT group were higher than those of the AM group. The AT group was Yin+ but not Yang+, whereas the AM group was Yang+ but not Yin+. Thus, the AT group showed more elements of “cold” (Yin > Yang) compared with the AM group with elements of “hot” (Yin < Yang). Tongue inspection suggested a possibility of consistence with those of WBCs although statistical significance was not obtained. Moreover, some Yin+ and Yang+ subjects showed some trend in similarities between tongue inspection and WBC subsets although this was not statistically significant. Therefore, traditional techniques (such as tongue inspection) acupuncture must be studied further to detect whether subtle effects are induced by acupuncture treatment. As this study is underpowered, a larger scale study including males is required in the future.展开更多
目的通过机器学习分析“舌边白涎”舌象特性,对舌象进行局部特征识别研究,探讨卷积神经网络算法在舌象识别应用中的性能。方法使用Python进行图像预处理,搭建用于舌象识别的视觉几何组16层(visual geometry group 16,VGG16)卷积神经网...目的通过机器学习分析“舌边白涎”舌象特性,对舌象进行局部特征识别研究,探讨卷积神经网络算法在舌象识别应用中的性能。方法使用Python进行图像预处理,搭建用于舌象识别的视觉几何组16层(visual geometry group 16,VGG16)卷积神经网络模型,分析其对“舌边白涎”舌象鉴别分析的效果,并结合热力图分析“舌边白涎”典型舌象表现。结果基于PyTorch框架,进行卷积神经网络的舌象鉴别研究,VGG16及残差网络50层(residual network 50,ResNet50)模型验证准确率均较高,达到80%以上,且ResNet50模型优于VGG16模型,可为舌象识别提供一定参考。基于加权梯度类激活映射(gradient-weighted class activation mapping,Grad-CAM)技术,通过舌苔舌色差异分布的网络可视化,有助于直观进行模型评估分析。结论基于卷积神经网络模型对舌象数据库进行分析,实现“舌边白涎”舌象识别,有助于临床诊疗的客观化辅助分析,为舌诊智能化发展提供一定借鉴。展开更多
文摘The autonomic nervous system (ANS) controls white blood cell (WBC) subsets;therefore, the status of ANS can be assessed by assaying WBCs. However, this requires invasive blood sampling, time, cost, and training. Therefore, this study focused on a traditional technique, tongue inspection, which is a simpler method. The purpose of this study was to investigate whether there is an association between the traditional method of tongue inspection and clinical assay of WBC subsets. Twenty-one female alopecia areata patients were divided into two age-matched groups: 1) alopecia areata totalis (AT);and 2) alopecia areata multiplex (AM). Images of patient tongues were captured by a digital camera and categorized before blood sampling. Finally, patients were divided into five groups (normal, Yin+, Yang–, Yin– and Yang+) based on the Eight Principles of traditional Chinese medicine (TCM). Concurrently, venous blood was obtained for WBC subsets. The absolute numbers of WBCs and granulocytes of the AT group were higher than those of the AM group. The AT group was Yin+ but not Yang+, whereas the AM group was Yang+ but not Yin+. Thus, the AT group showed more elements of “cold” (Yin > Yang) compared with the AM group with elements of “hot” (Yin < Yang). Tongue inspection suggested a possibility of consistence with those of WBCs although statistical significance was not obtained. Moreover, some Yin+ and Yang+ subjects showed some trend in similarities between tongue inspection and WBC subsets although this was not statistically significant. Therefore, traditional techniques (such as tongue inspection) acupuncture must be studied further to detect whether subtle effects are induced by acupuncture treatment. As this study is underpowered, a larger scale study including males is required in the future.
文摘目的通过机器学习分析“舌边白涎”舌象特性,对舌象进行局部特征识别研究,探讨卷积神经网络算法在舌象识别应用中的性能。方法使用Python进行图像预处理,搭建用于舌象识别的视觉几何组16层(visual geometry group 16,VGG16)卷积神经网络模型,分析其对“舌边白涎”舌象鉴别分析的效果,并结合热力图分析“舌边白涎”典型舌象表现。结果基于PyTorch框架,进行卷积神经网络的舌象鉴别研究,VGG16及残差网络50层(residual network 50,ResNet50)模型验证准确率均较高,达到80%以上,且ResNet50模型优于VGG16模型,可为舌象识别提供一定参考。基于加权梯度类激活映射(gradient-weighted class activation mapping,Grad-CAM)技术,通过舌苔舌色差异分布的网络可视化,有助于直观进行模型评估分析。结论基于卷积神经网络模型对舌象数据库进行分析,实现“舌边白涎”舌象识别,有助于临床诊疗的客观化辅助分析,为舌诊智能化发展提供一定借鉴。
