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首页> 外文期刊>International journal for numerical methods in biomedical engineering >A machine learning method correlating pulse pressure wave data with pregnancy
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A machine learning method correlating pulse pressure wave data with pregnancy

机译:一种将脉压波数据与妊娠相关联的机器学习方法

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摘要

Pulse feeling , representing the tactile arterial palpation of the heartbeat, has been widely used in traditional Chinese medicine (TCM) to diagnose various diseases. The quantitative relationship between the pulse wave and health conditions however has not been investigated in modern medicine. In this paper, we explored the correlation between pulse pressure wave (PPW), rather than the pulse key features in TCM, and pregnancy by using deep learning technology. This computational approach shows that the accuracy of pregnancy detection by the PPW is 84% with an area under the curve (AUC) of 91%. Our study is a proof of concept of pulse diagnosis and will also motivate further sophisticated investigations on pulse waves.
机译:脉搏感觉代表了心跳的触觉动脉触诊,已被广泛用于中医(TCM)诊断各种疾病。然而,现代医学尚未研究脉搏波与健康状况之间的定量关系。在本文中,我们使用深度学习技术探索了脉压波(PPW)而非妊娠中医的脉搏关键特征与妊娠之间的相关性。这种计算方法表明,PPW检测怀孕的准确性为84%,曲线下面积(AUC)为91%。我们的研究证明了脉搏诊断的概念,也将激发对脉搏波的进一步复杂研究。

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