首页> 外文会议>Conference on Artificial Intelligence in Medicine(AIME 2007); 20070707-11; Amsterdam(NL) >Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine
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Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine

机译:中医药的分层潜类模型与统计基础

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摘要

The theories of traditional Chinese medicine (TCM) originated from experiences doctors had with patients in ancient times. We ask the question whether aspects of TCM theories can be reconstructed through modern day data analysis. We have recently analyzed a TCM data set using a machine learning method and found that the resulting statistical model matches the relevant TCM theory well. This is an exciting discovery because it shows that, contrary to common perception, there are scientific truths in TCM theories. It also suggests the possibility of laying a statistical foundation for TCM through data analysis and thereby turning it into a modern science.
机译:中医理论起源于古代医生对病人的经历。我们提出一个问题,即中医理论的各个方面是否可以通过现代数据分析来重建。我们最近使用机器学习方法分析了中医数据集,发现生成的统计模型与相关中医理论非常吻合。这是一个令人兴奋的发现,因为它表明,与通常的看法相反,中医理论中存在科学真理。这也表明有可能通过数据分析为中医药奠定统计基础,从而将其转化为现代科学。

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