Title | ||
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Hierarchical Latent Class Models and Statistical Foundation for Traditional Chinese Medicine |
Abstract | ||
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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. |
Year | DOI | Venue |
---|---|---|
2007 | 10.1007/978-3-540-73599-1_15 | AIME '87 |
Keywords | Field | DocType |
modern science,statistical foundation,data analysis,relevant tcm theory,common perception,statistical model,modern day data analysis,tcm theory,hierarchical latent class models,ancient time,traditional chinese medicine,tcm data,machine learning,cluster analysis | Ask price,Computer science,Latent variable,Traditional Chinese medicine,Artificial intelligence,Natural language processing,Statistical model,Perception,Machine learning | Conference |
Volume | ISSN | Citations |
4594 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 3 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Nevin .L Zhang | 1 | 895 | 97.21 |
Shihong Yuan | 2 | 23 | 1.61 |
Tao Chen | 3 | 76 | 7.04 |
Yi WANG | 4 | 28 | 2.08 |