Abstract
Cluster analysis is a popular method for statistical classification for data mining. It is introduced to traditional Chinese medicine (TCM) for quantifying and normalizing the clinical practice objectively. The present study reported that TCM syndromes classification and diagnosis of 163 cases of ankylosing spondylitis (AS) active stage through cluster analysis were feasible. And 32 symptoms and signs of AS active stage were clustered and discriminated clearly. The results showed four syndromes and their corresponding therapy methods were compatible to guide TCM clinical practice, which integrated valuable experience and modern methodology preferably. Cluster analysis for AS information excavation in TCM is worthily manipulable as well as the use of which in other TCM fields.
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© 2011 Springer-Verlag Berlin Heidelberg
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Yao, K., Zhang, L., Wang, J., Zhang, J. (2011). Syndromes Classification of the Active Stage of Ankylosing Spondylitis in Traditional Chinese Medicine by Cluster Analysis of Symptoms and Signs Data. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_97
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DOI: https://doi.org/10.1007/978-3-642-19853-3_97
Publisher Name: Springer, Berlin, Heidelberg
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