Abstract
Relevance exists in Traditional Chinese Medicine(TCM) clinical symptoms. Their different combinations reflect different effects. Focusing on these characteristics, an univariate analysis method based on the factor analysis and clustering(FACUA) is proposed. First, the independent common factors extracted from the correlative multivariable are used to establish the eigenvectors of symptoms for patients. Then, the symptom patterns are discovered from the gathered similar symptoms combination. The method is verified by the patients with advanced NSCLC(non-small cell lung cancer) from Beijing Hospital of Traditional Chinese Medicine. The experimental result shows that the FACUA method can deal with the TCM clinical symptoms and analyze the relationship between the TCM clinical symptoms and the tumor progression. The FACUA method can improve the universal applicability of the univariate analysis in TCM clinical symptoms.
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© 2011 Springer-Verlag Berlin Heidelberg
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Liu, Z., Fang, L., Yu, M., Wang, P. (2011). Study of Prognostic Factor Based on Factor Analysis and Clustering Method. In: Li, S., Wang, X., Okazaki, Y., Kawabe, J., Murofushi, T., Guan, L. (eds) Nonlinear Mathematics for Uncertainty and its Applications. Advances in Intelligent and Soft Computing, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22833-9_65
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DOI: https://doi.org/10.1007/978-3-642-22833-9_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22832-2
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