Analysis of Synergistic and Antagonistic Effects of TCM: Cases on Diabetes and Insomnia

Author(s)
McGrane, Martin
Poon, Simon
Gao, Junbin
Poon, Josiah
Zhou, Xuezhong
Zhang, Runshun
Liu, Baoyan
Chan, Kelvin
Loy, Clement
Kwan, Paul H
Sze, Daniel
Publication Date
2010
Abstract
Background: Herbal Medicine in Traditional Chinese Medicine (TCM) relies on interactions between the ingredients of a prescription. The combination is chosen to promote desirable interactions. Analyzing these interactions is an important step in quantitatively analyzing the effects of TCM on patient outcomes. The concept of interactions has not been adequately formulated in analyzing the effects of TCM due to the ambiguity of "interaction" and the need to go beyond traditional quantitative methods for analyzing data. Results: In this working paper, we present an exploratory analysis of clinical records of treatment using an interaction pattern mining approach. We present the most significant interactions found with a summary of the clinical significance of the interactions. Conclusions: Experimental evaluation confirms that this approach is able to detect effective high order herb-herb interactions in high dimensional TCM datasets. The interaction mining approach can be a potentially useful technique for discovering interactions not detected by other analysis techniques. The results will have implications for better understanding of the mechanisms of action and the overall system effects.
Citation
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), p. 620-624
ISBN
9781424483037
Link
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Title
Analysis of Synergistic and Antagonistic Effects of TCM: Cases on Diabetes and Insomnia
Type of document
Conference Publication
Entity Type
Publication

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