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Title: Novel two-stage analytic approach in extraction of strong herb-herb interactions in TCM clinical treament of insomnia
Authors: Zhou, X
Poon, J
Kwan, P
Zhang, R
Wang, Y
Poon, S
Liu, B
Sze, D
Keywords: Multifactor dimensionality reduction
Features selection
Traditional chinese medicine insomnia
Network analysis
Herb interactions
Issue Date: 2010
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2010, v. 6165, p. 258-267 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: In this paper, we aim to investigate strong herb-herb interactions in TCM for effective treatment of insomnia. Given that extraction of herb interactions is quite similar to gene epistasis study due to non-linear interactions among their study factors, we propose to apply Multifactor Dimensionality Reduction (MDR) that has shown useful in discovering hidden interaction patterns in biomedical domains. However, MDR suffers from high computational overhead incurred in its exhaustive enumeration of factors combinations in its processing. To address this drawback, we introduce a two-stage analytical approach which first uses hierarchical core sub-network analysis to pre-select the subset of herbs that have high probability in participating in herb-herb interactions, which is followed by applying MDR to detect strong attribute interactions in the pre-selected subset. Experimental evaluation confirms that this approach is able to detect effective high order herb-herb interaction models in high dimensional TCM insomnia dataset that also has high predictive accuracies.
Description: 2nd International Conference on Medical Biometrics, ICMB 2010, Hong Kong, China, Jun 28-30, 2010
ISBN: 978-3-642-13922-2
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-642-13923-9_28
Appears in Collections:Conference Paper

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