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A novel approach in discovering significant interactions from TCM patient prescription data
by Simon K. Poon, Josiah Poon, Martin McGrane, Xuezhong Zhou, Paul Kwan, Runshun Zhang, Baoyan Liu, Junbin Gao, Clement Loy, Kelvin Chan, Daniel Man-yuen Sze
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 5, No. 4, 2011
Abstract: The efficacy of a traditional Chinese medicine medication derives from the complex interactions of herbs or Chinese Materia Medica in a formula. The aim of this paper is to propose a new approach to systematically generate combinations of interacting herbs that might lead to good outcome. Our approach was tested on a data set of prescriptions for diabetic patients to verify the effectiveness of detected combinations of herbs. This approach is able to detect effective higher orders of herb-herb interactions with statistical validation. We present an exploratory analysis of clinical records using a pattern mining approach called Interaction Rules Mining.
Online publication date: Tue, 26-Jul-2011
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