A novel approach in discovering significant interactions from TCM patient prescription data Online publication date: Tue, 26-Jul-2011
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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