A novel approach in discovering significant interactions from TCM patient prescription data

Simon K. Poon, Josiah Poon, Martin McGrane, Xuezhong Zhou, Paul Kwan, Runshun Zhang, Baoyan Liu, Junbin Gao

    Research output: Contribution to journalArticlepeer-review

    29 Citations (Scopus)

    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.
    Original languageEnglish
    Pages (from-to)353-368
    Number of pages16
    JournalInternational Journal of Data Mining and Bioinformatics
    Volume5
    Issue number4
    DOIs
    Publication statusPublished - Jul 2011

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