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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
  • , Clement Loy
  • , Kelvin Chan
  • , Daniel Man-yuen Sze

Research output: Contribution to journalArticlepeer-review

31 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 - 2011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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