title: A novel approach in discovering significant interactions from TCM patient prescription data.
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.
authors.affiliation: School of Information Technologies, University of Sydney, Sydney, Australia simon.poon@sydney.edu.au
authors.forename: Simon K
authors.initials: SK
authors.lastname: Poon
authors.forename: Josiah
authors.initials: J
authors.lastname: Poon
authors.forename: Martin
authors.initials: M
authors.lastname: McGrane
authors.forename: Xuezhong
authors.initials: X
authors.lastname: Zhou
authors.forename: Paul
authors.initials: P
authors.lastname: Kwan
authors.forename: Runshun
authors.initials: R
authors.lastname: Zhang
authors.forename: Baoyan
authors.initials: B
authors.lastname: Liu
authors.forename: Junbin
authors.initials: J
authors.lastname: Gao
authors.forename: Clement
authors.initials: C
authors.lastname: Loy
authors.forename: Kelvin
authors.initials: K
authors.lastname: Chan
authors.forename: Daniel Man-Yuen
authors.initials: DM
authors.lastname: Sze
mesh_terms: D057225:Data Mining / Q000379:methods*; D016208:Databases, Factual; D011307:Drug Prescriptions / Q000592:standards; D006801:Humans; D008516:Medicine, Chinese Traditional