title: Association rule mining and network analysis in oriental medicine.
abstract: Extracting useful and meaningful patterns from large volumes of text data is of growing importance. In the present study we analyze vast amounts of prescription data, generated from the book of oriental medicine to identify the relationships between the symptoms and the associated medicines used to treat these symptoms. The oriental medicine book used in this study (called Bangyakhappyeon) contains a large number of prescriptions to treat about 54 categorized symptoms and lists the corresponding herbal materials. We used an association rule algorithm combined with network analysis and found useful and informative relationships between the symptoms and medicines.
authors.affiliation: Department of Biofunctional Medicine and Diagnostics, Kyung Hee University, Hoegi-dong, Seoul, Republic of Korea.
authors.forename: Dong Hoon
authors.initials: DH
authors.lastname: Yang
authors.forename: Ji Hoon
authors.initials: JH
authors.lastname: Kang
authors.forename: Young Bae
authors.initials: YB
authors.lastname: Park
authors.forename: Young Jae
authors.initials: YJ
authors.lastname: Park
authors.forename: Hwan Sup
authors.initials: HS
authors.lastname: Oh
authors.forename: Seoung Bum
authors.initials: SB
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D003625:Data Collection / Q000379:methods / Q000706:statistics & numerical data*; D057225:Data Mining / Q000379:methods / Q000706:statistics & numerical data*; D062313:Databases, Pharmaceutical / Q000706:statistics & numerical data*; D011307:Drug Prescriptions; D006801:Humans; D008518:Medicine, East Asian Traditional; D016571:Neural Networks, Computer; D028321:Plant Preparations / Q000627:therapeutic use*; D056910:Republic of Korea
chemical_list: D028321:Plant Preparations
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