Open AccessAssociation Rule Mining and Network Analysis in Oriental Medicine
Author(s) -
DongHoon Yang,
Ji Hoon Kang,
Young Bae Park,
Young-Jae Park,
Hwan Sup Oh,
Seoung Bum Kim
Publication year - 2013
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0059241
Subject(s) - association rule learning , medical prescription , data mining , association (psychology) , traditional medicine , medicine , alternative medicine , medline , data science , computer science , psychology , pharmacology , biology , pathology , biochemistry , psychotherapist
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.
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