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Association Rule Mining and Network Analysis in Oriental Medicine

Authors
Yang, Dong HoonKang, Ji HoonPark, Young BaePark, Young JaeOh, Hwan SupKim, Seoung Bum
Issue Date
15-Mar-2013
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, v.8, no.3
Indexed
SCIE
SCOPUS
Journal Title
PLOS ONE
Volume
8
Number
3
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/103736
DOI
10.1371/journal.pone.0059241
ISSN
1932-6203
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.
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