Association Rule Mining and Network Analysis in Oriental Medicine

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...

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Detalles Bibliográficos
Autores principales: Yang, Dong Hoon, Kang, Ji Hoon, Park, Young Bae, Park, Young Jae, Oh, Hwan Sup, Kim, Seoung Bum
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3598694/
https://www.ncbi.nlm.nih.gov/pubmed/23555003
http://dx.doi.org/10.1371/journal.pone.0059241
Descripción
Sumario: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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