Young Bae Park

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 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.

A Text Mining Approach to Find Patterns Associated with Diseases and Herbal Materials in Oriental Medicine

Currently, in Oriental Medicine, obtaining the statistical backgrounds is a very important and challenging issue to be authorized as the evidence-based medical science. Medicinal treatment is one of main part in Oriental Medicine, and it has some difficulties to specify the effectiveness of herbs because of its own theoretical basis and practical experience. The main purpose of this study is to clarify the relationship between herbal materials and efficacy of remedies in Bangyakhappyeon which is one of the representative textbook in Oriental Medicine with a text mining approach. We adopted an association rule induction combined with the network analysis and found useful and informative relationships between the symptoms and herbal materials.