Association rule mining and network analysis in oriental medicine

PLoS One. 2013;8(3):e59241. doi: 10.1371/journal.pone.0059241. Epub 2013 Mar 15.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Data Collection / methods
  • Data Collection / statistics & numerical data*
  • Data Mining / methods
  • Data Mining / statistics & numerical data*
  • Databases, Pharmaceutical / statistics & numerical data*
  • Drug Prescriptions
  • Humans
  • Medicine, East Asian Traditional*
  • Neural Networks, Computer
  • Plant Preparations / therapeutic use*
  • Republic of Korea

Substances

  • Plant Preparations

Grants and funding

This work was support in part by Brain Korea 21. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study.