Analysis on the Law of External Treatment of Saposhnikovia Divaricata Based on Data Mining

DOI

10.2991/seeie-19.2019.60How to use a DOI?

Keywords

Saposhnikovia divaricata; law of medication; data mining; compound prescription; association rule

Abstract

Objective: To analyze the medication rule of compound prescription containing Saposhnikovia divaricata for external treatment, and to provide reference for guiding clinical medication and research and development of new prescriptions. Method: Taking the periodical literature collected by CNKI as the data source, and using Excel 2013 and Clementine12.0 statistical software as tools, the statistical processing and association rule analysis of traditional Chinese medicine included in the standard are carried out.Result:Among all the compounds included in the standard, the top five Chinese medicines with the highest cumulative frequency are Saposhnikovia divaricata (45times,100.0%), Sophora flavescens (22times,48.9%), Phellodendron amurense (19times, 42.2%), Glycyrrhiza uralensis (15times,33.3%) and Dictamnus dasycarpus (14 times,31.1%).By analyzing association rules of compound prescription containing Saposhnikovia divaricata,12 common drug pairs were obtained. There are 7 kinds of common clinical diseases of traditional Chinese medicine in the treatment of diseases. The association rule analysis found that 8 kinds of combination of drug pairs with the highest association intensity for anorectal diseases and 8 kinds of combination of drug pairs with the highest association intensity for skin diseases. Conclusion: Through the analysis of compound prescription containing Saposhnikovia divaricata, the medication rule and compatibility characteristics of Saposhnikovia divaricata in external treatment for different diseases are reflected, which provides theoretical support for " simultaneous treatment of different diseases". Mathematical statistics is an important tool for analysis of medication rule in traditional Chinese medicine and provides modern research direction for guiding clinical medication.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - En Lei
AU  - Jing Yang
AU  - Mingsan Miao
PY  - 2019/05
DA  - 2019/05
TI  - Analysis on the Law of External Treatment of Saposhnikovia Divaricata Based on Data Mining
BT  - Proceedings of the 2019 2nd International Conference on Sustainable Energy, Environment and Information Engineering (SEEIE 2019)
PB  - Atlantis Press
SP  - 260
EP  - 262
SN  - 2352-5401
UR  - https://doi.org/10.2991/seeie-19.2019.60
DO  - 10.2991/seeie-19.2019.60
ID  - Lei2019/05
ER  -