Text Mining on Chinese Herbal Medicine Rule Exploration for Ovarian Cyst

DOI

10.2991/icassr.2013.58How to use a DOI?

Keywords

text mining; ovarian cyst; medicine regularity

Abstract

Ovarian cyst (OC) is one of the biggest concerns of women around the world. With the increase in the number of cases of OC, it seems like no woman is safe from this dreaded disease. Traditional Chinese Medicine (TCM) has its advantage in OC management, while due to the complexity and opacity; it is hard to clarify the rules of Chinese herbs. Text mining is a useful method to explore the regularity; we put this technology in principle research of Chinese herbal medicine (CHM) and associated it with patterns of TCM in OC treatment. The results we obtained from this study:Fuling, Guizhi, Taoren, Danpi, Chishao are top five herbs frequently used in OC. The pattern of Qi stagnation and blood stasis is the No.1 syndrome, which is highly coincided with the top lists of the herbs. Conclusion: Text mining is a practical technology, which can help with the research field of medicine regularity and assist the physician with clinical decision; the future research shall be benefited from the outcome mined out by this technology.

Copyright

© 2013, 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/).

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TY  - CONF
AU  - Dan He
AU  - Aiping Lu
AU  - Miao Jiang
AU  - Guang Zheng
AU  - Ning Zhao
AU  - Minzhi Wang
PY  - 2013/08
DA  - 2013/08
TI  - Text Mining on Chinese Herbal Medicine Rule Exploration for Ovarian Cyst
BT  - Proceedings of the 2013 International Conference on Applied Social Science Research (ICASSR-2013)
PB  - Atlantis Press
SP  - 224
EP  - 226
SN  - 1951-6851
UR  - https://doi.org/10.2991/icassr.2013.58
DO  - 10.2991/icassr.2013.58
ID  - He2013/08
ER  -