Analysis on the Medication Rule of Proprietary Chinese Medicines in Chonglou Listed in "CNKI" and "Standards Issued by the Ministry of Traditional Chinese Medicine"
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DOI: 10.23977/meb.2019.1212
Author(s)
Yangbo Li,Ming Bai, Mingsan Miao
Corresponding Author
Yangbo Li
ABSTRACT
To study the application law of toxic Chinese medicine chonglou, and to provide reference for guiding clinical drug use and new prescription development.With "chonglou" and "clinical" as keywords, the clinical prescription about chonglou was searched on cnki, and the prescription about chonglou was searched in the "standards for the ministry of traditional Chinese medicine", and then summarized and sorted. Excel 2019 and SPSS Clementine12.0 statistical software were used to conduct statistical processing and association rule analysis on the Chinese medicine included in the standard. Among all the formulae included in the standard, the top six appeared frequently were zhonglou (67 times, 100 %), licorice (19 times, 28.36 %), partridge (14 times, 20.90 %), angelica (14 times, 20.90 %), banzhilian (13 times, 19.40 %), panax notoginseng (13 times, 19.40 %).The high frequency Chinese medicine taste is mainly bitter, xin and gan, appearing 10 times, 8 times and 7 times respectively.The drug was most common in cold and warm, appearing 6 and 5 times respectively.The main meridians were spleen meridians (9 times, 20%), lung meridians (9 times, 20%) and liver meridians (7 times, 15.6%).Through the analysis of the association rules of the formula containing zhonglou, 7 kinds of commonly used drugs were obtained. The main functions of the formula containing zhonglou were detumescence and analgesia, promoting blood circulation and removing blood stasis, clearing heat and detoxifying, and anti-tumor. Through the method of mathematical statistics and related software to analyze formula containing chonglou, digging out toxic Chinese medicine clinical use chonglou compatibility features, provide more scientific guidance for clinical use.
KEYWORDS
Chonglou, Toxic Chinese Medicine, Data Mining