FOLLOWUS
Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods
- Chinese Journal of Integrative Medicine Vol. 19, Issue 8, Pages: 621-628(2013)
- Affiliations：
1. School of Information Management, Shandong University of Traditional Chinese Medicine,Jinan,China
2. Key Laboratory of Marine Drugs, Ministry of Education, Marine Drug and Food Institute, Ocean University of China,Shandong Province,Qingdao,China
3. Department of Neurology, Qingdao Municipal Hospital,Shandong Province,Qingdao,China
- Author bio：
- Funds：Supported by the Major State Basic Research Development Program of China (973 Program, No. 2007CB512601)
DOI：10.1007/s11655-012-1090-2
CLC：Published：2013，
Published Online：19 May 2012，
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Fu, Xj., Song, Xx., Wei, Lb. et al. Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods., Chin. J. Integr. Med. 19, 621–628 (2013). https://doi.org/10.1007/s11655-012-1090-2
Xian-jun Fu, Xu-xia Song, Lin-bo Wei, et al. Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods. [J]. Chinese Journal of Integrative Medicine 19(8):621-628(2013)
Fu, Xj., Song, Xx., Wei, Lb. et al. Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods., Chin. J. Integr. Med. 19, 621–628 (2013). https://doi.org/10.1007/s11655-012-1090-2 DOI：
Xian-jun Fu, Xu-xia Song, Lin-bo Wei, et al. Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods. [J]. Chinese Journal of Integrative Medicine 19(8):621-628(2013) DOI： 10.1007/s11655-012-1090-2.
摘要
To provide the distribution pattern and compatibility laws of the constituent herbs in prescriptions
for doctor’s convenience to make decision in choosing correct herbs and prescriptions for treating respiratory disease. Classical prescriptions treating respiratory disease were selected from authoritative prescription books. Data mining methods (frequent itemsets and association rules) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions. A total of 562 prescriptions were selected to be studied. The result exhibited that
Radix glycyrrhizae was the most frequently used in 47.2% prescriptions
other frequently used were Semen armeniacae amarum
Fructus schisandrae Chinese
Herba ephedrae
and Radix ginseng. Herbal ephedrae was always coupled with Semen armeniacae amarum with the confidence of 73.3%
and many herbs were always accompanied by Radix glycyrrhizae with high confidence. More over
Fructus schisandrae Chinese
Herba ephedrae and Rhizoma pinelliae was most commonly used to treat cough
dyspnoea and associated sputum respectively besides Radix glycyrrhizae and Semen armeniacae amarum. The prescriptions treating dyspnoea often used double herb group of Herba ephedrae & Radix glycyrrhizae
while prescriptions treating sputum often used double herb group of Rhizoma pinelliae & Radix glycyrrhizae and Rhizoma pinelliae & Semen armeniacae amarum
triple herb groups of Rhizoma pinelliae & Semen armeniacae amarum & Radix glycyrrhizae and Pericarpium citri reticulatae & Rhizoma pinelliae & Radix glycyrrhizae. The prescriptions treating respiratory disease showed common compatibility laws in using herbs and special compatibility laws for treating different respiratory symptoms. These principle patterns and special compatibility laws reported here could be useful for doctors to choose correct herbs and prescriptions in treating respiratory disease.
Abstract
To provide the distribution pattern and compatibility laws of the constituent herbs in prescriptions
for doctor’s convenience to make decision in choosing correct herbs and prescriptions for treating respiratory disease. Classical prescriptions treating respiratory disease were selected from authoritative prescription books. Data mining methods (frequent itemsets and association rules) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions. A total of 562 prescriptions were selected to be studied. The result exhibited that
Radix glycyrrhizae was the most frequently used in 47.2% prescriptions
other frequently used were Semen armeniacae amarum
Fructus schisandrae Chinese
Herba ephedrae
and Radix ginseng. Herbal ephedrae was always coupled with Semen armeniacae amarum with the confidence of 73.3%
and many herbs were always accompanied by Radix glycyrrhizae with high confidence. More over
Fructus schisandrae Chinese
Herba ephedrae and Rhizoma pinelliae was most commonly used to treat cough
dyspnoea and associated sputum respectively besides Radix glycyrrhizae and Semen armeniacae amarum. The prescriptions treating dyspnoea often used double herb group of Herba ephedrae & Radix glycyrrhizae
while prescriptions treating sputum often used double herb group of Rhizoma pinelliae & Radix glycyrrhizae and Rhizoma pinelliae & Semen armeniacae amarum
triple herb groups of Rhizoma pinelliae & Semen armeniacae amarum & Radix glycyrrhizae and Pericarpium citri reticulatae & Rhizoma pinelliae & Radix glycyrrhizae. The prescriptions treating respiratory disease showed common compatibility laws in using herbs and special compatibility laws for treating different respiratory symptoms. These principle patterns and special compatibility laws reported here could be useful for doctors to choose correct herbs and prescriptions in treating respiratory disease.
关键词
multi-herb recipescompatibility lawsrespiratory diseasedata mining methods
Keywords
multi-herb recipescompatibility lawsrespiratory diseasedata mining methods
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