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Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods

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Abstract

Objective

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.

Methods

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.

Results

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.

Conclusions

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.

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Authors and Affiliations

  1. School of Information Management, Shandong University of Traditional Chinese Medicine, Jinan, 250355, China

    Xian-jun Fu  (付先军) & Zhen-guo Wang  (王振国)

  2. Key Laboratory of Marine Drugs, Ministry of Education, Marine Drug and Food Institute, Ocean University of China, Qingdao, Shandong Province, 266000, China

    Xian-jun Fu  (付先军) & Lin-bo Wei  (魏陵博)

  3. Department of Neurology, Qingdao Municipal Hospital, Qingdao, Shandong Province, 266011, China

    Xu-xia Song  (宋旭霞)

Authors
  1. Xian-jun Fu  (付先军)
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  2. Xu-xia Song  (宋旭霞)
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  3. Lin-bo Wei  (魏陵博)
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  4. Zhen-guo Wang  (王振国)
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Corresponding author

Correspondence to Xian-jun Fu  (付先军).

Additional information

Supported by the Major State Basic Research Development Program of China (973 Program, No. 2007CB512601)

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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

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  • DOI: https://doi.org/10.1007/s11655-012-1090-2

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