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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.
Chin J Integr Med. 2013 Aug; 19(8):621-8.CJ

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.

Authors+Show Affiliations

School of Information Management, Shandong University of Traditional Chinese Medicine, Jinan 250355, China. xianxiu@hotmail.comNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

22610955

Citation

Fu, Xian-Jun, et al. "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, no. 8, 2013, pp. 621-8.
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. 2013;19(8):621-8.
Fu, X. J., Song, X. X., Wei, L. B., & Wang, Z. G. (2013). 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, 19(8), 621-8. https://doi.org/10.1007/s11655-012-1090-2
Fu XJ, 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. 2013;19(8):621-8. PubMed PMID: 22610955.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods. AU - Fu,Xian-Jun, AU - Song,Xu-Xia, AU - Wei,Lin-Bo, AU - Wang,Zhen-Guo, Y1 - 2012/05/19/ PY - 2010/10/21/received PY - 2012/5/22/entrez PY - 2012/5/23/pubmed PY - 2014/4/8/medline SP - 621 EP - 8 JF - Chinese journal of integrative medicine JO - Chin J Integr Med VL - 19 IS - 8 N2 - 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. SN - 1672-0415 UR - https://www.unboundmedicine.com/medline/citation/22610955/Study_of_the_distribution_patterns_of_the_constituent_herbs_in_classical_Chinese_medicine_prescriptions_treating_respiratory_disease_by_data_mining_methods_ L2 - https://dx.doi.org/10.1007/s11655-012-1090-2 DB - PRIME DP - Unbound Medicine ER -