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Research on Component Law of Chinese Patent Medicine for Anti-influenza and Development of New Recipes for Anti-influenza by Unsupervised Data Mining Methods

Objective:To analyze the component law of Chinese patent medicines for anti-influenza and develop new prescriptions for anti-influenza by unsupervised data mining methods. Methods: Chinese patent medicine recipes for anti-influenza were collected and recorded in the database, and then the correlatio...

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Published in:Journal of traditional Chinese medicine 2010-12, Vol.30 (4), p.288-293
Main Author: 唐仕欢 陈建新 李耿 吴宏伟 陈畅 张娜 高娜 杨洪军 黄璐琦
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description Objective:To analyze the component law of Chinese patent medicines for anti-influenza and develop new prescriptions for anti-influenza by unsupervised data mining methods. Methods: Chinese patent medicine recipes for anti-influenza were collected and recorded in the database, and then the correlation coefficient between herbs, core combinations of herbs and new prescriptions were analyzed by using modified mutual information, complex system entropy cluster and unsupervised hierarchical clustering, respectively. Results: Based on analysis of 126 Chinese patent medicine recipes, the frequency of each herb occurrence in these recipes, 54 frequently-used herb pairs, 34 core combinations were determined, and 4 new recipes for influenza were developed. Conclusion: Unsupervised data mining methods are able to mine the component law quickly and develop new prescriptions.
doi_str_mv 10.1016/S0254-6272(10)60058-1
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subjects Antiviral Agents - analysis
Antiviral Agents - therapeutic use
Chemistry, Pharmaceutical
Data Mining
Drugs, Chinese Herbal - analysis
Drugs, Chinese Herbal - therapeutic use
Humans
Influenza A Virus, H1N1 Subtype - drug effects
Influenza A Virus, H1N1 Subtype - physiology
Influenza, Human - drug therapy
Influenza, Human - virology
Nonprescription Drugs - analysis
Nonprescription Drugs - therapeutic use
中国专利
中成药
基于构件
挖掘方法
新处方
新配方
title Research on Component Law of Chinese Patent Medicine for Anti-influenza and Development of New Recipes for Anti-influenza by Unsupervised Data Mining Methods
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