基于文本挖掘技术分析治疗肺癌的中医用药规律

郭玉明; 姜淼; 郑光; 郭洪涛; 吕爱平

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基于文本挖掘技术分析治疗肺癌的中医用药规律

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- 基于文本挖掘技术分析治疗肺癌的中医用药规律
- Regularity for Lung Cancer Treatnrent by Traditional Chinese Medicine Analyzed with Text Mining Technique
- 中国实验方剂学杂志 2011年17卷第16期页码：277-280
- 作者机构：
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- 基金信息：
  
  国家"十一五"科技支撑计划项目(2006BAI04A10);科技部创新方法知识体系建设项目(2008IM020900);国家自然科学基金项目(30825047,30902003);中国中医科学院自主选题项目(Z0134)
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- 纸质出版日期：2011
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郭玉明, 姜淼, 郑光, 等. 基于文本挖掘技术分析治疗肺癌的中医用药规律[J]. 中国实验方剂学杂志, 2011,17(16):277-280.

GUO Yu-ming, JIANG Miao, ZHENG Guang, et al. Regularity for Lung Cancer Treatnrent by Traditional Chinese Medicine Analyzed with Text Mining Technique[J]. Chinese journal of experimental traditional medical formulae, 2011, 17(16): 277-280.
郭玉明, 姜淼, 郑光, 等. 基于文本挖掘技术分析治疗肺癌的中医用药规律[J]. 中国实验方剂学杂志, 2011,17(16):277-280. DOI：

GUO Yu-ming, JIANG Miao, ZHENG Guang, et al. Regularity for Lung Cancer Treatnrent by Traditional Chinese Medicine Analyzed with Text Mining Technique[J]. Chinese journal of experimental traditional medical formulae, 2011, 17(16): 277-280. DOI：

摘要

目的: 分析治疗肺癌的常用中医用药规律

为临床应用提供参考依据。方法: 采用一维敏感字频数统计方法等技术

统计分析常用中药用药频率及药物协同关系规律

绘制协同药物网络图

抽取其中三层进行分析讨论。结果: 中药频数分析显示人参、黄芪等补益药物为治疗肺癌首要核心用药

中药协同关系分析显示治疗肺癌药物按照益气养阴、健脾化痰、解毒消积的规律分布。结论: 常用中药用药规律与病因病机相符

对临床应用具有一定指导意义

文本挖掘技术可以为中医药研究提供技术支持。

Abstract

Objective: To analyze the regularity of treating lung cancer with traditional Chinese medicine (TCM) herbs

and supply a foundation for the clinical practice. Method: All the references searched from Chinese biomedical literature database (CBM) were analyzed with one dimension sensitive character frequencies analysis. Then a co-existed herbs network was set up. The final analysis included three of all the networks. Result: Ginseng (Radix Ginseng) and Milkvetch Root (Radix Astragali) were the primary tonic herbs in treating lung cancer. The regularity of prescriptions was consistent to therapeutic principle of supplementing qi and nourishing yin

strengthening the spleen and reducing phlegm

and removing the toxic and stagnation. Conclusion: The regularity was consistent to the etiology and pathogenesis of lung cancer. And it will be useful for the clinical application. Text mining could be used as a reliable tool of TCM research.

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