Exploring Relationship Among Symptom, Pattern and Medication Regularity of Hypertension Based on Text Mining Technology

HE Dan; JIANG Miao; ZHENG Guang; ZHANG Chi; YANG Jing; ZHAO Ning; SHEN Shan-shan; BIAN Yan-qin; LV Ai-ping

doi:10.13422/j.cnki.syfjx.2014190214

您当前的位置：

首页 >

文章列表页 >

Exploring Relationship Among Symptom, Pattern and Medication Regularity of Hypertension Based on Text Mining Technology

更新时间：2024-01-04

- Exploring Relationship Among Symptom, Pattern and Medication Regularity of Hypertension Based on Text Mining Technology
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 20, Issue 19, Pages: 214-216(2014)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.13422/j.cnki.syfjx.2014190214
  CLC： R259
- Published：2014
- 稿件说明：
移动端阅览
HE Dan, JIANG Miao, ZHENG Guang, et al. Exploring Relationship Among Symptom, Pattern and Medication Regularity of Hypertension Based on Text Mining Technology[J]. Chinese journal of experimental traditional medical formulae, 2014, 20(19): 214-216.
DOI：

HE Dan, JIANG Miao, ZHENG Guang, et al. Exploring Relationship Among Symptom, Pattern and Medication Regularity of Hypertension Based on Text Mining Technology[J]. Chinese journal of experimental traditional medical formulae, 2014, 20(19): 214-216. DOI： 10.13422/j.cnki.syfjx.2014190214.

摘要

目的：利用文本挖掘技术探索高血压病中医证治方药规律。方法：在中国生物医学文献服务系统中收集治疗高血压的文献数据，采用基于敏感关键词频数统计的数据分层算法，挖掘高血压中医症状、证候以及用药规律。这些规律通过一维频次表及二维网络图进行展示。结果：高血压的最常见症状为头痛（2 650次），头晕（1 734次），证候以肝阳上亢为主，其次为阴虚阳亢和肝火亢盛，病变涉及肝、肾等脏腑。治法方面，为平肝潜阳，补益肝肾，并与活血化瘀法配合使用。汤药以天麻钩藤饮，钩藤饮以及半夏白术天麻汤为最常用。中药以天麻、钩藤应用最多。结论：文本挖掘能够比较客观地总结中医证治方药规律，为临床应用提供有益的探索和参考。

Abstract

Objective: This investigation aimed at applying data mining technology to explore the relationship among symptoms

patterns and medication regularity of hypertension. Method: All the relative literatures were collected from sinomed database

then subject to data slicing algorithm to mine out the relationship among symptoms

patterns and medication regularity of hypertension. Result: The most common symptoms of hypertension are headache(2 650)

dizziness(1 734)

and the patterns are manifested as liver Yang hyperactivity

Yin deficiency and Yang excess as well as upward liver fire

the most injured organ are liver and kidney.Treating methods would be to suppress the upward liver yang and strengthen liver and kidney which should be accompanied by activating Qi and Blood.The most common applied herbs are Gastrodiae Rhizoma and Uncariae Ramulus Cum Uncis. Conclusion: Text mining is a branch of data mining and a practicable technology which can be used in the field of traditional Chinese medicine(TCM).Through putting this technology in the research of TCM clinical practice

both doctors and patients could benefit from it.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Exploring Association Rules of Traditional Chinese Medicine'Syndrome-symptom-formula-herb’in Chronic Glomerulonephritis by a Novel Text Mining Approach

Exploring Association Rules of Syndrome and Herbal Medicine within Framework of Traditional Chinese Medicine on Coronary Heart Disease Through Text Mining Approach

Exploring Association Rules of Traditional Chinese Medicine ‘Syndrome-symptom-formula-herb’ in Chronic Glomerulonephritis by a Novel Text Mining Approach

Efficacy of Fufang Lingjiao Jiangya Pills with Different Proportions of Goat Horn Replacing Antelope Horn on Spontaneous Hypertensive Rats

Characterization of Animal Models of Type 2 Diabetes Mellitus with Hypertension Based on Clinical Symptoms in Traditional Chinese and Western Medicine

Related Author

ZHAN Jun-ping

LV Cheng

HE Xiao-juan

LV Ai-ping

TIAN Jing-ping

TAN Yong

CAI Feng

ZHAN Jun-ping1

Related Institution

Shanghai University of Traditional Chinese Medicine

Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences

School of Information Science and Engineering Technology,Lanzhou University

School of Pharmaceutical Sciences， Zhejiang Chinese Medical University

Guang'anmen Hospital， China Academy of Chinese Medical Sciences

AI问答

Postal code：100700
Tel：010-84076882 Email：syfjx_2010@188.com
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备11006657号-10 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰