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摘要:
Objective:This study aimed to collect,sort out and excavate the literature on the diagnosis and treatment of insomnia in Chinese Medical Code,and to explore the law of internal administration of traditional Chinese medicine in the treatment of insomnia.Methods:We used"Chinese Medical Code"as the source of data retrieval,"insomnia","not sleepy","no sleeping"and"eye not sleeping"as the key words,and excluded temporary insomnia,physiological insomnia,insomnia caused by other diseases,and excluded other methods such as acupuncture and massage,the medical cases.Prescriptions of insomnia treated with traditional Chinese medicine were screened out.The database was established by using Microsoft excel 2010.Descriptive statistics were used to analyze the frequency,menstruation of nature,taste and efficacy of traditional Chinese medicine.We analyzed the association rules between drugs and mined the rules of prescriptions by the Apriori algorithm in SPSS Modeler 14.1.Results:A total of 147 prescriptions,138 traditional Chinese medicines,20 pairs of core drugs,57 common drug combinations and 3 core pharmaceuticals were included.The basic prescription is:Suan Zao Ren,Bai Zi Ren,Fu Shen,Fu Ling,Yuan Zhi,Dang Gui,Gan Cao(Zhi).Conclusion:In summary,according to the drug analysis above,the main disease of insomnia is in the heart,involving the liver,spleen and kidney.Because it involves different viscera and syndrome,the methods of treatment are also different.However,there is a basic pathogenesis,that’s the loss of mental nourishment.By excavating the law of the use of traditional Chinese medicine in the treatment of insomnia on the Chinese Medical Code,we expect that it can guide the treatment of insomnia.
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篇名 The law of oral traditional Chinese medicine for insomnia based on Chinese medical code
来源期刊 TMR医学数据挖掘 学科 工学
关键词 INSOMNIA LITERATURE mining medicine LAW CHINESE MEDICAL CODE
年,卷(期) 2019,(4) 所属期刊栏目
研究方向 页码范围 160-168
页数 9页 分类号 TP3
字数 语种
DOI
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研究主题发展历程
节点文献
INSOMNIA
LITERATURE
mining
medicine
LAW
CHINESE
MEDICAL
CODE
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
TMR医学数据挖掘
季刊
2624-1587
天津市河东区大直沽中路伯苓大厦B座906
出版文献量(篇)
40
总下载数(次)
2
总被引数(次)
0
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