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Based On Data Mining, Professor Xu Bin's Medication Rule Analysis For The Treatment Of Benign Thyroid Nodules

Posted on:2021-04-27Degree:MasterType:Thesis
Country:ChinaCandidate:L J YuFull Text:PDF
GTID:2434330614457725Subject:Integrative Medicine
Abstract/Summary:PDF Full Text Request
Purpose:To retrospectively collect and sort out the medical records of Professor Xu Bin’s treatment of benign thyroid nodule disease,and use data mining software to analyze the basic prescriptions and drug compatibility of Professor Xu Bin’s treatment of thyroid nodule,and try to discover the clinical medicine of Xu Shi’s treatment of diseases Regularly,to understand Xu Shi’s experience in treating thyroid nodule disease,to make the experience of famous old Chinese medicine better,and to provide clinical guidance for other scholars.Material and method: This study collected 140 patients,426 patients’ prescriptions,collected medical records,used EXECL software to count the basic information of patients and prescriptions,and established a database,using IBM SPSS Statistics 22.0 software for frequency and cluster analysis,and IBM SPSS MODELER 18.0 software for association rule analysis,so as to excavate Xu Shi’s medication regularity in treating Thyroid nodule disease,xu’s experience in the treatment of Thyroid nodule disease was summarized.Results:1.This data includes 140 patients,including a total of 426 visits including returning patients,including 35 male patients and 105 female patients,aged 18-73 years.193 cases of liver stagnation and phlegm coagulation syndrome,48 cases of spleen deficiency phlegm coagulation syndrome,90 cases of liver stagnation qi stagnation syndrome,46 cases of qi yin stagnation syndrome,46 cases of qi and yin deficiency syndrome,other)49 cases.2.Statistics on the use of medicines: the number of Chinese medicines involved is 132,the total number of prescriptions is 426,the total frequency of medicines is 7,100 times,and 31 kinds of high-frequency medicines are calculated based on the medicines with a frequency greater than 15%.Medicine,tonic medicine,phlegm relieving medicine,tranquilizer medicine,promoting blood circulation and removing blood stasis medicine.3.Using cluster analysis,the first class of drugs are Magnolia officinalis,Astragalus membranaceus,Fructus Aurantii,Codonopsis,Chenpi,Atractylodes,Polygala,Licorice,Shengdihuang,Poria,Sour Jujube,Bamboo Ru,Hehuan,Scutellaria Baicalensis,Cistanche;The second class of drugs are melons,oysters,turmeric,prunella,pinellia,Bupleurum,Ligustrum lucidum,Paeonia lactiflora,Cuscuta chinensis,Eclipta prostrata;the third class is Yanhusuo,Coriander shell,Chuanxiong.4.Association analysis was used to analyze the association of two drugs and three drugs for high frequency drugs based on the principles of 90% confidence,0.6 support,and 2 maximum front term.The main results were as follows: The commonly used medicines such as Bupleurum-yujin,Baiji-yujin,Bupleurum-xiangxiang,Yujin-xiangfu,Baiji-xiangfu and so on.The three drug-related results were mainly Chaihu-Yujin,Baiji,Yujin-Chaihu,Baiji,Baiji-Chaihu,Yujin,Chaihu-Xiangfu,Yujin,Baiji-Xiangfu,Yujin,Bupleurum-Xiang Fu,Bai Zhi,Yu Jin-Xiang Fu,Bai Zhi,Yu Jin-Xiang Fu,Bupleurum,Bai Zhi-Xiang Fu,Bupleurum and so on.Conclusion:1.The patient’s disease is the thyroid in the neck,but its occurrence is closely related to the liver meridian.2.Professor Xu Bin treats thyroid nodules based on syndrome differentiation,which is divided into four main syndrome types: liver stagnation phlegm coagulation syndrome,spleen deficiency phlegm coagulation syndrome,liver fire exuberant syndrome,and qi yin syndrome.3.The occurrence of benign thyroid nodules is clinically closely related to liver qi stagnation.The general principles of treatment are regulating qi and activating blood circulation,relieving liver and softening liver,and dissolving phlegm.4.Professor Xu Bin has been treating thyroid nodules for many years,advocating "treatment from the liver".
Keywords/Search Tags:thyroid nodules, data mining, association rules, cluster analysis
PDF Full Text Request
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