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基于国医大师周仲瑛临证肝胆医案的经验解构研究 被引量:19

Study on TCM master ZHOU Zhong-ying's clinical experience in treating liver and gallbladder diseases based on his proven cases
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摘要 目的:基于中医本体特色,引入文本挖掘法并改进研究模式,结合原始医案数据挖掘分析,形成医案解构,从中分析周仲瑛教授临床诊治肝胆系统疾病经验。方法:对周仲瑛教授临证肝胆系统疾病的医案进行解构分析,并结合数据挖掘分析运用规律。结果:本次研究涉及病例83例,108诊次,中医病种9大类、涉及病机130条,药物281种。"胁痛"占最高频次,病机以"湿热瘀郁"为主,舌象"苔黄薄腻""质暗红"为主,脉象"细""滑"居多,中药"生地""麦冬"频次较高。结论:周仲瑛教授辨治肝胆病着眼于调养肝脾,肝脾两伤是关键,用药特别重视维护肝阴,体现了"治肝重于治脾"的治疗原则。 Objective:Based on the characteristics of TCM ontology,text mining method and improved research model,and original basis of data mining analysis,the proven cases deconstruction was form to analyze TCM master ZHOU Zhong-ying's clinical experience in treating liver and gallbladder diseases.Methods:The proven cases of professor ZHOU was deconstructed and analyzed,and the application rule was analyzed by combining data mining method.Results:The study involved 83 cases of patients,108 diagnosis times,101 kinds of diseases,130 pathogenesis,and 281 kinds of drugs.Hypochondriac pain accounted for the highest frequency,the pathogenesis was given priority to dampness,heat,stasis,and depression,the tongue manifestation was given priority to dull-red tongue,the pulse manifestation was given priority to thready and slippery pulse,and the drugs was given priority to unprocessed rehmannia root and dwarf lilyturf tuber.Conclusion:Professor ZHOU Zhong-ying's treatment on h liver and gallbladder diseases mainly focused on maintenance liver and spleen,both injury of spleen and liver was the key to liver and gallbladder diseases.His medications given priority to maintaining liver yin,and his therapeutic principle embodied 'treating liver is more important than treating the spleen'.
出处 《中华中医药杂志》 CAS CSCD 北大核心 2017年第4期1814-1817,共4页 China Journal of Traditional Chinese Medicine and Pharmacy
基金 江苏省高等学校大学生创新训练项目(No.201413981005Y) 江苏省2013年度普通高校研究生科研创新计划项目(No.CXZZ13_0610) 江苏省科技型企业重点研发计划(No.BC2015022)~~
关键词 周仲瑛 经验分析 肝胆系统 频次统计 数据挖掘 ZHOU Zhong-ying Clinical experience Liver and gallbladder system Frequency statistics Data mining
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