基于信息挖掘技术总结谢海洲治疗血管性痴呆的遣方用药经验

Experience of Selecting Drugs on Treating Vascular Dementia by Theory of Traditional Chinese Medicine Based on the Information Mining Technology

目的:对谢海洲教授辨证论治血管性痴呆临床遣方用药经验进行初步总结。方法:利用现代计算机数据挖掘技术,建立谢海洲临床诊疗信息采集模块,采集其辨证论治血管性痴呆的临床诊疗信息并形成数据库,共采集录入门诊病例85例212诊次,分析和挖掘研究其临床思维模式和遣方用药规律。结果:谢海洲教授治疗血管性痴呆多选择补虚开窍、祛瘀化痰方剂,补虚、活血化瘀、化痰的药物类别出现频次达50.15%。结论:通过现代信息挖掘技术对谢海洲教授辨证论治血管性痴呆的遣方用药经验进行系统整理研究,为今后的深入研究奠定了基础。

Objetive：To preliminarily summarise Professor XIE Hai-zhou＇ s experience of selecting drugs on treating vascular dementia by theory of traditional Chinese medicine. Methods ： This study is relied on the Beijing science plan based on data-mining technology in traditional Chinese medicine study of clinical experience. We used modem computer datamining technology to build director Professor XIE Hai-zhou＇ s clinical information collection module, data acquisition of vascular dementia clinical information form database. We collected clinical diagnosis and treatment of Professor XIE Haizhou for 85 cases of vascular dementia of 212 total visits. We preliminarily analysed and researched Professor XIE Haizhou＇ s clinical thinking mode and law of selecting drugs, diagnosis and treatment experience. Results： Confirm the Professor XIE Hai-zhou＇ s evolution laws related to the pathogenesis of vascular dementia. Professor XIE Hai-zhou most choose tonify deficiency agent,sobriety agent,blood-activating and stasis-dissolving agent,phlegm agent. The frequency of above agents is as high as 50. 15%. Conclusion： This study through the modern technology of information mining on Professor XIE Hai-zhou systematized study of the experience of the treatment based on syndrome differentiation of vascular dementia, laid the foundation for future in-depth research.