基于数据挖掘的刘宝文教授治疗骨髓增殖性疾病用药特色分析

发布时间：2018-11-04 18:21

【摘要】：目的:采用数据挖掘技术分析刘宝文教授中医药治疗骨髓增殖性疾病用药特色。方法:对刘宝文教授治疗骨髓增殖性疾病的28例(149诊次)患者病案建立信息数据库。采用SPSS Modeler作为数据挖掘平台,分析用药频次,对药物进行关联分析,绘制关联规则网状图。结果:刘宝文教授中医药治疗骨髓增殖性疾病常用药物22味,核心用药8味,分别为陈皮、甘草、丹参、当归、牛膝、熟地黄、山药、红花。关联分析发现43组药对,其中11组药对与刘宝文教授经验相符合,数据挖掘发现5组新药对,分别为丹参与柴胡、柴胡与牛膝、蒲黄与丹参、牛膝与丹参、当归与青黛。结论:刘宝文教授治疗骨髓增殖性疾病以活血化瘀药物为主,配合补气、补血、滋阴等药物。数据挖掘的结果基本体现了刘宝文教授治疗骨髓增殖性疾病的学术思想与用药特色。
[Abstract]:Objective: to analyze the drug characteristics of Professor Liu Baowen in the treatment of bone marrow proliferative diseases by using data mining technology. Methods: 28 cases (149 visits) of bone marrow proliferative diseases were treated by Professor Liu Baowen. SPSS Modeler is used as the data mining platform to analyze the frequency of drug use, to analyze the association of drugs, and to draw the network map of association rules. Results: professor Liu Baowen used 22 kinds of drugs and 8 kinds of core drugs in treating bone marrow proliferative diseases. They were Chen Pei, liquorice, Salvia miltiorrhiza, Angelica sinensis, Achyranthes bidentata, Radix Rehmanniae, Chinese yam, Carthamus tinctorius. Correlation analysis found 43 groups of drug pairs, of which 11 groups were consistent with Professor Liu Baowen's experience. Five groups of new drug pairs were found by data mining, respectively: Dan participating in Bupleurum, Bupleurum and Achyranthes bidentata, Puhuang and Salvia miltiorrhiza, Achyranthes bidentata and Radix Salviae Miltiorrhizae, Angelica sinensis and Qing Dai. Conclusion: professor Liu Baowen in the treatment of bone marrow proliferative diseases mainly by promoting blood circulation and removing blood stasis, combined with drugs such as tonifying qi, reinforcing blood, nourishing yin and so on. The results of data mining basically reflect Professor Liu Baowen's academic thoughts and characteristics of drug use in the treatment of bone marrow proliferative diseases.
【作者单位】：辽宁中医药大学;沈阳国际旅行卫生保健中心;辽宁中医药大学附属医院血液科;
【基金】：国家中医药管理局“十二五”中医药重点学科中医血液病学建设项目(编号:国中医药人教发(2012)32号)
【分类号】：R249;R259

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