| 引用本文:周己扬1，王嫱2，刘欣3，张会永3，刘宝文3.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[J].世界中医药,2016,(03):. |
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| 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 |
| Analysis of Professor Liu Baowen’s Administration Features in the Treatment of Myeloproliferative Disease Based on Data Mining |
| 投稿时间：2015-05-07 |
| DOI：10.3969/j.issn.1673-7202.2016.03.047 |
| 中文关键词: 数据挖掘 名老中医经验 骨髓增殖性疾病 关联规则 |
| English Keywords:Data Mining TCM Experience Myeloproliferative Disease Association Analysis |
| 基金项目: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） |
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| 中文摘要: |
| 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。 |
| English Summary: |
| To analyze professor Liu Baowen’s administration features on treating myeloproliferative applying data mining technology. Methods: A database was set up including 28 myeloproliferative cases (149 clinic consultations) treated by Prof. Liu. Frequency of administration and correlation of herbs was tested. Analysis was performed by SPSS Modeler. Results: The herbs that were most frequently used by Prof. Liu on treating MPD were Chenpi, Gancao, Dansheng, Danggui, Nuxi, Shudi, Shanyao, Honghua. There were 43 parts of herbs tested from the correlated analysis, of 12 pairs corresponded to Prof. Liu’s experience. Besides, we found 5 new pairs: Dansheng and Chaihu, Chaihu and Niuxi, Niuxi and Dangsheng, Puhuang and Dangsheng, Danggui and Qingdai. Conclusion: Prof. Liu treated MPD mainly by promoting blood circulation and removing blood stasis, and also combined with generating qi and blood herbs. The result of data mining basically reflects Prof. Liu’s medical experience on treating MPD. |
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