基于方剂数据分析的“脾胃阳虚证”方药配伍规律研究

目的:探讨"脾胃阳虚证"方药配伍规律。方法:以《中医方剂大辞典》为线索,筛选治疗"脾胃阳虚证"方剂203首,采取"Excel数据透视表","SQL Server 2005_DMAddin关联规则","spss17.0因子分析"等方法,进行数据分析。结果:治疗"脾胃阳虚证"方剂中,温里药、补气药分别占整个用药23%、20%,而补阳药仅占用药2%;出现频次超过60次的药物是炙甘草、白术、人参、干姜、厚朴、附子等;关联性较为重要的药物是干姜、白术、人参、炙甘草、附子等;排名较前公因子分别代表"补气药"集合,"理气活血化湿药"集合,"温里药"集合等。结论:"脾胃阳虚证"治疗方剂由"温里药"、"补气药"配伍"理气药","芳香化湿药"等而成,基础方为"人参、白术、干姜、炙甘草、附子、诃子、茯苓、厚朴"。

基于方剂数据分析的“脾气虚证”与“脾胃气虚证”方药配伍规律比较

文章以《中医方剂大辞典》为线索,分别筛选治疗"脾气虚证"、"脾胃气虚证"的方剂54首、284首,采取"Excel数据透视表","SQL Server 2005_DMAddin关联规则","SPSS 17.0因子分析"等方法,探讨"脾气虚证"、"脾胃气虚证"用药配伍规律的异同。结果显示,"脾气虚证"、"脾胃气虚证"其治疗方剂同中有异,两者均以补气、消食药配伍理气、温里、祛湿药等组成,均以白术、陈皮为基础方。但"脾气虚证"方剂以补脾治本为主,喜用"人参";"脾胃气虚证"方剂以补脾、行气、渗湿、消食等同用,标本兼治,喜用"党参"。

基于方剂数据分析的“脾气血两虚证”存在情况及用药配伍规律研究

文章以《中医方剂大辞典》为线索,筛选治疗"脾虚证"方剂850首,采取"Excel数据透视表"、"SQL Server 2005_DMAddin关联规则"、"spss17.0因子分析"等方法,探讨"脾气血两虚证"存在情况及其用药配伍规律。结果显示,"脾气血两虚证"存在,其治疗方剂主要由补气药、补血药配伍利水渗湿药、补阴药、活血祛瘀药等组成,基础方为"人参、炙黄芪、山药、当归、白芍、炙甘草",核心配伍为"人参、当归"。

肺癌的中医治法及方药使用规律研究

目的:分析、总结肺癌的中医证型规律和方药使用规律,探索中医治疗肺癌的常规治法及常用药对。方法:收集到中医方药治疗肺癌的方剂213首,构建肺癌方剂库,运用频数统计及频繁集分析肺癌的中医证型规律和方药使用规律。结果:肺癌以气阴两虚、阴虚内热、脾虚痰湿、痰瘀互结等为主要证型。肺癌常用治法应为:化痰祛湿、清热解毒、活血化瘀、扶正固本(补气、滋阴、养血等)。肺癌用药以补虚药为第一位,其中气虚为最,之后为化痰药、祛湿药、清热药、活血化瘀药等。具体又以白术-黄芪补气,麦冬-沙参滋阴,半夏-陈皮化痰,白术-茯苓祛湿,白花蛇舌草-半枝莲清热解毒,当归-桃仁活血化瘀。结论:肺癌治疗当围绕气虚、阴虚、痰浊、水湿、热毒、血瘀等病机,以补气滋阴、化痰祛湿、清热解毒、活血化瘀为基本治法,以白术-黄芪,麦冬-沙参,半夏-陈皮,白术-茯苓,白花蛇舌草-半枝莲,当归-桃仁为常用药对,临症加减化裁。

中晚期非小细胞肺癌中医证型及方药使用规律研究

目的:分析中国期刊全文数据库(CNKI)1999~2019年中医药治疗中晚期非小细胞肺癌文献34篇中中医证型规律和方药使用规律,总结中医药治疗中晚期非小细胞肺癌的常用方法,进一步挖掘治疗新思路,为临床治疗提供参考。方法:应用中医传承辅助平台软件,构建中晚期肺癌证型及组方数据库,通过软件计算方法,对组方数据库进行证型分布、组方规律及新方分析等研究。结果:34篇文献共涉及中晚期非小细胞肺癌的证型27个,方剂96首,中药171味,常见证型有气阴两虚证、阴虚内热证、脾虚痰湿证、气血瘀滞证,常用药物有麦冬、白术、茯苓、党参、北沙参、黄芪、白花蛇舌草、半夏、陈皮、浙贝母、桔梗、当归、桃仁等。演化得到新处方组合8组。结论:中晚期非小细胞肺癌病机以气阴两虚为主,夹杂痰湿、瘀血、热毒等邪实,治疗常用益气养阴、化痰祛湿、清热解毒、活血化瘀之法。

99'SAS软件应用高级研讨会交流论文选登——中药方药的对数线性模型分析方法

本文以五苓散方药为例，收集古今临床医案、整理，并用对数线性模型方法进行分析，以探讨对数线性模型分析方法在中药方药配伍规律研究中的应用。

Research on Herb Pairs of Classical Formulae of ZHANG ZhongJing Using Big Data Technology

Objective To analyze various herbal combinations in Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》),seeking to identify fundamental rules dictating the selection of herbal combinations through probability models and big data technology.Methods A total of 252 formulae were collected from Treatise on Exogenous Febrile Diseases(Shang Han Lun,《伤寒论》)and Synopsis of Prescriptions of the Golden Chamber(Jin Gui Yao Lve,《金匮要略》)by ZHANG Zhong-Jing.Formulae were then preprocessed with all herb names standardized.The concepts of candidate herb pair and candidate herb pair probability were proposed to analyze the rules of combinations in classical formulae based on probability statistics.MapReduce parallel computing framework of distributed big data technology was adopted to analyze large data samples combined with inverted index algorithm.Results The results showed that the core herbs were Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Cinnamomi Ramulus(Gui Zhi,桂枝),Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Jujubae Fructus(Da Zao,大枣),Paeoniae Radix Alba(Bai Shao,白芍),etc.43 high-frequency pairs co-occurring 10 times or above were extracted,and 35 of these combinations were recognized as traditional herb pairs,such as Cinnamomi Ramulus(Gui Zhi,桂枝)-Glycyrrhizae Radix Rhizoma(Gan Cao,甘草),Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Jujubae Fructus(Da Zao,大枣),and Cinnamomi Ramulus(Gui Zhi,桂枝)-Ginseng Radix Et Rhizoma(Ren Shen,人参).The other 8 pairs of combinations,such as Paeoniae Radix Alba(Bai Shao,白芍)-Zingiberis Rhizoma Recens(Sheng Jiang,生姜),Paeoniae Radix Alba(Bai Shao,白芍)-Jujubae Fructus(Da Zao,大枣),and Zingiberis Rhizoma Recens(Sheng Jiang,生姜)-Ginseng Radix Et Rhizoma(Ren Shen,人参),were not defined traditionally,but in connection with commonly used herbs.Classical formulae took the core herbs as principles,focusing on tonifying deficiency,strengthening the spleen and the stomach,strengthening the healthy Qi,and eliminating pathogenic factors.The compatibility pattern of properties involved was mainly acrid and sweet,which reflected the compatibility laws of benefiting Qi and tonifying Yang,replenishing Qi and nourishing blood,etc.Conclusions The research of classical formulae provides common understanding of some basic rules that have been adopted to tackle common illnesses/diseases using herbal medicine.The results help to reinforce theoretical understanding and development of traditional Chinese medicine(TCM),and revealing the hidden rules of combination in TCM data.Analyzing wider data samples of various herbal combinations through computation and big data technology can further optimize the use of TCM.