基于胃脘痛方剂整理的数据仓库建模研究
|
摘要
中医药学其完整的理论体系和丰富的临床实践经验,为中华民族的健康保健做出了突出的贡献。方剂学在中医药学中占有重要位置。中医方剂是名老中医将中医药学基本理论、前人经验与实践相结合,解决临床疑难问题的经验的结晶:中医方剂是中医药学理、法、方、药的一个重要组成部分,其药对、配伍规律有着深刻的科学内涵。几千年来,中医药领域的无数的理论研究和临床实践积累了海量的中医方剂,如何有效的利用这些宝贵的中医方剂资源就成了发展中医药必须面对的一个问题。
随着信息技术的飞速发展,数据库、数据仓库、数据挖掘技术已广泛应用于银行、零售、电信、医学等行业的海量数据的研究分析并已取得了丰硕的成果。利用数据库、数据仓库、数据挖掘技术对海量的中医方剂数据进行科学的研究分析,或许可以帮助我们找到感兴趣的知识。
综观相关文献,目前利用编程软件对方剂的研究基本上都是开发单一的数据库、数据仓库或管理应用系统的应用研究,而且也没有对方剂词典中整理的某种病进行的开发研究。
本研究的主要目的是以方剂数据仓库建模为核心,建立一个集方剂数据库、方剂数据仓库及方剂集成管理应用系统于一体的综合应用系统平台,体现管理理念和突出中医药特色,帮助医务工作者学习、提高研究工作效率并为方剂的统计分析服务。
本研究利用Excel、PowerBuilder8.0程序开发语言、SQL Server 2000、AnalysisServices 2005等软件,按照软件工程建模思想,对方剂进行数据库、数据仓库及集成管理应用系统建模。
本研究尝试做了以下工作:(1)在《中医方剂大辞典》整理的治疗胃脘痛方剂的基础上,把总共502条、字数约8万字的方剂转换为数据库二维表。(2)应用Excel简便、快速的数据处理功能代替复杂的程序对方剂数据进行预处理。(3)以方剂数据仓库建模为核心,建立一个集方剂数据库、方剂数据仓库及方剂集成管理应用系统于一体的综合应用系统平台,体现管理理念和中医药特色并集成方便、快捷的数据移植功能。(4)方剂数据库、方剂数据仓库及方剂集成管理应用系统三者相互联系、相辅相承,方剂集成管理应用系统可以为方剂数据库提供新的数据,而方剂数据库可以为方剂数据仓库提供新的历史数据,方剂集成管理应用系统又可以将方剂数据仓库的数据进行统计、挖掘分析并提供对方剂的日常管理操作。
本研究暂还没有扩展开发病症数据仓库及完善数据挖掘功能,会在以后的研究中加以完善。虽然只是应用于基于胃脘痛这一病种的点上,但随着信息技术的迅猛发展及研究的不断探索,以后可以扩展到其他病种的面上并做得更先进,为中医方剂乃至中医药的信息化研究及管理提供一定程度的借鉴。
Chinese medicine's complete theoretical system and rich experience in clinical practice have made outstanding contributions to health care for the Chinese nation.Science of prescriptions occupies an important position in Chinese medicine.Prescription is crystallization of the experience that famous old TCM doctors combine Chinese medicine's basic theory,previous experience with practice to resolve the clinical problems.Prescription is an important component of Chinese medicine's theory,methods,prescription and herbs,its pair of herb and prescription compounding have a profound scientific connote.For thousands of years,the numerous theory researches and clinical practices of Chinese medicine has accumulated massive prescription.How to effectively use these valuable resources on the prescription has become a problem that develops Chinese medicine has to face.
With the rapid development of information technology,database,data warehouse and data mining technologies are widely used in banking,retail, telecommunications,medicine and other industries,research and analysis of their massive data have been made fruitful.Using these technologies to do scientific research and analysis on massive prescription may be able to help us to find interesting knowledge.
Overview of related literature,at present,the use of programming software to research prescription is basically a single database,data warehouse or management application system.And there is no other developing research on a disease based on a prescription dictionary.
The research's main purpose is to make data warehouse modeling of prescription as the core.And to build an integrated application system that combines prescription database,data warehouse with management application system and that it reflects the management concept and the characteristics of Chinese medicine.It can help medical workers to learn and improve the efficiency of research and statistical analysis of prescription services.
The research uses software such as Excel,PowerBuilder8.0,SQL Server 2000, Analysis Services 2005 and so on.It is in accordance with the Software Engineering modeling and to model database,data warehouse and management application system for the prescription.
This research attempts to have done these work:(1)It bases on prescription of treatment of epigastric pain from the dictionary called "Dictionary of Chinese Medicine Prescription".To convert 502 prescription of about 80 thousand words to a two-dimensional table.(2)Using Excel's simple and rapid data processing function instead of complex procedures to pre-process prescription data.(3)It's core is data warehouse modeling of prescription. It is an integrated application system that combines prescription database, prescription data warehouse with prescription management application system and that it reflects the management concept and the characteristics of Chinese medicine,and integrates comfortable and rapid data transplanting function.(4)Prescription database,prescription data warehouse and prescription management application system complement each other. Prescription management application system can supply new data for prescription database,prescription database can supply new historical data for prescription data warehouse,and prescription management application system can make statistical and mining analysis of data from the prescription data warehouse and it can supply daily management operation for prescription.
The research also did not extend the temporary development of disease data warehouse and data mining features,but it will be better in subsequent studies. Although this is only applies to the point of epigastric pain,with the rapid development of information technology and research continue to explore,some years later it can be extended to other types of disease and more advanced. The research can provide informationization research and management of the prescription and even the Chinese medicine with a degree of reference.
随着信息技术的飞速发展,数据库、数据仓库、数据挖掘技术已广泛应用于银行、零售、电信、医学等行业的海量数据的研究分析并已取得了丰硕的成果。利用数据库、数据仓库、数据挖掘技术对海量的中医方剂数据进行科学的研究分析,或许可以帮助我们找到感兴趣的知识。
综观相关文献,目前利用编程软件对方剂的研究基本上都是开发单一的数据库、数据仓库或管理应用系统的应用研究,而且也没有对方剂词典中整理的某种病进行的开发研究。
本研究的主要目的是以方剂数据仓库建模为核心,建立一个集方剂数据库、方剂数据仓库及方剂集成管理应用系统于一体的综合应用系统平台,体现管理理念和突出中医药特色,帮助医务工作者学习、提高研究工作效率并为方剂的统计分析服务。
本研究利用Excel、PowerBuilder8.0程序开发语言、SQL Server 2000、AnalysisServices 2005等软件,按照软件工程建模思想,对方剂进行数据库、数据仓库及集成管理应用系统建模。
本研究尝试做了以下工作:(1)在《中医方剂大辞典》整理的治疗胃脘痛方剂的基础上,把总共502条、字数约8万字的方剂转换为数据库二维表。(2)应用Excel简便、快速的数据处理功能代替复杂的程序对方剂数据进行预处理。(3)以方剂数据仓库建模为核心,建立一个集方剂数据库、方剂数据仓库及方剂集成管理应用系统于一体的综合应用系统平台,体现管理理念和中医药特色并集成方便、快捷的数据移植功能。(4)方剂数据库、方剂数据仓库及方剂集成管理应用系统三者相互联系、相辅相承,方剂集成管理应用系统可以为方剂数据库提供新的数据,而方剂数据库可以为方剂数据仓库提供新的历史数据,方剂集成管理应用系统又可以将方剂数据仓库的数据进行统计、挖掘分析并提供对方剂的日常管理操作。
本研究暂还没有扩展开发病症数据仓库及完善数据挖掘功能,会在以后的研究中加以完善。虽然只是应用于基于胃脘痛这一病种的点上,但随着信息技术的迅猛发展及研究的不断探索,以后可以扩展到其他病种的面上并做得更先进,为中医方剂乃至中医药的信息化研究及管理提供一定程度的借鉴。
Chinese medicine's complete theoretical system and rich experience in clinical practice have made outstanding contributions to health care for the Chinese nation.Science of prescriptions occupies an important position in Chinese medicine.Prescription is crystallization of the experience that famous old TCM doctors combine Chinese medicine's basic theory,previous experience with practice to resolve the clinical problems.Prescription is an important component of Chinese medicine's theory,methods,prescription and herbs,its pair of herb and prescription compounding have a profound scientific connote.For thousands of years,the numerous theory researches and clinical practices of Chinese medicine has accumulated massive prescription.How to effectively use these valuable resources on the prescription has become a problem that develops Chinese medicine has to face.
With the rapid development of information technology,database,data warehouse and data mining technologies are widely used in banking,retail, telecommunications,medicine and other industries,research and analysis of their massive data have been made fruitful.Using these technologies to do scientific research and analysis on massive prescription may be able to help us to find interesting knowledge.
Overview of related literature,at present,the use of programming software to research prescription is basically a single database,data warehouse or management application system.And there is no other developing research on a disease based on a prescription dictionary.
The research's main purpose is to make data warehouse modeling of prescription as the core.And to build an integrated application system that combines prescription database,data warehouse with management application system and that it reflects the management concept and the characteristics of Chinese medicine.It can help medical workers to learn and improve the efficiency of research and statistical analysis of prescription services.
The research uses software such as Excel,PowerBuilder8.0,SQL Server 2000, Analysis Services 2005 and so on.It is in accordance with the Software Engineering modeling and to model database,data warehouse and management application system for the prescription.
This research attempts to have done these work:(1)It bases on prescription of treatment of epigastric pain from the dictionary called "Dictionary of Chinese Medicine Prescription".To convert 502 prescription of about 80 thousand words to a two-dimensional table.(2)Using Excel's simple and rapid data processing function instead of complex procedures to pre-process prescription data.(3)It's core is data warehouse modeling of prescription. It is an integrated application system that combines prescription database, prescription data warehouse with prescription management application system and that it reflects the management concept and the characteristics of Chinese medicine,and integrates comfortable and rapid data transplanting function.(4)Prescription database,prescription data warehouse and prescription management application system complement each other. Prescription management application system can supply new data for prescription database,prescription database can supply new historical data for prescription data warehouse,and prescription management application system can make statistical and mining analysis of data from the prescription data warehouse and it can supply daily management operation for prescription.
The research also did not extend the temporary development of disease data warehouse and data mining features,but it will be better in subsequent studies. Although this is only applies to the point of epigastric pain,with the rapid development of information technology and research continue to explore,some years later it can be extended to other types of disease and more advanced. The research can provide informationization research and management of the prescription and even the Chinese medicine with a degree of reference.
引文
[1]刘德军.中药方剂学.北京:中国中医药出版社,2006:1-29.
[2]冯泳,申惠鹏.方剂学.北京:中医古籍出版社,2003:9.
[3]朱金伟,鞠时光,辛燕.基于数据挖掘的中医药数据预处理方法.计算机工程,2006,32(15):280-282,F0003.
[4]张承江.医学数据仓库与数据挖掘.北京:中国中医药出版社,2008:56-65.
[5]彭怀仁.中医方剂大辞典.北京:人民卫生出版社,2002.
[6]康晓东.基于数据仓库的数据挖掘技术.北京:机械工业出版社,2005:12-13.
[7]张海藩.软件工程导论(第四版).北京:清华大学出版社,2003:11.
[8]瞿海斌,王祥君等.中医药信息智能检索系统构建方法研究.浙江大学学报:工学版,2002,36(4):460-462,472.
[9]王学伟,瞿海斌,王阶.一种基于数据挖掘的中医定量诊断方法.北京中医药大学学报,2005,28(1):4-7.
[10]孙亚男,宁士勇,鲁明羽等.贝叶斯分类算法在冠心病中医临床证型诊断中的应用.计算机应用研究,2006,23(11):164-166.
[11]徐蕾,贺佳,孟虹等.基于信息熵的决策树在慢性胃炎中医辨证中的应用.第二军医大学学报,2004,25(9):1009-1012.
[12]王波,张斌,魏伟杰等.面向中医辨证规范的交互式数据挖掘框架.世界科学技术:中医药现代化,2006,8(1):24-30.
[13]Merwyn Taylor,Joel Saltz,James H.Nichols.Design of an Integrated Clinical Data Warehouse.Journal of the Association for Laboratory Automation,2000,5(3):54-59.
[14]Joseph L.Breault,Colin R.Goodall,Peter J.Fos.Data mining a diabetic data warehouse.Artificial Intelligence in Medicine,2002,26(1-2):37-54.
[15]Andrew Grant,Andriy Moshyk,Hassan Diab.Integrating feedback from a clinical data warehouse into practice organisation.International Journal of Medical Informatics,2006,75(3-4):232-239.
[16]Joseph L.Breault,Colin R.Goodall,Peter J.Fos.Erratum to "Data mining a diabetic data warehouse".Artificial Intelligence in Medicine,2003,27(2):227.
[17]N.B.Szirbik,C.Pelletier,T.Chaussalet.Six methodological steps to build medical data warehouses for research.International Journal of Medical Informatics,2006,75(9):683-691.
[18]Miho Ohsaki,Hidenao Abe,Shusaku Tsumoto.Evaluation of rule interestingness measures in medical knowledge discovery in databases. Artificial Intelligence in Medicine,2007,41(3):177-196.
[19]胥庆华,刘丽云,赵瑞华.中药药对大全.北京:中国中医药出版社,1996:3-4.
[20]郭蓉.胃脘痛的辨证论治.四川中医,2003,21(9):12-13.
[21]萨师煊,王珊.数据库系统概论(第三版).北京:高等教育出版社,2000:13-17.
[22]龚波等.SQL Server 2000教程.北京:北京希望电子出版社,2002:1-5.
[23]ZhaoHui Tang,Jamie MacLennan.Data Mining with SQL Server 2005.北京:清华大学出版社,2007:1-5.
[24]国家药典委员会.中国药典2005年版.北京:化学工业出版社,2005.
[25]网冠科技.PowerBui lder 8.0时尚编程百例.北京:机械工业出版社,2002:196.
[26]柯建勋,张涛,邵亮等.PowerBuilder 8.0进阶篇(实例与技巧篇).北京:清华大学出版社,2002:349-351.
[27]段兴.PowerBuilder 8.0实用程序设计100例.北京:人民邮电出版社,2003:304.
[28]孙亚男,宁士勇,鲁明羽等.中医诊疗决策支持系统中的OLAP与DM融合.计算机工程,2006,32(9):251-252,255.
[29]陆伟,王雁峰,吴朝晖.中药复方组成规律的关联规则发现系统.浙江大学学报:工学版,2001,35(4):370-373,407.
[30]王映辉,姜在旸,闫英杰等.基于信息和数据挖掘技术的名老中医临床诊疗经验研究思路.世界科学技术:中医药现代化,2005,7(1):98-105.
[31]陆伟,王雁峰,吴朝晖.中药复方组成规律的关联规则发现系统.浙江大学学报:工学版,2001,35(4):370-373,407.
[32]张启明,田欣.脏腑病辨证用药的Logistic回归分析(1)—脾(胃)病篇.辽宁中医杂志,2003,30(1):22-25.
[33]李飞,柴瑞霁,樊巧玲.方剂的配伍方法(第2版).北京:人民卫生出版社,2005:20.
[34]詹文涛,杨国祥.中药方剂研究进展.北京:云南科技出版社,2000,10-19.
[35]Chih-Lin Chi,W.Nick Street,Marcia M.Ward.Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm.Journal of Biomedical Informatics,2007.
[36]Po Shun Ngan,Man Leung Wong,Wai Lam.Medical data mining using evolutionary computation.Artificial Intelligence in Medicine,1999,16(1):73-96.
[37]高洁,谢鸣,陈德兴等.方剂的现代研究.北京:中医古籍出版社,2006:62.
[38]陈建设,陈文垲.胃炎(胃脘痛)的证候聚类分析.辽宁中医杂志,2007,34(3):291-292.
[39]徐远.印会河教授治疗胃脘痛经验简介.新中医,1999,31(7):5-6.
[40]王欣,徐腾飞,唐连章等.SQL Server 2005 Data Mining Analysis by Living Example.北京:中国水利水电出版社,2008:1-5.
[41]宋姚屏,李昆,吴孟旭等.药对剂量的关联分析初探.辽宁中医杂志,2006, 33(9):1095-1096.
[42]周忠眉.中医方剂数据挖掘模式和算法研究:[博士学位论文].浙江:浙江大学,2007:1-3.
[43]姚美村,艾路,袁月梅等.消渴病复方配伍规律的关联规则分析.北京中医药大学学报,2002,25(6):48-50.
[44]范颖.试论中医方剂配伍规律研究的现状与基本思路.江苏中医药,2003,24(4):1-2.
[45]乔延江,李澎涛,苏钢强等.中药(复方)KDD研究开发的意义.北京中医药大学学报,1998,(3):9-11.
[46]彭京,唐常杰,曾涛等.基于神经网络和属性距离矩阵的中药方剂功效归约算法.四川大学学报(工程科学版),2006,38(1):96-98.
[47]高彦伟,郑文瑞,韩燕等.复方配伍的摄动模糊聚类方法.生物数学学报,2005,20(2):219-222.
[48]蒋永光,胡波,刘娟等.方剂配伍的数据挖掘可行性探索.四川中医,2004,22(8):25-28.
[49]张菊英,查干花,李力等.脾胃方配伍规律统计方法探讨.四川中医,2004,22(6):93-94.
[50]宋余庆,朱玉全,孙志挥等.基于FP-Tree的最大频繁项目集挖掘及更新算法.软件学报,2003,14(9):1586-1592.
[51]王咏梅,马红,刘苏中.方剂配伍的模糊数学特性研究.中国实验方剂学杂志,2000,6(6):59-60.
[52]宋小莉,牛欣,司银楚.人工神经网络在半夏泻心汤配伍建模中的应用.中国临床药理学与治疗学,2005,10(1):104-107.
[53]李崑,宋姚屏,陈云惠等.数据挖掘技术在药对配伍规律研究中的应用.辽宁中医杂志,2006,33(7):773-774.
[54]刘娟,蒋永光,陈春林.抗流感验方用药趋向的数据分析.辽宁中医杂志,2007,34(5):550-551.
[55]赵贺增.运用计算机总结董建华教授论治胃脘痛的经验.北京生物医学工程,1996,15(1):55-56.
[56]于友华.方剂配伍理论的系统科学思想.中国中医基础医学杂志,2004,10(8):63-64.
[57]田琳,阎英杰,朱建贵.数据挖掘及其在中医药现代化研究中的应用.北京中医药大学学报,2002,25(5):20-23.
[58]夏邦贵,郭胜等.PowerBuilder数据库开发—入门与范例解析.北京:机械工业出版社,2004:2.
[59]王晟.PowerBuilder数据库开发经典案例解析.北京:清华大学出版社,2005:385-401.
[60]陈磊,郭斌,李翔.PowerBuilder9数据库项目案例导航.北京:清华大学出版社, 2005:63-65.
[61]崔杜武,姚全珠,黑新宏等.PowerBuilder9.0基础应用与系统开发.北京:电子工业出版社,2004:347-350.
[62]李建义.数据库原理及开发SQL Server+PowerBuilder.北京:中国水利水电出版社,2005:6-7.
[63]陈禹,杨波.信息管理与信息系统概论.北京:中国人民大学出版社,2005:285.
[64]蒋永光,季力,李认书等.中医脾胃方配伍规律的数据挖掘试验.世界科学技术:中医药现代化,2003,5(3):33-37.
[2]冯泳,申惠鹏.方剂学.北京:中医古籍出版社,2003:9.
[3]朱金伟,鞠时光,辛燕.基于数据挖掘的中医药数据预处理方法.计算机工程,2006,32(15):280-282,F0003.
[4]张承江.医学数据仓库与数据挖掘.北京:中国中医药出版社,2008:56-65.
[5]彭怀仁.中医方剂大辞典.北京:人民卫生出版社,2002.
[6]康晓东.基于数据仓库的数据挖掘技术.北京:机械工业出版社,2005:12-13.
[7]张海藩.软件工程导论(第四版).北京:清华大学出版社,2003:11.
[8]瞿海斌,王祥君等.中医药信息智能检索系统构建方法研究.浙江大学学报:工学版,2002,36(4):460-462,472.
[9]王学伟,瞿海斌,王阶.一种基于数据挖掘的中医定量诊断方法.北京中医药大学学报,2005,28(1):4-7.
[10]孙亚男,宁士勇,鲁明羽等.贝叶斯分类算法在冠心病中医临床证型诊断中的应用.计算机应用研究,2006,23(11):164-166.
[11]徐蕾,贺佳,孟虹等.基于信息熵的决策树在慢性胃炎中医辨证中的应用.第二军医大学学报,2004,25(9):1009-1012.
[12]王波,张斌,魏伟杰等.面向中医辨证规范的交互式数据挖掘框架.世界科学技术:中医药现代化,2006,8(1):24-30.
[13]Merwyn Taylor,Joel Saltz,James H.Nichols.Design of an Integrated Clinical Data Warehouse.Journal of the Association for Laboratory Automation,2000,5(3):54-59.
[14]Joseph L.Breault,Colin R.Goodall,Peter J.Fos.Data mining a diabetic data warehouse.Artificial Intelligence in Medicine,2002,26(1-2):37-54.
[15]Andrew Grant,Andriy Moshyk,Hassan Diab.Integrating feedback from a clinical data warehouse into practice organisation.International Journal of Medical Informatics,2006,75(3-4):232-239.
[16]Joseph L.Breault,Colin R.Goodall,Peter J.Fos.Erratum to "Data mining a diabetic data warehouse".Artificial Intelligence in Medicine,2003,27(2):227.
[17]N.B.Szirbik,C.Pelletier,T.Chaussalet.Six methodological steps to build medical data warehouses for research.International Journal of Medical Informatics,2006,75(9):683-691.
[18]Miho Ohsaki,Hidenao Abe,Shusaku Tsumoto.Evaluation of rule interestingness measures in medical knowledge discovery in databases. Artificial Intelligence in Medicine,2007,41(3):177-196.
[19]胥庆华,刘丽云,赵瑞华.中药药对大全.北京:中国中医药出版社,1996:3-4.
[20]郭蓉.胃脘痛的辨证论治.四川中医,2003,21(9):12-13.
[21]萨师煊,王珊.数据库系统概论(第三版).北京:高等教育出版社,2000:13-17.
[22]龚波等.SQL Server 2000教程.北京:北京希望电子出版社,2002:1-5.
[23]ZhaoHui Tang,Jamie MacLennan.Data Mining with SQL Server 2005.北京:清华大学出版社,2007:1-5.
[24]国家药典委员会.中国药典2005年版.北京:化学工业出版社,2005.
[25]网冠科技.PowerBui lder 8.0时尚编程百例.北京:机械工业出版社,2002:196.
[26]柯建勋,张涛,邵亮等.PowerBuilder 8.0进阶篇(实例与技巧篇).北京:清华大学出版社,2002:349-351.
[27]段兴.PowerBuilder 8.0实用程序设计100例.北京:人民邮电出版社,2003:304.
[28]孙亚男,宁士勇,鲁明羽等.中医诊疗决策支持系统中的OLAP与DM融合.计算机工程,2006,32(9):251-252,255.
[29]陆伟,王雁峰,吴朝晖.中药复方组成规律的关联规则发现系统.浙江大学学报:工学版,2001,35(4):370-373,407.
[30]王映辉,姜在旸,闫英杰等.基于信息和数据挖掘技术的名老中医临床诊疗经验研究思路.世界科学技术:中医药现代化,2005,7(1):98-105.
[31]陆伟,王雁峰,吴朝晖.中药复方组成规律的关联规则发现系统.浙江大学学报:工学版,2001,35(4):370-373,407.
[32]张启明,田欣.脏腑病辨证用药的Logistic回归分析(1)—脾(胃)病篇.辽宁中医杂志,2003,30(1):22-25.
[33]李飞,柴瑞霁,樊巧玲.方剂的配伍方法(第2版).北京:人民卫生出版社,2005:20.
[34]詹文涛,杨国祥.中药方剂研究进展.北京:云南科技出版社,2000,10-19.
[35]Chih-Lin Chi,W.Nick Street,Marcia M.Ward.Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm.Journal of Biomedical Informatics,2007.
[36]Po Shun Ngan,Man Leung Wong,Wai Lam.Medical data mining using evolutionary computation.Artificial Intelligence in Medicine,1999,16(1):73-96.
[37]高洁,谢鸣,陈德兴等.方剂的现代研究.北京:中医古籍出版社,2006:62.
[38]陈建设,陈文垲.胃炎(胃脘痛)的证候聚类分析.辽宁中医杂志,2007,34(3):291-292.
[39]徐远.印会河教授治疗胃脘痛经验简介.新中医,1999,31(7):5-6.
[40]王欣,徐腾飞,唐连章等.SQL Server 2005 Data Mining Analysis by Living Example.北京:中国水利水电出版社,2008:1-5.
[41]宋姚屏,李昆,吴孟旭等.药对剂量的关联分析初探.辽宁中医杂志,2006, 33(9):1095-1096.
[42]周忠眉.中医方剂数据挖掘模式和算法研究:[博士学位论文].浙江:浙江大学,2007:1-3.
[43]姚美村,艾路,袁月梅等.消渴病复方配伍规律的关联规则分析.北京中医药大学学报,2002,25(6):48-50.
[44]范颖.试论中医方剂配伍规律研究的现状与基本思路.江苏中医药,2003,24(4):1-2.
[45]乔延江,李澎涛,苏钢强等.中药(复方)KDD研究开发的意义.北京中医药大学学报,1998,(3):9-11.
[46]彭京,唐常杰,曾涛等.基于神经网络和属性距离矩阵的中药方剂功效归约算法.四川大学学报(工程科学版),2006,38(1):96-98.
[47]高彦伟,郑文瑞,韩燕等.复方配伍的摄动模糊聚类方法.生物数学学报,2005,20(2):219-222.
[48]蒋永光,胡波,刘娟等.方剂配伍的数据挖掘可行性探索.四川中医,2004,22(8):25-28.
[49]张菊英,查干花,李力等.脾胃方配伍规律统计方法探讨.四川中医,2004,22(6):93-94.
[50]宋余庆,朱玉全,孙志挥等.基于FP-Tree的最大频繁项目集挖掘及更新算法.软件学报,2003,14(9):1586-1592.
[51]王咏梅,马红,刘苏中.方剂配伍的模糊数学特性研究.中国实验方剂学杂志,2000,6(6):59-60.
[52]宋小莉,牛欣,司银楚.人工神经网络在半夏泻心汤配伍建模中的应用.中国临床药理学与治疗学,2005,10(1):104-107.
[53]李崑,宋姚屏,陈云惠等.数据挖掘技术在药对配伍规律研究中的应用.辽宁中医杂志,2006,33(7):773-774.
[54]刘娟,蒋永光,陈春林.抗流感验方用药趋向的数据分析.辽宁中医杂志,2007,34(5):550-551.
[55]赵贺增.运用计算机总结董建华教授论治胃脘痛的经验.北京生物医学工程,1996,15(1):55-56.
[56]于友华.方剂配伍理论的系统科学思想.中国中医基础医学杂志,2004,10(8):63-64.
[57]田琳,阎英杰,朱建贵.数据挖掘及其在中医药现代化研究中的应用.北京中医药大学学报,2002,25(5):20-23.
[58]夏邦贵,郭胜等.PowerBuilder数据库开发—入门与范例解析.北京:机械工业出版社,2004:2.
[59]王晟.PowerBuilder数据库开发经典案例解析.北京:清华大学出版社,2005:385-401.
[60]陈磊,郭斌,李翔.PowerBuilder9数据库项目案例导航.北京:清华大学出版社, 2005:63-65.
[61]崔杜武,姚全珠,黑新宏等.PowerBuilder9.0基础应用与系统开发.北京:电子工业出版社,2004:347-350.
[62]李建义.数据库原理及开发SQL Server+PowerBuilder.北京:中国水利水电出版社,2005:6-7.
[63]陈禹,杨波.信息管理与信息系统概论.北京:中国人民大学出版社,2005:285.
[64]蒋永光,季力,李认书等.中医脾胃方配伍规律的数据挖掘试验.世界科学技术:中医药现代化,2003,5(3):33-37.