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An CTM Prescriptions Database System (CPDBS), an CTM Intelligent Analysis System (CPIAS) and an CTM Classification Model Recognition System are developed with Support Vector Machine (CPSVM) to study the knowledge of CTM prescriptions. Progress has been made on insight discovery, qualitative and quantitative computation of key knowledge and classification model recognition of CTM prescriptions. It is shown that with the data mining of CTM prescriptions as the entry point of CTM diagnostics study, an effective way may be found to transfer human experience to systematic knowledge, which has a practical meaning on modernization of CTM., authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=9A40zh6ZPjm3ZfcLGByHzw==, pdfFileSize=621294, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242120392463155621, articleId=1242120390135316894, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=计算技术对中医方剂知识的挖掘, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=以中医方剂为研究对象，运用数据库挖掘、不确定性推理、机器学习等计算技术构建了一个数据挖掘平台；采用自主研制的“中医方剂数据库系统”（CPDBS）、“中医方剂智能分析系统”（CPIAS）、“中医方剂分类模式识别系统”（CPSVM）等软件，对中医方剂知识进行了挖掘研究。在中医方剂内涵知识的发现、方剂知识要点的形式化与量化计算、方剂模式分类识别等方面的研究成果表明：把对中医方剂知识的挖掘作为解读中医诊治思维的切入点，是实现把人的“经验”转化为“知识”的有效途径，对中医学的现代化研究具有现实意义。, authors=任廷革，刘晓峰，张 帆，孙 燕，汤尔群, authorsList=任廷革;刘晓峰;张 帆;孙 燕;汤尔群, authorCompany=北京中医药大学基础医学院，北京 100029, correspAuthors=null, authorNote=null, correspAuthorsNote=任廷革, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=BMNRF2K/NiGTQoIX7FWrug==, pdfFileSize=621294, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, authors=null, keywords=[Keyword(id=1242120392035336609, tenantId=1146029695717560320, journalId=1146031591421210625, 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