“方证相应”的数据挖掘方法研究

【作者】 李认书；

【导师】 蒋永光；

【作者基本信息】 成都中医药大学 ， 中医医史文献， 2002， 硕士

【摘要】 “方证相应”理论起源于仲景《伤寒论》，后经历代医家的发挥与实践，渐趋成熟和完善。其在理论上强调方为证立、方随证转，实践中注重辨主证、析兼证、抓变证，非常有助于执简驭繁地运用成方，具有很大的临床应用价值。目前，方证相应的研究已成为中医药领域的热点之一。 随着中医药现代化研究的不断深入，出现了中医药学与现代医学、生物学、电子信息技术等多种新学科互相渗透的局面，从而使得多学科的中医药研究成为其学科发展的重要趋势。 近年来数据挖掘技术得到了迅速发展，被广泛应用于包括医药在内的多种研究领域。为探索中医药现代化研究的新思路，我们将数据挖掘技术引入方证相应的研究。数据挖掘能从大量数据中挖掘先前未知的、有效的、可实用的知识，以利于科学的决策和知识更新。本课题的研究内容主要包括：所涉方证数据的预处理；系统聚类、模糊聚类、频繁集、对应分析方法的选定和试验；知识的发现与评价。 本文将就课题研究中涉及的以下问题：方证相应理论、数据挖掘技术、方证数据的处理、数据挖掘方法等进行论述。更多还原

【Abstract】 The theory of correspondence of formula and syndrome roots in shanghanlun written by Zhangzhongjing. It emphasizes that the formula’s creating and changing must be corresponded with the symptoms. In practice,to use the set prescription effectively,the key step is to distinguish the main symptoms,the secondary symptoms and the developed symptoms. Therefore,it is a short cut to use set prescriptions according to this theory. Because of its utility,study of this theory’s essential has been one of the hot research fields in TCM (traditional Chinese medicine).With the deepening of the TCM’s modernization study,it has been a trend to introduce some new subjects to TCM’s research such as modern medicine,biology,electronic informatics,ect. In recent years,data mining has made a rapid development and been widely used to many research fields involving TCM.To discover a new study method of TCM’s modernization,we adopted data mining to research the correspondence of formula and syndrome. Data mining (also known as Knowledge Discovery in Databases - KDD) has been defined as "The nontrivial extraction of implicit,previously unknown,and potentially useful information from data". According to the study task,we choose methods of hierarchical clustering,fuzzy clustering,frequent item set and correspondence analysis. In this article,what are discussed include the pretreatment of data,establishment of data mining methods,analysis and value of the results.更多还原