【正文】 ............... 7 相關研究的現狀 ............................................................................................... 8 高血壓領域的研究現狀 .......................................................................... 8 關聯規(guī)則的研究現狀 .............................................................................. 9 本課題的主要研究目標 .................................................................................. 10 第二章 數據 挖掘技術研究 .......................................................................................... 11 數據挖掘技術及其在中醫(yī)藥研究中的應用 ................................................... 11 數據挖掘簡介 ....................................................................................... 11 數據挖掘的功 能概述 ............................................................................ 14 數據挖掘技術在中醫(yī)藥研究中的應用 ................................................. 16 數據挖掘和傳統(tǒng)數據分析工具和學習機器的區(qū)別 .............................. 18 關聯規(guī)則 ......................................................................................................... 19 關聯規(guī)則介紹 ....................................................................................... 19 關聯規(guī)則的有關定義 ............................................................................ 20 關聯規(guī)則的分類 ................................................................................... 23 2． 3 挖掘關聯規(guī)則的經典算法介紹 ................................................................... 24 AIS 算法 .............................................................................................. 25 APRIORI 算法 .................................................................................... 25 不產生候選挖掘頻繁項集算法 ............................................................ 28 北京科技大 學本科生畢業(yè)設計（論文） 2 第三章 中醫(yī)醫(yī)案分析系統(tǒng)的實施及結果分析 ........................................................... 32 系統(tǒng)體系結構 ................................................................................................. 32 功能模塊 ......................................................................................................... 33 原始數據錄入 .............................................................................................. 33 中醫(yī)醫(yī)案模型創(chuàng)建模塊 ........................................................................ 35 模型瀏覽模塊 ....................................................................................... 35 數據存儲結構的設計 ...................................................................................... 36 算法設計的基本思想及實現過程 .................................................................. 39 算法設計的基本思想 ............................................................................ 39 Apriori 算法的實現過程 ........................................................................ 39 算法運行結果 ................................................................................................. 40 結果評價及性能分析 ...................................................................................... 41 對高血壓醫(yī)案模型進行分析 ................................................................ 41 對 Apriori 算法進行性能分析 ............................................................... 42 第四章 總結與展望 ..................................................................................................... 45 總結 ................................................................................................................ 45 展望 ................................................................................................................ 45 參考文獻 ...................................................................................................................... 47 在學取得成果 ............................................................................................................... 49 致謝 .............................................................................................................................. 50 3 摘 要 名老中醫(yī)寶貴的臨床經驗是中醫(yī)學術與臨證思維相結合的產物。中醫(yī)學經過長期的發(fā)展積累了大量的關于臨證經驗及治法、方劑、藥物和相關知識等信息的歷史文獻。 基于原始數據的可靠性、準確性和完整性方面的考慮，本研究以自 2020 年 1 月一 2020 年 10 月 中國中醫(yī)研究院基礎所胸痹急癥研究室主任、國家中醫(yī)藥管理局醫(yī)政司胸痹急癥協(xié)作組組長沈紹功 先生醫(yī)案 65 份為醫(yī)案來源，以高血壓病為例，采用 Apriori算法 進行頻繁項集的搜索，所得醫(yī)案模型幾乎完全符合沈 教授在治療高血壓病時常用的處方 。 北京科技大 學本科生畢業(yè)設計（論文） 4 關鍵詞：關聯規(guī)則； Apriori 算法；數據挖掘；用藥規(guī)律；名老中醫(yī)經驗 Abstract Famous TCM valuable clinical experience is Chinese medicine academic and clinical medicine card product of the bination of thinking. TCM Clinical Treatment is the process of gathering information by the viewpoint of TCM, Chinese medicine thought to process information, and accordingly imposes the healing method. Chinese medicine knowledge from generation to generation, mostly words and deeds, virtually for the dissemination of knowledge and the benefit of the public medicine made obstacles. Just using data mining addresses key issues and technical challenges in the study of Chinese medicine characteristics . After a longterm development of Chinese medicine has accumulated a great deal of clinical experience, treatment, prescription drugs, and other information relevant knowledge about the history of literature. using data mining methods to study inherit old TCM clinical experience, digging finishing their academic thinking, innovation and research methods, bined with the application of data mining technology, machine learning technology and other intelligent technology, and striving to get the real experience of old TCM, easily inheritors learning.. The main work is as follows: 1． indepth analysis and discussion of the typical association rule mining algorithms Apriori algorithm, plete the basic idea of the database mining on the basis of this algorithm. 2． Visual BAS work on Windows XP platform C6. 0 environment, using Apriori algorithm, developed analysis of medical records system ， based on data mining for TCM hypertension. 3． based on considering the reliability, accuracy and integrity of the original data this