【正文】 ............... 7 相關(guān)研究的現(xiàn)狀 ............................................................................................... 8 高血壓領(lǐng)域的研究現(xiàn)狀 .......................................................................... 8 關(guān)聯(lián)規(guī)則的研究現(xiàn)狀 .............................................................................. 9 本課題的主要研究目標(biāo) .................................................................................. 10 第二章 數(shù)據(jù) 挖掘技術(shù)研究 .......................................................................................... 11 數(shù)據(jù)挖掘技術(shù)及其在中醫(yī)藥研究中的應(yīng)用 ................................................... 11 數(shù)據(jù)挖掘簡(jiǎn)介 ....................................................................................... 11 數(shù)據(jù)挖掘的功 能概述 ............................................................................ 14 數(shù)據(jù)挖掘技術(shù)在中醫(yī)藥研究中的應(yīng)用 ................................................. 16 數(shù)據(jù)挖掘和傳統(tǒng)數(shù)據(jù)分析工具和學(xué)習(xí)機(jī)器的區(qū)別 .............................. 18 關(guān)聯(lián)規(guī)則 ......................................................................................................... 19 關(guān)聯(lián)規(guī)則介紹 ....................................................................................... 19 關(guān)聯(lián)規(guī)則的有關(guān)定義 ............................................................................ 20 關(guān)聯(lián)規(guī)則的分類 ................................................................................... 23 2． 3 挖掘關(guān)聯(lián)規(guī)則的經(jīng)典算法介紹 ................................................................... 24 AIS 算法 .............................................................................................. 25 APRIORI 算法 .................................................................................... 25 不產(chǎn)生候選挖掘頻繁項(xiàng)集算法 ............................................................ 28 北京科技大 學(xué)本科生畢業(yè)設(shè)計(jì)（論文） 2 第三章 中醫(yī)醫(yī)案分析系統(tǒng)的實(shí)施及結(jié)果分析 ........................................................... 32 系統(tǒng)體系結(jié)構(gòu) ................................................................................................. 32 功能模塊 ......................................................................................................... 33 原始數(shù)據(jù)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(shù)據(jù)存儲(chǔ)結(jié)構(gòu)的設(shè)計(jì) ...................................................................................... 36 算法設(shè)計(jì)的基本思想及實(shí)現(xiàn)過(guò)程 .................................................................. 39 算法設(shè)計(jì)的基本思想 ............................................................................ 39 Apriori 算法的實(shí)現(xiàn)過(guò)程 ........................................................................ 39 算法運(yùn)行結(jié)果 ................................................................................................. 40 結(jié)果評(píng)價(jià)及性能分析 ...................................................................................... 41 對(duì)高血壓醫(yī)案模型進(jìn)行分析 ................................................................ 41 對(duì) Apriori 算法進(jìn)行性能分析 ............................................................... 42 第四章 總結(jié)與展望 ..................................................................................................... 45 總結(jié) ................................................................................................................ 45 展望 ................................................................................................................ 45 參考文獻(xiàn) ...................................................................................................................... 47 在學(xué)取得成果 ............................................................................................................... 49 致謝 .............................................................................................................................. 50 3 摘 要 名老中醫(yī)寶貴的臨床經(jīng)驗(yàn)是中醫(yī)學(xué)術(shù)與臨證思維相結(jié)合的產(chǎn)物。中醫(yī)學(xué)經(jīng)過(guò)長(zhǎng)期的發(fā)展積累了大量的關(guān)于臨證經(jīng)驗(yàn)及治法、方劑、藥物和相關(guān)知識(shí)等信息的歷史文獻(xiàn)。 基于原始數(shù)據(jù)的可靠性、準(zhǔn)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(guó)中醫(yī)研究院基礎(chǔ)所胸痹急癥研究室主任、國(guó)家中醫(yī)藥管理局醫(yī)政司胸痹急癥協(xié)作組組長(zhǎng)沈紹功 先生醫(yī)案 65 份為醫(yī)案來(lái)源，以高血壓病為例，采用 Apriori算法 進(jìn)行頻繁項(xiàng)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(shí)常用的處方 。 北京科技大 學(xué)本科生畢業(yè)設(shè)計(jì)（論文） 4 關(guān)鍵詞：關(guān)聯(lián)規(guī)則； Apriori 算法；數(shù)據(jù)挖掘；用藥規(guī)律；名老中醫(yī)經(jīng)驗(yàn) 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