【摘要】：目的:在傳統(tǒng)關(guān)聯(lián)規(guī)則“支持度-置信度”模式的基礎(chǔ)上引入新的參數(shù)Kulc和IR參數(shù),以優(yōu)化挖掘結(jié)果的準(zhǔn)確性;對(duì)比分析優(yōu)化前后的挖掘結(jié)果,證實(shí)新參數(shù)的引入能夠更加深入有效的得到有意義的配伍規(guī)律;挖掘出的結(jié)果可以應(yīng)用于現(xiàn)代中醫(yī)的臨床教學(xué)、理論研究以及與大數(shù)據(jù)、互聯(lián)網(wǎng)+相結(jié)合的中醫(yī)類應(yīng)用平臺(tái)等。方法:對(duì)目前中醫(yī)領(lǐng)域的研究熱點(diǎn)中風(fēng)病病歷信息建立SQL Server數(shù)據(jù)庫,使用Apriori算法對(duì)其方劑配伍規(guī)律進(jìn)行挖掘分析;使用Microsoft Visual Studio 2010編寫程序,引入相關(guān)性度量參數(shù)Kulc和不平衡比(IR)參數(shù),避免“偽強(qiáng)規(guī)則”的出現(xiàn),確保挖掘出真正有強(qiáng)相關(guān)性的規(guī)則;結(jié)合中醫(yī)理論對(duì)優(yōu)化后的挖掘結(jié)果進(jìn)行中醫(yī)分析,確定配伍規(guī)律。結(jié)果:通過Apriori算法和新參數(shù)Kulc和IR,得到優(yōu)化前后的中風(fēng)病方劑配伍規(guī)律;對(duì)比優(yōu)化前后的挖掘結(jié)果,發(fā)現(xiàn)優(yōu)化后確實(shí)能夠過濾掉許多相關(guān)性不強(qiáng)的藥物組合,得到真正意義上的藥對(duì)藥組;中醫(yī)分析結(jié)果顯示挖掘出的藥物確實(shí)在治療中風(fēng)病時(shí)配伍使用效果更佳,為現(xiàn)代中醫(yī)治療中風(fēng)病提供數(shù)據(jù)支持和理論依據(jù)。結(jié)論:通過引入Kulc和IR參數(shù)確實(shí)可以過濾非強(qiáng)關(guān)聯(lián)的配伍規(guī)則,提高了關(guān)聯(lián)規(guī)則挖掘的準(zhǔn)確度,得到了可應(yīng)用的現(xiàn)代中醫(yī)治療中風(fēng)病的配伍規(guī)律;新方法同樣可應(yīng)用于其它疾病的診療規(guī)律挖掘,尤其是用藥規(guī)律尚未完全明確的疾病,可以為中醫(yī)理論的學(xué)習(xí)和臨床提供理論支持和教學(xué)引導(dǎo)。
[Abstract]:Aim: to optimize the accuracy of mining results by introducing new parameters Kulc and IR on the basis of the traditional support and confidence model of association rules, and to compare and analyze the mining results before and after optimization. The results can be applied to the clinical teaching of modern Chinese medicine, the theoretical research and the application platform of TCM combined with big data and Internet. Methods: the SQL Server database was established for the information of stroke medical records, which is a hot research topic in the field of traditional Chinese medicine, and its prescription compatibility law was excavated and analyzed by using Apriori algorithm, and the program was compiled with Microsoft Visual Studio 2010. In order to avoid the appearance of pseudo-strong rule, the correlation measure parameter Kulc and the unbalanced ratio (IR) parameter are introduced to ensure that the rules with real strong correlation can be excavated. Combined with TCM theory, the optimized mining results are analyzed in TCM, and the compatibility law is determined. Results: by using Apriori algorithm and new parameters Kulc and IR, the compatibility of stroke prescription before and after optimization was obtained, and by comparing the mining results before and after optimization, it was found that the optimized combination could filter out many drug combinations with no strong correlation. The results of traditional Chinese medicine analysis show that the medicine is better in the treatment of apoplexy, which provides data support and theoretical basis for modern Chinese medicine treatment of apoplexy. Conclusion: by introducing the parameters of Kulc and IR, the compatibility rules of non-strong association can be filtered, the accuracy of association rules mining can be improved, and the compatibility law of modern TCM treatment of apoplexy can be obtained. The new method can also be applied to excavate the rule of diagnosis and treatment of other diseases, especially the disease which has not completely defined the law of drug use, which can provide theoretical support and teaching guidance for the study of TCM theory and clinical practice.
【學(xué)位授予單位】：山東中醫(yī)藥大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP311.13;R255.2

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