基于模糊聚类与模糊关联的中药处方剂量配伍规律研究
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摘要
目的:探究中药处方剂量大小分布形式,挖掘中药处方剂量关联关系,为临床用药提供参考,为中药处方量效研究提供方法基础。方法:在对12 138组临床中药处方进行预处理后,使用模糊聚类与模糊关联规则进行挖掘。结果:研究求得309味药物大中小剂量中心点及其各自剂量隶属度矩阵,据此生成21条剂量模糊关联规则,并将该算法与传统数据挖掘方法进行比较。结论:模糊聚类算法可实现中药剂量的合理划分,模糊关联算法较之传统关联分析手段更适用中药处方剂量的挖掘。
Objectives: To explore dosage size distribution of Chinese medicine prescription and excavate the association relationship of prescription dosage so as to provide reference for clinical medication and method foundation for researching prescription dosage as well as effect. Methods: Based on the pretreatment of 12138 groups of clinical Chinese medicine prescriptions,fuzzy clustering and fuzzy association rules were used for mining. Results: The central points of309 kinds of medicine dosage sizes along with their respective dosage membership matrixes were acquired,which were applied to generate 21 dosage fuzzy association rules. Meanwhile,this algorithm was used to compare with traditional data mining method. Conclusions: Fuzzy clustering algorithm can realize the reasonable partition of Chinese medicine dosage,and fuzzy association algorithm,compared with traditional association analysis means,is more suitable for excavating prescription dosage.
Objectives: To explore dosage size distribution of Chinese medicine prescription and excavate the association relationship of prescription dosage so as to provide reference for clinical medication and method foundation for researching prescription dosage as well as effect. Methods: Based on the pretreatment of 12138 groups of clinical Chinese medicine prescriptions,fuzzy clustering and fuzzy association rules were used for mining. Results: The central points of309 kinds of medicine dosage sizes along with their respective dosage membership matrixes were acquired,which were applied to generate 21 dosage fuzzy association rules. Meanwhile,this algorithm was used to compare with traditional data mining method. Conclusions: Fuzzy clustering algorithm can realize the reasonable partition of Chinese medicine dosage,and fuzzy association algorithm,compared with traditional association analysis means,is more suitable for excavating prescription dosage.
引文
[1] 文乐兮, 魏飞跃. 方剂中药物量-效-毒关系的研究[J]. 中国实验方剂学杂志, 2009, 15(5):84-87.
[2] 曹爱霞, 谢宏涛. 中药剂量与疗效关系的探析[J]. 现代中医药, 2004(5):63.
[3] 袁晓红. 对《方剂学》中茯苓白术配伍规律的探讨[J]. 中医药导报, 2005, 11(4):55-56.
[4] 马彦敏, 孟静岩, 马佐英,等. 中医理论术语的模糊性对中医科普文本易读性的影响[J]. 中国中医基础医学杂志, 2017(10):1397-1398.
[5] 马红, 刘苏中, 王咏梅. 模糊数学方法在中药方剂研究中的应用[J]. 中国实验方剂学杂志, 2000, 6(2):56-58.
[6] 王咏梅, 马红. 方剂配伍的模糊数学特性研究[J]. 中国实验方剂学杂志, 2000, 6(6):59-60.
[7] 郭佳. 针对多维数据的模糊聚类算法研究[D]. 武汉:华中科技大学, 2016.
[8] Baraldi A, Blonda P. A survey of fuzzy clustering algorithms for pattern recognition. II[J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, 1999, 29(6):786-801.
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[10] Lin CW, Hong TP, Lu WH. Linguistic data mining with fuzzy FP-trees[J]. Expert Systems with Applications, 2010, 37(6):4560-4567.
[11] Geng L, Hamilton HJ. Interestingness measures for data mining:A survey[J]. Acm Computing Surveys, 2006, 38(3):9.
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[13] Jafarzadeh H, Torkashvand RR, Asgari C, et al. Provide A New Approach for Mining Fuzzy Association Rules using Apriori Algorithm[J]. Indian Journal of Science & Technology, 2015, 8(8):707.
[14] Mangalampalli A, Pudi V. Fuzzy association rule mining algorithm for fast and efficient performance on very large datasets[C]// IEEE International Conference on Fuzzy Systems, IEEE, 2009:1163-1168.
[15] 李敏, 何庆勇, 陈胤峰,等. 张仲景方中茯苓量效关系的研究[J]. 中华中医药杂志, 2015(12):4311-4313.
[16] 武胜萍, 徐立鹏, 刘洪兴,等. 黄连的临床应用及其用量探究[J]. 中国临床医生杂志, 2015, 43(2):92-94.
[17] 梅全喜. 中药汤剂中金银花用量的实验探讨[J]. 中国药房, 1993(4):7-8.
[18] 张林, 王海洋, 傅延龄. 历代当归临床用量评述[J]. 中华中医杂志, 2015(9):3058-3061.
[19] 曹雪,张卫华.国医大师郭诚杰教授临床应用黄芪经验介绍[J].新中医,2016(5):217-219.
[20] 徐菁晗,谷松.探析柴胡剂量与功效的关系[J].世界中医药,2018(1):202-206.
[21] 吴均华. 基于数据挖掘技术的五苓散用量及影响因素研究[D]. 成都:成都中医药大学, 2011.
[2] 曹爱霞, 谢宏涛. 中药剂量与疗效关系的探析[J]. 现代中医药, 2004(5):63.
[3] 袁晓红. 对《方剂学》中茯苓白术配伍规律的探讨[J]. 中医药导报, 2005, 11(4):55-56.
[4] 马彦敏, 孟静岩, 马佐英,等. 中医理论术语的模糊性对中医科普文本易读性的影响[J]. 中国中医基础医学杂志, 2017(10):1397-1398.
[5] 马红, 刘苏中, 王咏梅. 模糊数学方法在中药方剂研究中的应用[J]. 中国实验方剂学杂志, 2000, 6(2):56-58.
[6] 王咏梅, 马红. 方剂配伍的模糊数学特性研究[J]. 中国实验方剂学杂志, 2000, 6(6):59-60.
[7] 郭佳. 针对多维数据的模糊聚类算法研究[D]. 武汉:华中科技大学, 2016.
[8] Baraldi A, Blonda P. A survey of fuzzy clustering algorithms for pattern recognition. II[J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, 1999, 29(6):786-801.
[9] Chan KCC, Au WH. Mining fuzzy association rules[C]// International Conference on Information and Knowledge Management. ACM, 1997:209-215.
[10] Lin CW, Hong TP, Lu WH. Linguistic data mining with fuzzy FP-trees[J]. Expert Systems with Applications, 2010, 37(6):4560-4567.
[11] Geng L, Hamilton HJ. Interestingness measures for data mining:A survey[J]. Acm Computing Surveys, 2006, 38(3):9.
[12] Roy A, Chatterjee R. Realizing New Hybrid Rough Fuzzy Association Rule Mining Algorithm (RFA) Over Apriori Algorithm[M]. Intelligent Computing, Communication and Devices. Springer India, 2015:157-167.
[13] Jafarzadeh H, Torkashvand RR, Asgari C, et al. Provide A New Approach for Mining Fuzzy Association Rules using Apriori Algorithm[J]. Indian Journal of Science & Technology, 2015, 8(8):707.
[14] Mangalampalli A, Pudi V. Fuzzy association rule mining algorithm for fast and efficient performance on very large datasets[C]// IEEE International Conference on Fuzzy Systems, IEEE, 2009:1163-1168.
[15] 李敏, 何庆勇, 陈胤峰,等. 张仲景方中茯苓量效关系的研究[J]. 中华中医药杂志, 2015(12):4311-4313.
[16] 武胜萍, 徐立鹏, 刘洪兴,等. 黄连的临床应用及其用量探究[J]. 中国临床医生杂志, 2015, 43(2):92-94.
[17] 梅全喜. 中药汤剂中金银花用量的实验探讨[J]. 中国药房, 1993(4):7-8.
[18] 张林, 王海洋, 傅延龄. 历代当归临床用量评述[J]. 中华中医杂志, 2015(9):3058-3061.
[19] 曹雪,张卫华.国医大师郭诚杰教授临床应用黄芪经验介绍[J].新中医,2016(5):217-219.
[20] 徐菁晗,谷松.探析柴胡剂量与功效的关系[J].世界中医药,2018(1):202-206.
[21] 吴均华. 基于数据挖掘技术的五苓散用量及影响因素研究[D]. 成都:成都中医药大学, 2011.