关联规则技术在中医药中的应用现状及思考
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摘要
关联规则技术是从大量数据中发现项之间有趣的关联和相关联系。随着现代科学技术及互联网的发展,其在中医药领域应用扩大,涉及病因病机、证候研究、方药研究等方面。但是关联规则技术亟须解决一些问题:①关联规则挖掘技术存在局限性,结果可能缺乏准确性、科学性,需进一步提高生成关联规则的质量。②用户须从数千条关联规则中寻找其感兴趣的或者有价值的,工作量较大且易出现错误,应对所挖掘的结果进行有效的组织和处理。中医药数据具有繁杂、重复、异质性,在搜集数据时,为了确保关联规则的准确性,必须对数据进行规范和筛选,按照制定的标准严格控制。结合各个医家的诊疗思路,将中医药研究与现代科学技术充分结合,发挥其优势,同时开展大数据、多中心的研究,完善数据库信息,将关联规则技术与中医药研究相结合,共同促进中医药的发展。
Association rule technology is the discovery of interesting associations and related relationships between items from large amounts of data. With the development of modern science and technology and the internet,its application in the field of Chinese medicine has expanded,involving diseases,pathogen and pathogenesis,syndrome research,and prescription research. But the association rule technology needs to solve some problems:(1)The association rule mining technology has limitations,and the results may lack accuracy and scientificity. It is necessary to further improve the quality of the generated association rules.(2)Users need to find out the interesting or valuable association rules from thousands of association rules,which are heavy workload and prone to errors.They should organize and process the mining results effectively. Chinese medicine data is cumbersome,repetitive,and heterogeneous. In order to ensure the accuracy of association rules,data must be standardized and screened,and strictly controlled according to established standards. Combining the diagnosis and treatment ideas of various medical doctors,the Chinese medicine research and modern science and technology are fully combined to give full play to their advantages. At the same time,big data and multicenter research are carried out,database information is improved,and association rules technology and traditional Chinese medicine research are combined to promote the development of Chinese medicine.
Association rule technology is the discovery of interesting associations and related relationships between items from large amounts of data. With the development of modern science and technology and the internet,its application in the field of Chinese medicine has expanded,involving diseases,pathogen and pathogenesis,syndrome research,and prescription research. But the association rule technology needs to solve some problems:(1)The association rule mining technology has limitations,and the results may lack accuracy and scientificity. It is necessary to further improve the quality of the generated association rules.(2)Users need to find out the interesting or valuable association rules from thousands of association rules,which are heavy workload and prone to errors.They should organize and process the mining results effectively. Chinese medicine data is cumbersome,repetitive,and heterogeneous. In order to ensure the accuracy of association rules,data must be standardized and screened,and strictly controlled according to established standards. Combining the diagnosis and treatment ideas of various medical doctors,the Chinese medicine research and modern science and technology are fully combined to give full play to their advantages. At the same time,big data and multicenter research are carried out,database information is improved,and association rules technology and traditional Chinese medicine research are combined to promote the development of Chinese medicine.
引文
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[11]黄小波,李宗信,陈文强,等.慢性疲劳综合征气虚与血虚病机关系的定量分析[J].中国中医药科技,2007,14(1):3-5.
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[13]孙媛媛,王明春,刘恩顺,等.ARDS证候特征的关联规则研究[J].天津职业技术师范大学学报,2013,23(3):29-35.
[14]黄文金,姚明龙,叶云金,等.关联规则在《中医妇科学》证素诊断中的应用[J].湖南中医杂志,2015,31(8):148-149.
[15]李文林,赵国平,陆建峰,等.关联规则在名医临证经验分析挖掘中的应用[J].南京中医药大学学报,2008,24(1):21-24.
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[18]孙秀丽,姜学永,李明.关联规则研究及在中风诊治中的应用分析[J].计算机技术与发展,2011,21(9):145-147,152.
[19]陈丽平,李建生,蔡永敏.基于聚类分析和关联规则的名老中医辨治风温规律研究[J].辽宁中医杂志,2016,43(10):2017-2020.
[20]朱蕾蕾,孙继佳,金采映,等.基于数据库及数据挖掘的中医医案方法学研究——蒋健教授治疗胃痛的临床经验总结[J].中华中医药杂志,2013,28(10):2888-2893.
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[22]李赛,聂莉芳,孙红颖.聂莉芳治疗慢性肾功能衰竭经验的关联规则分析[J].中华中医药杂志,2011,26(7):1602-1606.
[23]张润顺,周雪忠,姚乃礼,等.基于关联规则挖掘肝脾不调证中药配伍规律研究[J].中国中医药信息杂志,2010,17(2):97-99.
[24]陈菲,范欣生,王崇峻,等.基于关联规则等方法的肺胀方剂配伍规律研究[J].南京中医药大学学报,2013,29(6):514-516.
[25]沈斌.关联规则技术研究[M].杭州:浙江大学出版社,2012.
[26]贺志,黄厚宽,田盛丰.一种优化相关规则的发现方法[J].计算机学报,2006,29(6):906-913.
[27]HUI X,TAN P N,VIPIN K.Hyperclique pattern discovery[J].Data Mining and Knowledge Discovery.2006,13(2):219-242.
[28]沈斌,刘渊.物联网应用的安全与隐私问题审视[J].自然辩证法通讯,2011,33(6):77-83.
[2]王华,胡学钢.基于关联规则的数据挖掘在临床上的应用[J].安徽大学学报(自然科学版),2006,30(2):21-25.
[3]谭展鹏,罗翌,李际强,等.当代名中医痢疾医案43则中药配伍及方证规律的数据挖掘分析[J].临床医学工程,2011,18(3):412-414.
[4]汪受传,艾军,杨燕,等.基于关联规则的肺炎热郁痰瘀相关病机分析[J].南京中医药大学学报,2010,26(2):97-101.
[5]田琳,闫英杰,朱建贵,等.整理挖掘名老中医诊疗眩晕病辨证思维模式的思路与探讨[J].中国中医基础医学杂志,2006,12(8):618-620.
[6]胡波,刘红霞.基于中医文献探析女性不孕的症状分布规律[J].内蒙古中医药,2012,31(16):99-100.
[7]付先军,周永红,王中琳,等.基于频繁项集与关联规则挖掘技术探索王新陆临床用药及处方配伍规律的初步研究[J].中国中医药信息杂志,2010,17(9):92-94.
[8]张书河,郭爱银,陈群,等.肝脏辨证常见证型辨证论治文献的关联规则数据挖掘研究(一)[J].中华中医药学刊,2009,27(12):2622-2624.
[9]钟颖,胡雪蕾,陆建峰.基于关联规则和决策树的中医胃炎诊断分析[J].中国中医药信息杂志,2008,18(8):97-99.
[10]沈亚诚,陈燕升,王小云.绝经综合征中医证候规律的数据挖掘研究[J].南方医科大学学报,2008,28(8):1369-1371.
[11]黄小波,李宗信,陈文强,等.慢性疲劳综合征气虚与血虚病机关系的定量分析[J].中国中医药科技,2007,14(1):3-5.
[12]陈明,杨慧芳,余蕾.基于关联规则的肝硬变辨证数据挖掘研究[J].河南中医,2009,29(3):258-260.
[13]孙媛媛,王明春,刘恩顺,等.ARDS证候特征的关联规则研究[J].天津职业技术师范大学学报,2013,23(3):29-35.
[14]黄文金,姚明龙,叶云金,等.关联规则在《中医妇科学》证素诊断中的应用[J].湖南中医杂志,2015,31(8):148-149.
[15]李文林,赵国平,陆建峰,等.关联规则在名医临证经验分析挖掘中的应用[J].南京中医药大学学报,2008,24(1):21-24.
[16]梁卫.酒精性肝病的中医辨证规律研究[D].南京:南京中医药大学,2013.
[17]时丽莎,鲁明羽,李丹.关联规则在冠心病中医临床证型诊断中的应用[J].广西师范大学学报(自然科学版),2008,26(3):206-209.
[18]孙秀丽,姜学永,李明.关联规则研究及在中风诊治中的应用分析[J].计算机技术与发展,2011,21(9):145-147,152.
[19]陈丽平,李建生,蔡永敏.基于聚类分析和关联规则的名老中医辨治风温规律研究[J].辽宁中医杂志,2016,43(10):2017-2020.
[20]朱蕾蕾,孙继佳,金采映,等.基于数据库及数据挖掘的中医医案方法学研究——蒋健教授治疗胃痛的临床经验总结[J].中华中医药杂志,2013,28(10):2888-2893.
[21]陈欣然.基于数据挖掘技术的近15年反流性食管炎中医临床期刊文献研究[D].北京:北京中医药大学,2014.
[22]李赛,聂莉芳,孙红颖.聂莉芳治疗慢性肾功能衰竭经验的关联规则分析[J].中华中医药杂志,2011,26(7):1602-1606.
[23]张润顺,周雪忠,姚乃礼,等.基于关联规则挖掘肝脾不调证中药配伍规律研究[J].中国中医药信息杂志,2010,17(2):97-99.
[24]陈菲,范欣生,王崇峻,等.基于关联规则等方法的肺胀方剂配伍规律研究[J].南京中医药大学学报,2013,29(6):514-516.
[25]沈斌.关联规则技术研究[M].杭州:浙江大学出版社,2012.
[26]贺志,黄厚宽,田盛丰.一种优化相关规则的发现方法[J].计算机学报,2006,29(6):906-913.
[27]HUI X,TAN P N,VIPIN K.Hyperclique pattern discovery[J].Data Mining and Knowledge Discovery.2006,13(2):219-242.
[28]沈斌,刘渊.物联网应用的安全与隐私问题审视[J].自然辩证法通讯,2011,33(6):77-83.