[1]张 润,冯云霞.基于改进 Apriori 算法的肺癌致病因素研究[J].计算机技术与发展,2020,30(02):143-147.[doi:10. 3969 / j. issn. 1673-629X. 2020. 02. 028]
　ZHANG Run,FENG Yun-xia.Research on Pathogenic Factors of Lung Cancer Based on Improved Apriori Algorithm[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(02):143-147.[doi:10. 3969 / j. issn. 1673-629X. 2020. 02. 028]
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基于改进 Apriori 算法的肺癌致病因素研究()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年02期
页码:
143-147
栏目:
应用开发研究
出版日期:
2020-02-10

文章信息/Info

Title:
Research on Pathogenic Factors of Lung Cancer Based on Improved Apriori Algorithm
文章编号:
1673-629X(2020)02--0143-05
作者:
张 润; 冯云霞
青岛科技大学 信息科学技术学院,山东 青岛 266000
Author(s):
ZHANG Run; FENG Yun-xia
School of Information Science and Technology,Qingdao University of Science and Technology, Qingdao 266000,China
关键词:
关联规则; Apriori算法; Hadoop; 肺癌
Keywords:
association rules; Apriori algorithm; Hadoop; lung cancer
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 02. 028
摘要:
随着人民生活水平的不断提高,肿瘤疾病的人数在不断增多,其中肺癌是21世纪严重危害人类健康的重大疾病。 面向肺癌电子病历如此庞大的数据量时,传统Apriori算法的串行计算方式需要频繁扫描数据库,会消耗巨大的内存占用 量。 对此,提出一种基于改进Apriori算法的肺癌风险评估因素分析的方法。 运用Hadoop平台实现并行Apriori算法的优 化,应用HBase文件存储系统对海量数据分布式存储以及MapReduce框架进行分布式计算,最后给出基于Hadoop平台和 MapReduce分布式计算模型的执行流程和测试结果。 实验结果表明,改进算法在处理大数据及时有较好的执行效率以及 良好的可扩展性,得出了肺癌的疾病模式与致病因素之间的隐匿规则,从而验证了改进后的Apriori算法对于辅助肺癌临 床实验具有重要的意义。
Abstract:
With the continuous improvement of people’s living standards,the number of cancer diseases is increasing,among which lung cancer is a serious threat to human health in the 21st century. Faced with such a large data volume in electronic medical records of lung cancer,the serial calculation method of traditional Apriori algorithm requires frequent scanning of the database,which will consume huge memory consumption. To this end,a method based on improved Apriori algorithm for lung cancer risk assessment factor analysis is proposed. The Hadoop platform isused to optimize the parallel Apriori algorithm. The HBase file storage system is used to distribute distributed data and the MapReduce framework. Finally,the execution flow and test results based on Hadoop platform and MapReduce distributed computing model are given. The experiment shows that the improved algorithm has better execution efficiency and scalability in dealing with big data in time,and obtains the hidden rules between the disease pattern and the pathogenic factors of lung cancer,thus verifying the improved Apriori algorithm is of great significance for assisting clinical trials to assist lung cancer.

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更新日期/Last Update: 2020-02-10