{"title":"基于hadoop的医疗保健和临床数据处理分布式计算算法","authors":"Jun Ni, Ying Chen, Jie Sha, Minghuan Zhang","doi":"10.1109/ICICSE.2015.41","DOIUrl":null,"url":null,"abstract":"There exit a huge demand on utilizing big data technology to process healthcare related patients data for healthcare information extraction and medical knowledge discovery. In this paper, we briefly review the demands and application potentials using big data technology with an emphasis on common challenges. After briefly addressing the Hadoop/MapReduce code components and modules, we use a simple clinic data to demonstrate how to map and reduce on small dataset with illustrated workflow. We give simple scenario of using other MapReduce calculation modules for counting and classification. This serves as a basic step into future utilization of big data to healthcare domain.","PeriodicalId":159836,"journal":{"name":"2015 Eighth International Conference on Internet Computing for Science and Engineering (ICICSE)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Hadoop-Based Distributed Computing Algorithms for Healthcare and Clinic Data Processing\",\"authors\":\"Jun Ni, Ying Chen, Jie Sha, Minghuan Zhang\",\"doi\":\"10.1109/ICICSE.2015.41\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There exit a huge demand on utilizing big data technology to process healthcare related patients data for healthcare information extraction and medical knowledge discovery. In this paper, we briefly review the demands and application potentials using big data technology with an emphasis on common challenges. After briefly addressing the Hadoop/MapReduce code components and modules, we use a simple clinic data to demonstrate how to map and reduce on small dataset with illustrated workflow. We give simple scenario of using other MapReduce calculation modules for counting and classification. This serves as a basic step into future utilization of big data to healthcare domain.\",\"PeriodicalId\":159836,\"journal\":{\"name\":\"2015 Eighth International Conference on Internet Computing for Science and Engineering (ICICSE)\",\"volume\":\"144 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Eighth International Conference on Internet Computing for Science and Engineering (ICICSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSE.2015.41\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Eighth International Conference on Internet Computing for Science and Engineering (ICICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2015.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hadoop-Based Distributed Computing Algorithms for Healthcare and Clinic Data Processing
There exit a huge demand on utilizing big data technology to process healthcare related patients data for healthcare information extraction and medical knowledge discovery. In this paper, we briefly review the demands and application potentials using big data technology with an emphasis on common challenges. After briefly addressing the Hadoop/MapReduce code components and modules, we use a simple clinic data to demonstrate how to map and reduce on small dataset with illustrated workflow. We give simple scenario of using other MapReduce calculation modules for counting and classification. This serves as a basic step into future utilization of big data to healthcare domain.