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| Content Provider | Springer Nature Link |
|---|---|
| Author | Yao, Qin Tian, Yu Li, Peng Fei Tian, Li Li Qian, Yang Ming Li, Jing Song |
| Copyright Year | 2015 |
| Abstract | Secondary use of medical big data is increasingly popular in healthcare services and clinical research. Understanding the logic behind medical big data demonstrates tendencies in hospital information technology and shows great significance for hospital information systems that are designing and expanding services. Big data has four characteristics – Volume, Variety, Velocity and Value (the 4 Vs) – that make traditional systems incapable of processing these data using standalones. Apache Hadoop MapReduce is a promising software framework for developing applications that process vast amounts of data in parallel with large clusters of commodity hardware in a reliable, fault-tolerant manner. With the Hadoop framework and MapReduce application program interface (API), we can more easily develop our own MapReduce applications to run on a Hadoop framework that can scale up from a single node to thousands of machines. This paper investigates a practical case of a Hadoop-based medical big data processing system. We developed this system to intelligently process medical big data and uncover some features of hospital information system user behaviors. This paper studies user behaviors regarding various data produced by different hospital information systems for daily work. In this paper, we also built a five-node Hadoop cluster to execute distributed MapReduce algorithms. Our distributed algorithms show promise in facilitating efficient data processing with medical big data in healthcare services and clinical research compared with single nodes. Additionally, with medical big data analytics, we can design our hospital information systems to be much more intelligent and easier to use by making personalized recommendations. |
| Starting Page | 1 |
| Ending Page | 11 |
| Page Count | 11 |
| File Format | |
| ISSN | 01485598 |
| Journal | Journal of Medical Systems |
| Volume Number | 39 |
| Issue Number | 3 |
| e-ISSN | 1573689X |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2015-02-10 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Medical big data Hadoop MapReduce User-generated content Sqoop Mahout Health Informatics Statistics for Life Sciences, Medicine, Health Sciences |
| Content Type | Text |
| Resource Type | Article |
| Subject | Health Information Management Information Systems Health Informatics |
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