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An Architecture for Healthcare Big Data Management and Analysis

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Book cover Health Information Science (HIS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10038))

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Abstract

Within the recent decades, data volume increases exponentially in different industries especially in healthcare field. Extracting the hidden value behind such massive data has become one of the hottest topics for both industry and academy. In this paper, we present an architecture for healthcare big data management and analysis. Under the guidance of the proposed architecture, a prototype system constructed based on HBase, Hive, Spark MLLib and Spark Streaming is introduced for personal health problem detection and real-time vital sign monitoring.

This research is supported under the grant NO.71661167007 of National Natural Science of China.

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References

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  4. Apache Hive. http://hive.apache.org

  5. Apache HBase. http://hbase.apache.org

  6. Apache Spark. http://spark.apache.org

  7. Apache Hadoop. http://hadoop.apache.org

  8. Apache Sqoop. http://sqoop.apache.org

  9. Apache Oozie. http://oozie.apache.org

  10. Kettle. http://community.pentaho.com/projects/data-integration

  11. HL7. http://www.hl7.org

  12. ERH. http://www.himss.org/library/ehr

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Correspondence to Chao Ma .

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© 2016 Springer International Publishing AG

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Gui, H., Zheng, R., Ma, C., Fan, H., Xu, L. (2016). An Architecture for Healthcare Big Data Management and Analysis. In: Yin, X., Geller, J., Li, Y., Zhou, R., Wang, H., Zhang, Y. (eds) Health Information Science. HIS 2016. Lecture Notes in Computer Science(), vol 10038. Springer, Cham. https://doi.org/10.1007/978-3-319-48335-1_17

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  • DOI: https://doi.org/10.1007/978-3-319-48335-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48334-4

  • Online ISBN: 978-3-319-48335-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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