Abstract
In this paper, we have discussed the challenges in handling real-time medical big data collection and storage in health information system (HIS). Based on challenges, we have proposed a model for real-time analysis of medical big data. We exemplify the approach through Spark Streaming and Apache Kafka using the processing of health big data Stream. Apache Kafka works very well in transporting data among different systems such as relational databases, Apache Hadoop and non-relational databases. However, Apache Kafka lacks analyzing the stream, Spark Streaming framework has the capability to perform some operations on the stream. We have identified the challenges in current real-time systems and proposed our solution to cope with the medical big data streams.
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This work was supported by the Industrial Core Technology Development Program (10049079, Develop of mining core technology exploiting personal big data) funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea) and This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2011-0030079). This research work was also supported by Zayed University Research Initiative Fund R15098.
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Akhtar, U., Khattak, A.M., Lee, S. (2016). Challenges in Managing Real-Time Data in Health Information System (HIS). In: Chang, C., Chiari, L., Cao, Y., Jin, H., Mokhtari, M., Aloulou, H. (eds) Inclusive Smart Cities and Digital Health. ICOST 2016. Lecture Notes in Computer Science(), vol 9677. Springer, Cham. https://doi.org/10.1007/978-3-319-39601-9_27
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DOI: https://doi.org/10.1007/978-3-319-39601-9_27
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