Abstract
Disease data provide an abundant source for chronic disease research. Hundreds of applications have been developed to deliver healthcare based on this big data. However, very few applications provide efficient chronic disease data visualization methods to better understand the results. This paper introduces a simple and practical way for visualizing the results of chronic disease detection and prediction. A model called IVIS4BigData has been used to implement the visualization procedure. This model not only demonstrates the historical data but also provides state-of-the-art visualization techniques. An exemplary set of scenarios corresponding to system design as well as visualization evaluation are given at last. Also we consulted several domain experts and common users about our visualization experimental results which satisfied their understanding about our systems. Finally conclusion and overlook of future work complete the paper.
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Acknowledgment
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2017R1A2B4010826) and the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-2013-0-00881) supervised by the IITP (Institute for Information & communication Technology Promotion).
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Li, D., Park, H.W., Batbaatar, E., Ryu, K.H. (2018). A Simply Way for Chronic Disease Prediction and Detection Result Visualization. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_64
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DOI: https://doi.org/10.1007/978-3-319-75417-8_64
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