Abstract
Monitoring and analysing epidemic trends is essential for an early warning system to impend outbreaks that could become public health emergencies and help track progress towards specified goals. In this paper, we present an intelligent platform for influenza monitoring and analysis, which pipelines the process of utilising the raw surveillance data to visualise and model the graphical representations of the data. In particular, the platform involves data preparation, time series prediction and data visualisation components. Within the data visualisation component, we deliver statistical analysis that draws insights from the plain data. Further, the platform is capable of predicting future trends based on various machine learning models that are learned from previous years.
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Chen, X., Chen, Z., Wang, Z., Qiu, R., Luo, Y. (2022). FluMA: An Intelligent Platform for Influenza Monitoring and Analysis. In: Hua, W., Wang, H., Li, L. (eds) Databases Theory and Applications. ADC 2022. Lecture Notes in Computer Science, vol 13459. Springer, Cham. https://doi.org/10.1007/978-3-031-15512-3_12
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DOI: https://doi.org/10.1007/978-3-031-15512-3_12
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