FluMA: An Intelligent Platform for Influenza Monitoring and Analysis

Conference or Workshop item

Chen, Xi, Chen, Zhi, Wang, Zijian, Qui, Ruihong and Luo, Yadan. 2022. "FluMA: An Intelligent Platform for Influenza Monitoring and Analysis." 33rd Australasian Database Conference (ADC 2022). Sydney, Australia 02 - 04 Sep 2022 Switzerland . Springer. https://doi.org/10.1007/978-3-031-15512-3_12

Paper/Presentation Title	FluMA: An Intelligent Platform for Influenza Monitoring and Analysis
Authors	Chen, Xi, Chen, Zhi, Wang, Zijian, Qui, Ruihong and Luo, Yadan
Journal or Proceedings Title	Proceedings of the 33rd Australasian Database Conference (ADC 2022)
Journal Citation	13459, pp. 153-157
Number of Pages	5
Year	2022
Publisher	Springer
Place of Publication	Switzerland
ISSN	0302-9743
	1611-3349
ISBN	9783031155116
	9783031155123
Digital Object Identifier (DOI)	https://doi.org/10.1007/978-3-031-15512-3_12
Web Address (URL) of Paper	https://link.springer.com/chapter/10.1007/978-3-031-15512-3_12
Web Address (URL) of Conference Proceedings	https://link.springer.com/book/10.1007/978-3-031-15512-3
Conference/Event	33rd Australasian Database Conference (ADC 2022)
Event Details	33rd Australasian Database Conference (ADC 2022) Parent Australasian Database Conference Delivery In person Event Date 02 to end of 04 Sep 2022 Event Location Sydney, Australia
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.
Keywords	Medical data analysis; Epidemiological modeling
Contains Sensitive Content	Does not contain sensitive content
ANZSRC Field of Research 2020	4602. Artificial intelligence
Public Notes	Files associated with this item cannot be displayed due to copyright restrictions.
Series	Lecture Notes in Computer Science
Byline Affiliations	University of Queensland

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