Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods Comparison Study

Abstract : Traditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users' activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data.
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Submitted on : Friday, July 12, 2019 - 9:54:52 AM
Last modification on : Monday, July 15, 2019 - 11:14:34 AM

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Canelle Poirier, Audrey Lavenu, Valérie Bertaud, Boris Campillo-Gimenez, Emmanuel Chazard, et al.. Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods Comparison Study. JMIR Public Health and Surveillance, 2018, 4 (4), pp.e11361. ⟨10.2196/11361⟩. ⟨hal-01998537⟩

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