Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms

HIGHLIGHTS

• who: Kyriaki Kalimeri and colleagues from the Editor:, Northeastern University, France have published the research work: Unsupervised extraction of epidemic syndromes from participatory influenza surveillance self-reported symptoms, in the Journal: (JOURNAL)
• what: The authors propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the platforms and performs an algorithmic detection of groups of symptoms called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific . . .
  

   

  

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