Flu Detector: Estimating influenza-like illness rates from online user-generated content

نویسنده

  • Vasileios Lampos
چکیده

We provide a brief technical description of an online platform for disease monitoring, titled as the Flu Detector (fludetector.cs.ucl.ac.uk). Flu Detector, in its current version (v.0.5), uses either Twitter or Google search data in conjunction with statistical Natural Language Processing models to estimate the rate of influenza-like illness in the population of England. Its back-end is a live service that collects online data, utilises modern technologies for large-scale text processing, and finally applies statistical inference models that are trained offline. The front-end visualises the various disease rate estimates. Notably, the models based on Google data achieve a high level of accuracy with respect to the most recent four flu seasons in England (2012/13 to 2015/16). This highlighted Flu Detector as having a great potential of becoming a complementary source to the domestic traditional flu surveillance schemes.

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عنوان ژورنال:
  • CoRR

دوره abs/1612.03494  شماره 

صفحات  -

تاریخ انتشار 2016