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

December 11, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Vasileios Lampos arXiv ID 1612.03494 Category cs.AI: Artificial Intelligence Cross-listed cs.CL, cs.SI Citations 3 Venue arXiv.org Last Checked 4 months ago
Abstract
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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