ARGONet: the most accurate estimates of influenza activity available to date

AGRONet leverages its  information from electronic health records, flu-related Google searches and historical flu activity in a given location. Improved accuracy has been achieved by adding a second model, which draws on spatial-temporal patterns of flu spread in neighbouring areas [1]. Furthermore, the machine learning system was “trained” by feeding it flu predictions from both models as well as actual flu data, helping to reduce errors in the predictions.

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