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Background
Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide

Background
Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.
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    Date Created
    • 2014-08-13
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1186/1471-2105-15-276
    • Identifier Type
      International standard serial number
      Identifier Value
      1471-2105
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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Kane, M. J., Price, N., Scotch, M., & Rabinowitz, P. (2014). Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks. BMC Bioinformatics, 15(1), 276. doi:10.1186/1471-2105-15-276

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