Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data
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Researchers are exploring the use of graph neural networks to forecast west nile virus. This approach aims to harness spatial dependence in geospatial data that has been sampled irregularly. The method's potential to improve forecasting of the virus is being examined.