Abstract:Background
High temperatures in urban areas owing to climate change and urban heat islands have led to an increase in the number of heatstroke patients. To prevent heatstroke, accurate heatstroke patient prediction model should be used to predict and alert people to their risk. However, most previous models have not tested sufficient training data, although susceptibility to heatstroke is likely to be dependent on year-wise trends and is susceptible to training data. We investigated an accurate heatstroke ris… Show more
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