Deep Data-Driven Neural Network for Malaria Vaccination
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Malaria still remains a significant global health challenge that requires innovative strategies for its control and eventual eradication. In this article, we present a malaria vaccination model to assess and predict the effects of vaccination interventions. The model parameters are learned via feedforward Neural Network. We employed Residual Neural Network and Recurrent Neural Networks(GRU, LSTM, and BiLSTM) to predict and forecast daily and sequential malaria cases using generated data from the Ghana vaccination population.
