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Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models.

Daniel Adedayo AdeyinkaNazeem Muhajarine
Published in: BMC medical research methodology (2020)
GMDH-type neural network performed better in predicting and forecasting of under-five mortality rates for Nigeria, compared to the ARIMA and Holt-Winters models. Therefore, GMDH-type ANN might be more suitable for data with non-linear or unknown distribution, such as childhood mortality. GMDH-type ANN increases forecasting accuracy of childhood mortalities in order to inform policy actions in Nigeria.
Keyphrases
  • neural network
  • cardiovascular events
  • risk factors
  • healthcare
  • mental health
  • early life
  • coronary artery disease
  • type diabetes
  • artificial intelligence