MAKING USE OF MACHINE LEARNING MODEL FORECASTS TO INFORM MATERNAL HEALTH STRATEGIES IN ROMANIA
Keywords:
ANN, Forecasting, Maternal Mortality Ratio.Abstract
This research article employs annual time series data on MMR for Romania from 1985 to 2023 to predict future trends of MMR over the period 2024 to 2035. The forecast evaluation criteria of the applied model indicate that the ANN (12, 12, 1) model is stable. The neural network model projections revealed that MMR will remain very low throughout the out of sample period. Therefore, we encourage the government to identify and address local causes of preventable maternal deaths.
References
1.Merdad L and Ali M.M (2018). Timing of maternal death: Levels, trends, and ecological correlates using sibling data from 34 sub-Saharan African countries. PLoS ONE. 13(1):1–13.
2.World Health Organization (2018). Maternal mortality: Levels and trends 2000 to 2017. 2017. World Health Organization. Maternal mortality. Key facts. WHO. 2018. https://www.who.int/news-room/fact-sheet s/detail/maternal-mortality.
3.World Health Organization (2019). The World Health Statistics 2019. Monitoring health for the SDGs. 2019. https ://apps.who.int/iris/bitstream/handle/10665 /32483 5/97892 41565 707-eng.pdf?ua=1
4.World Health Organization (WHO, 2019). SDG 3: Ensure healthy lives and promote wellbeing for all at all ages. WHO. 2019. https ://www.who.int/sdg/targets/en/.
