Now showing items 1-2 of 2
Machine learning techniques for predicting depression and anxiety in pregnant and postpartum women during the COVID-19 pandemic: a cross-sectional regional study
(F1000 Research Ltd, 2022)
Background: Maternal depression and anxiety are significant public health concerns that play an important role in the health and well-being of mothers and children. The COVID-19 pandemic, the consequential lockdowns and ...
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID‑19 pandemic
(BioMed Central, 2023)
Background A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has ...