BACKGROUND: Postpartum depression (PPD) affects up to 20% of mothers globally. Early detection is vital for better outcomes, yet screening lacks scalability and predictive power. Artificial intelligence (AI)-through machine learning, deep learning, a...
Postpartum depression (PPD), a common mental illness among mothers, can affect the well-being of both mothers and their children. Early intervention is essential but hindered by difficulties in identifying at-risk women, as it remains unclear how soo...
Journal of reproductive and infant psychology
Jun 9, 2025
AIM: To evaluate the effectiveness of machine learning (ML) approaches in predicting individuals with postpartum depression (PPD), this study systematically reviewed and meta-analysed existing evidence.
BACKGROUND: Postpartum depression (PPD) is a mood disorder affecting 1 in 7 women after childbirth that is often underscreened and underdetected. If not diagnosed and treated, PPD is associated with long-term developmental challenges in the child and...
INTRODUCTION: Postpartum depression (PPD) is a prevalent mental health issue that poses significant challenges to maternal wellbeing and infant development. We aimed to determine the prevalence of PPD and to investigate its associated determinants an...
Depression during pregnancy and postpartum poses significant risks to both maternal and child well-being. The underlying biological mechanisms are unclear, but epigenetic variation could be exploited as a plausible candidate for early detection. We i...
AIM: The adoption of artificial intelligence (AI) tools is gaining traction in maternal mental health (MMH) research. Despite its growing usage, little is known about its prospects and challenges in low- and middle-income countries (LMICs). This stud...
INTRODUCTION: Postpartum depression (PPD) has numerous adverse impacts on the families of new mothers and society at large. Early identification and intervention are of great significance. Although there are many existing machine learning classifiers...
BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to develop and validate machine learning (ML) models using biopsychosocial predictors to predict the risk of PPD for perinatal women and to provide several...
BACKGROUND: Postpartum depression (PPD) is a prevalent mental health issue with significant impacts on mothers and families. Exploring reliable predictors is crucial for the early and accurate prediction of PPD, which remains challenging.
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