BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …

Background Unrestricted by time and place, electronic health (eHealth) provides solutions
for patient empowerment and value-based health care. Women in the reproductive age are …

Among all the forms of psychological and mental disorders, depression is the most common
form. Nowadays a large number of youths and adults around the world suffer from …

Depression is a common mental health condition for which many mobile apps aim to provide
support. This review aims to identify self-help apps available exclusively for people with …

Postpartum depression (PPD) is a detrimental health condition that affects 12% of new
mothers. Despite negative effects on mothers' and children's health, many women do not …

Objective: There is a scarcity in tools to predict postpartum depression (PPD). We propose a
machine learning framework for PPD risk prediction using data extracted from electronic …

Abstract Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and
results in severe depression and suicide attempts in the social community. Prompt actions …

Depression is a common illness worldwide with doubtless severe implications. Due to the
absence of early identification and treatment for depression, millions of individuals …

Background Clinical decision support systems (CDSSs) can provide various functions and
advantages to healthcare delivery. Quality healthcare during pregnancy and childbirth is of …

Postpartum depression is a serious health issue beyond the mental health problems that
affect mothers after childbirth. There are no predictive tools available to screen postpartum …