Enhanced AI Based Methodologies for Detection of Prenatal Postnatal Depression in Women

Abstract

The introduction of Artificial Intelligence (AI) and Machine Learning (ML) technologies has newline been causing a revolutionary change in the field of mental health, especially in prenatal and newline postpartum depression prediction. It enables healthcare professionals to make timely, informed newline decisions, which in turn improves mothers well-being and contribute to family dynamics pos newlineitively, and improvements in infant development and the mother-infant bond. newline During delivery (prenatal) and postpartum (1-6 weeks) after childbirth are two of the most newline critical stages where psychological disturbance remains undiagnosed, which also leads to the newline main cause of late-stage depression. This thesis investigates, develops, and proposes a trian newlinegulation model for prenatal and postnatal mental depression prediction. Organized interviews newline were used to gather data from women who were admitted for childbirth at SRM Medical Col newlinepsychological questionnaire responses, and social media posts make up the dataset newline