A machine learning based system for postpartum depression risk detection and preventive care

Abstract

The present invention is related to a machine learning based system for postpartum depression risk detection and preventive care. This invention is an AI-powered system that predicts the risk of postpartum depression (PPD) by studying at a wide range of clinical and behavioral data. It uses supervised learning models like Random Forest and Logistic Regression, and pulls off an impressive accuracy—over 99%. That means one can actually trust the results. The system also highlights the most important factors, like hormone levels, how much sleep someone gets, and their stress levels—things that really matter for a new mom’s mental health. With this framework, healthcare providers can spot risks early, step in before problems get worse, and use it right in the clinic. It gives mothers better support during the postpartum period and helps them get the care they need, right when it matters most.