MaternityAI: Smart Pregnancy Risk Prediction System

Abstract

Early pregnancy risk detection is crucial for maternal healthcare in order to avoid difficulties and this practice supports better health for expecting mothers together with their newborn. Conventional risk assessment techniques mostly rely on clinical knowledge, which can be laborious and subjective. To tackle these challenges, this research presents MaternityAI, a machine learning-based predictive system that categorizes pregnancy risks according to important health factors like age, blood pressure, and blood sugar levels. The suggested methodology analyzes patient data using sophisticated classification algorithms to produce precise and trustworthy risk predictions. Furthermore, feature importance analysis pinpoints important variables that lead to pregnancy difficulties, giving medical practitioners important information. MaternityAI improves maternal risk assessment by incorporating data-driven decision-making, which permits early interventions, lowers unfavorable outcomes, and improves mother care tactics. In the future, the model will be improved using deep learning methods and made available as a web application for clinical usage in real time.