Artificial Intelligence and Machine Learning for predicting Major Obstetric Emergencies: Current Evidence, Clinical Translation, and Future Directions

Background

Obstetric emergencies, including postpartum hemorrhage, preeclampsia, and preterm birth, remain major contributors to preventable maternal and neonatal morbidity and mortality worldwide. Conventional risk assessment approaches often rely on predefined clinical variables and may insufficiently capture complex nonlinear relationships among maternal characteristics, biomarkers, imaging findings, and electronic health record data.