Prediction of chemical miscarriage in assisted reproductive technology pregnancies using machine learning: A developmental study

Background

Early miscarriage is a common complication following assisted reproductive technology (ART), affecting 20–30% of conceptions and creating challenges for patient counseling and treatment planning. Accurate prediction remains difficult because of the multifactorial nature of miscarriage and variability in ART outcomes. Machine learning (ML) offers promising opportunities for individualized risk assessment.