Risk assessment of drug-associated miscarriage using XGBoost and SHAP explainability: a real-world pharmacovigilance analysis based on the FAERS database

Machine learning and SHAP interpretability analysis based on the FAERS database effectively identified immunomodulators, antiviral drugs, and psychiatric/neuropsychiatric medications as potential risk signals associated with miscarriage. These findings underscore the need for individualized medication assessment that considers patient age and body weight, providing evidence-based guidance and early alerting for reference for drug risk assessment during pregnancy.