Using machine learning to identify quality-of-care predictors for emergency caesarean sections: a retrospective cohort study.

This study provides empirical evidence for the importance of team member qualifications and experience relative to other predictors of arrival-to-delivery during ECS. Machine learning provides a promising method for expanding our current knowledge about the relative importance of different factors in predicting outcomes of complex obstetric events.