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

Betina Ristorp AndersenIda AmmitzbøllJesper HinrichSune LehmannCharlotte Vibeke RingstedEllen Christine Leth LøkkegaardMartin G Tolsgaard
Published in: BMJ open (2022)
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.
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