Machine learning prediction models for mode of delivery in prolonged pregnancies in Sweden.

At a 50% threshold, the mixed naïve bayes (study group 1: 15%) and random forest classifier (SG1: 10%) showed the highest sensitivity in predicting cesarean section with an increasing trend along the study groups (Table 2 , Table S4 supplementary material).

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In contrast, for spontaneous vaginal birth sensitivity reached 91% using a neural network and 90% with logistic regression with a decreasing trend along the study groups (Table 2 , Table S4 supplementary material).

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