Use of artificial intelligence to predict mean time to delivery following cervical ripening with dinoprostone vaginal insert

Jouffray, Clementine; Corroënne, Romain; Hachem, Hady El; Gillard, Philippe; Legendre, Guillaume; Levast, Fanny; Saulnier, Patrick; Descamps, Philippe; Verhaeghe, Caroline; Bouet, Pierre‐Emmanuel

doi:10.1016/j.ejogrb.2021.08.031

Cited by 1 publication

(2 citation statements)

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“…Regarding IOL, the choice of cervical ripening methods varied according to WHO recommendations and Bishop scores. These included oxytocin infusion, prostaglandin analogues and extra‐amniotic balloon catheters 1 , 48 , 49 . Premature rupture of membranes was defined as membrane rupture at term before labor onset.…”

Section: Methodsmentioning

confidence: 99%

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Ensemble learning for fetal ultrasound and maternal–fetal data to predict mode of delivery after labor induction

Ferreira,

Simões,

Pereira

et al. 2024

Sci Rep

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Providing adequate counseling on mode of delivery after induction of labor (IOL) is of utmost importance. Various AI algorithms have been developed for this purpose, but rely on maternal–fetal data, not including ultrasound (US) imaging. We used retrospectively collected clinical data from 808 subjects submitted to IOL, totaling 2024 US images, to train AI models to predict vaginal delivery (VD) and cesarean section (CS) outcomes after IOL. The best overall model used only clinical data (F1-score: 0.736; positive predictive value (PPV): 0.734). The imaging models employed fetal head, abdomen and femur US images, showing limited discriminative results. The best model used femur images (F1-score: 0.594; PPV: 0.580). Consequently, we constructed ensemble models to test whether US imaging could enhance the clinical data model. The best ensemble model included clinical data and US femur images (F1-score: 0.689; PPV: 0.693), presenting a false positive and false negative interesting trade-off. The model accurately predicted CS on 4 additional cases, despite misclassifying 20 additional VD, resulting in a 6.0% decrease in average accuracy compared to the clinical data model. Hence, integrating US imaging into the latter model can be a new development in assisting mode of delivery counseling.

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Section: Methodsmentioning

confidence: 99%

“…Premature rupture of membranes was defined as membrane rupture at term before labor onset. Prolonged pregnancy was determined at ≥ 41 weeks 48 . The definition of labor was the presence of regular uterine contractions with cervical changes 50 .…”

Section: Methodsmentioning

confidence: 99%