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Predicting vaginal birth after previous cesarean: Using machine‐learning models and a population‐based cohort in Sweden

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Predicting a woman’s probability of vaginal birth after cesarean could facilitate the antenatal decision‐making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women… Click to show full abstract

Predicting a woman’s probability of vaginal birth after cesarean could facilitate the antenatal decision‐making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women with only a cesarean delivery is more unpredictable. Therefore, to better predict vaginal birth in women with only one prior cesarean delivery and no vaginal deliveries would greatly benefit clinical practice and fill a key evidence gap in research. Our aim was to predict vaginal birth in women with one prior cesarean and no vaginal deliveries using machine‐learning methods, and compare with a US prediction model and its further developed model for a Swedish setting.

Keywords: vaginal birth; machine learning; using machine; birth; cesarean

Journal Title: Acta Obstetricia et Gynecologica Scandinavica
Year Published: 2020

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