Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model
This prognostic model produced a 0.794 AUROC for predicting vaginal delivery. This, coupled with knowing the features influencing this outcome, may aid providers in assessing an individual's risk of CS after IOL and provide personalized counseling.
Authors
- Ana Luísa Areia (ORCID: https://orcid.org/0000-0003-2371-8907)
- Joana Simões (ORCID: https://orcid.org/0000-0002-5294-6282)
- Iolanda Ferreira (ORCID: https://orcid.org/0000-0002-4102-3116)
- João Correia (ORCID: https://orcid.org/0000-0001-5562-1996)
Institutions
- University of Coimbra (PT)
Publication Details
- Journal
- Acta Obstetricia Et Gynecologica Scandinavica
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1111/aogs.14953
- Citations
- 2
- Primary Topic
- Maternal and Perinatal Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 1.17
Funders
- Fundação para a Ciência e a Tecnologia