An explainable machine learning model in predicting vaginal birth after cesarean section
Objective Vaginal birth after cesarean section (VBAC) is recommended by obstetrical guidelines or expert consensuses. However, no valid tools can exactly predict who can have a vaginal birth among eligible candidates with one prior cesarean section. In recent years, machine learning (ML) is graduall...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | The Journal of Maternal-Fetal & Neonatal Medicine |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/14767058.2025.2546544 |
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