Personalized machine learning model for predicting successful vaginal delivery during the active phase of labor
- DOI
- 10.1016/j.ajogmf.2026.102176
- Published
- 2026-11
- Container
- American Journal of Obstetrics & Gynecology MFM
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.ajogmf.2026.102176,
title = {Personalized machine learning model for predicting successful vaginal delivery during the active phase of labor},
author = {Lee Reicher and Emmanuel Attali and Yoav Baruch and Daniel Gabai and Michal Rosenberg and Omri Dominsky and Sharon Napadenski and Nadav Rappoport and Yariv Yogev},
year = {2026},
journal = {American Journal of Obstetrics \& Gynecology MFM},
doi = {10.1016/j.ajogmf.2026.102176},
url = {https://doi.org/10.1016/j.ajogmf.2026.102176}
}RIS
TY - JOUR TI - Personalized machine learning model for predicting successful vaginal delivery during the active phase of labor AU - Lee Reicher AU - Emmanuel Attali AU - Yoav Baruch AU - Daniel Gabai AU - Michal Rosenberg AU - Omri Dominsky AU - Sharon Napadenski AU - Nadav Rappoport AU - Yariv Yogev PY - 2026 JO - American Journal of Obstetrics & Gynecology MFM DO - 10.1016/j.ajogmf.2026.102176 UR - https://doi.org/10.1016/j.ajogmf.2026.102176 ER -
APA
Reicher, L., Attali, E., Baruch, Y., Gabai, D., Rosenberg, M., Dominsky, O., Napadenski, S., Rappoport, N., & Yogev, Y. (2026). Personalized machine learning model for predicting successful vaginal delivery during the active phase of labor. American Journal of Obstetrics & Gynecology MFM. https://doi.org/10.1016/j.ajogmf.2026.102176
Source records
- crossref · retrieved 2026-11-07T02:01:13.802Z