Development and validation of a prediction model for intrapartum cesarean delivery based on the artificial neural networks approach: a protocol for a prospective nested case-control study.
- DOI
- 10.1136/bmjopen-2022-066753
- Published
- 2023 Feb 24
- Container
- BMJ open
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1136/bmjopen-2022-066753,
title = {Development and validation of a prediction model for intrapartum cesarean delivery based on the artificial neural networks approach: a protocol for a prospective nested case-control study.},
author = {Huang C and Luo B and Wang G and Chen P and Ren J},
year = {2023},
journal = {BMJ open},
doi = {10.1136/bmjopen-2022-066753},
url = {https://doi.org/10.1136/bmjopen-2022-066753}
}RIS
TY - JOUR TI - Development and validation of a prediction model for intrapartum cesarean delivery based on the artificial neural networks approach: a protocol for a prospective nested case-control study. AU - Huang C AU - Luo B AU - Wang G AU - Chen P AU - Ren J PY - 2023 JO - BMJ open DO - 10.1136/bmjopen-2022-066753 UR - https://doi.org/10.1136/bmjopen-2022-066753 ER -
APA
C, H., B, L., G, W., P, C., & J, R. (2023). Development and validation of a prediction model for intrapartum cesarean delivery based on the artificial neural networks approach: a protocol for a prospective nested case-control study.. BMJ open. https://doi.org/10.1136/bmjopen-2022-066753
Source records
- pubmed · retrieved 2026-09-26T00:13:28.416Z