Development of a machine learning-based model for predicting adverse pregnancy outcomes in women with polycystic ovary syndrome (PCOS): a retrospective observational study protocol.
- DOI
- 10.1136/bmjopen-2025-112190
- Published
- 2026 Jul 10
- Container
- BMJ open
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1136/bmjopen-2025-112190,
title = {Development of a machine learning-based model for predicting adverse pregnancy outcomes in women with polycystic ovary syndrome (PCOS): a retrospective observational study protocol.},
author = {Seyedi R and Mirghafourvand M and Tanha J and Majd HA and Nahidi F},
year = {2026},
journal = {BMJ open},
doi = {10.1136/bmjopen-2025-112190},
url = {https://doi.org/10.1136/bmjopen-2025-112190}
}RIS
TY - JOUR TI - Development of a machine learning-based model for predicting adverse pregnancy outcomes in women with polycystic ovary syndrome (PCOS): a retrospective observational study protocol. AU - Seyedi R AU - Mirghafourvand M AU - Tanha J AU - Majd HA AU - Nahidi F PY - 2026 JO - BMJ open DO - 10.1136/bmjopen-2025-112190 UR - https://doi.org/10.1136/bmjopen-2025-112190 ER -
APA
R, S., M, M., J, T., HA, M., & F, N. (2026). Development of a machine learning-based model for predicting adverse pregnancy outcomes in women with polycystic ovary syndrome (PCOS): a retrospective observational study protocol.. BMJ open. https://doi.org/10.1136/bmjopen-2025-112190
Source records
- pubmed · retrieved 2026-09-26T10:09:52.957Z