Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births
This study successfully developed an interpretable ML model that predicts PPH with high accuracy. Future studies with larger and more diverse datasets are necessary to further validate and refine the model, particularly to assess its generalizability across different populations and healthcare settings.
Authors
- Hong‐Ping Lin (ORCID: https://orcid.org/0000-0001-9021-3146)
- Mengyuan Shao
- Dandan Zhang (ORCID: https://orcid.org/0000-0002-6584-5106)
- Zixuan Song (ORCID: https://orcid.org/0000-0002-8125-041X)
- Yangzi Zhou
- Xueting Chen
- Xiaoxue Wang
Institutions
- Shenyang First People's Hospital (CN)
- Shenyang 242 Hospital (CN)
- China Medical University (CN)
Publication Details
- Journal
- BMC Pregnancy and Childbirth
- Published
- 2025-05-03
- DOI
- https://doi.org/10.1186/s12884-025-07633-w
- Citations
- 6
- Primary Topic
- Trauma and Emergency Care Studies
- Type
- article
- Field-Weighted Citation Impact
- 13.52
Funders
- China Medical University
- Shengjing Hospital