Interpretable machine learning model for predicting low birth weight in singleton pregnancies: a retrospective cohort study
This study demonstrated that the LR and XGBoost model exhibited clinically meaningful predictive performance in identifying factors associated with LBW in singleton pregnancies. Pregnant women with a gestational age of less than 37 weeks, a gestational BMI below 18 kg/m², maternal age under than 25 years, and maternal comorbidities such as HDP or fetal distress are at higher risk of delivering LBW infants.
Authors
- Yong Gao (ORCID: https://orcid.org/0000-0002-7191-9351)
- Fuyan Shi (ORCID: https://orcid.org/0000-0002-0972-8335)
- Yiyu Zhang (ORCID: https://orcid.org/0000-0001-6033-5898)
- Nian X. Sun (ORCID: https://orcid.org/0000-0002-3120-0094)
- Linrui Xu
- Suzhen Wang (ORCID: https://orcid.org/0000-0003-2076-529X)
- Xiaoqing Cong (ORCID: https://orcid.org/0009-0002-2008-6924)
- Xiaojuan Wu (ORCID: https://orcid.org/0000-0002-3803-6661)
- Qingxiang Zhao
Institutions
- Weifang Medical University (CN)
- Binzhou Medical University (CN)
- Shandong University of Aeronautics (CN)
Publication Details
- Journal
- BMC Pregnancy and Childbirth
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1186/s12884-025-08318-0
- Citations
- 1
- Primary Topic
- Gestational Diabetes Research and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.06