Machine learning-based prediction of preterm birth risk using methylation changes in neonatal cord blood CpG sites

Machine learning-based prediction of preterm birth risk using methylation changes in neonatal cord blood CpG sites

Abstract Background Preterm birth, defined as delivery before 37 weeks of gestation, is a major cause of neonatal morbidity and mortality. DNA methylation changes at CpG sites have been associated with the risk of preterm birth. Objective This study aimed to identify differential CpG sites in cord b...

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Bibliographic Details
Main Authors: Yuxin Feng, Ying Ni, Wenkai Wang, Fen Guo, Liyu Wang, Fan Zhu, Luyao Zhang, Ying Feng
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Pregnancy and Childbirth
Subjects:
Preterm birth
CpG methylation
Cord blood
Machine learning
Lasso
Random forest
Online Access:https://doi.org/10.1186/s12884-025-07884-7
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