Predicting peripartum depression using elastic net regression and machine learning: the role of remnant cholesterol

Predicting peripartum depression using elastic net regression and machine learning: the role of remnant cholesterol

Abstract Background Traditional statistical methods have dominated research on peripartum depression (PPD), but innovative approaches may provide deeper insights. This study aims to predict the impact factors of PPD using elastic net regression (ENR) combined with machine learning (ML) model. Method...

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Bibliographic Details
Main Authors: Hongxu Chen, Denglan Wang, Juanjuan Shen, Baoyan Guo, Chun Song, Duo Ma, Yan Wu, Guohui Liu, Guangxue Chen, Yan Ni, Tiantian Kong, Fan Wang
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Pregnancy and Childbirth
Subjects:
Peripartum depression
Remnant cholesterol
Elastic net regression
Machine learning
Random forests
Online Access:https://doi.org/10.1186/s12884-025-07656-3
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https://doi.org/10.1186/s12884-025-07656-3

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