Postpartum depression risk prediction using explainable machine learning algorithms

Postpartum depression risk prediction using explainable machine learning algorithms

ObjectivePostpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an explainable machine learning model to predict the risk of PPD and to identify its key pred...

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Bibliographic Details
Main Authors: Xudong Huang, Lifeng Zhang, Chenyang Zhang, Jing Li, Chenyang Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Medicine
Subjects:
postpartum depression
machine learning
predictive model
influencing factors
maternal health
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1565374/full
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