A method for predicting postpartum depression via an ensemble neural network model

The research results show that the proposed model effectively improves the prediction performance of PPD, which can provide guiding suggestions for relevant medical staff and postpartum women in clinical decision-making. In the future, plans include collecting more disease datasets, using the proposed model to predict these diseases, and constructing an online disease prediction platform to embed the proposed model, which will help with real-time disease prediction.

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Publication Details

Journal
Frontiers in Public Health
Published
2025-04-14
DOI
https://doi.org/10.3389/fpubh.2025.1571522
Citations
1
Primary Topic
Maternal Mental Health During Pregnancy and Postpartum
Type
article
Field-Weighted Citation Impact
1.88
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article

A method for predicting postpartum depression via an ensemble neural network model

Dongqin Zhou, Yangyang Lin
1 citations
Frontiers in Public Health
Maternal Mental Health During Pregnancy and Postpartum
1.88
article

A method for predicting postpartum depression via an ensemble neural network model

Dongqin Zhou, Yangyang Lin
article en
1 citations

Abstract

The research results show that the proposed model effectively improves the prediction performance of PPD, which can provide guiding suggestions for relevant medical staff and postpartum women in clinical decision-making. In the future, plans include collecting more disease datasets, using the proposed model to predict these diseases, and constructing an online disease prediction platform to embed the proposed model, which will help with real-time disease prediction.

Frontiers in Public HealthVol. 13
Zhejiang DongFang Vocational and Technical College (CN), Wenzhou City People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 17%
Maternal Mental Health During Pregnancy and Postpartum
1.88
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