Article

A Particle Swarm-Optimized Multi-Layer Perceptron Model for Predicting Postpartum Depression Risk: A Machine Learning Study with SHAP Interpretation

2026-05-28

Abstract excerpt

<title>Abstract</title> <p>Background Postpartum depression (PPD) is one of the most prevalent mental illness following childbirth, imposing a substantial burden on families and society. Developing an algorithm-optimized machine learning tool for predicting PPD risk can assist in improving the accuracy of machine learning prediction tools. Methods We collected obstetric data and questionnaire data from 800 post...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 2e0bc94c-37bd-58fa-8dd9-0a37af0fc5a7
DOI: 10.21203/rs.3.rs-9675677/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Particle Swarm-Optimized Multi-Layer Perceptron Model for Predicting Postpartum Depression Risk: A Machine Learning Study with SHAP InterpretationDOI 10.21203/rs.3.rs-9675677/v1Read

Early risk stratification for antenatal depression-anxiety-sleep comorbidity: a three-factor nomogram based on PP-LCGM joint trajectoriesSemantic proximity Read

Explainable Machine Learning in the Prediction of DepressionSemantic proximity Read

Machine learning-optimized perinatal depression screening: Maximum impact, minimal burdenSemantic proximity Read

Stratifying Risk for Postpartum Depression at Time of Hospital DischargeSemantic proximity Read

Examining the Distinctions and Features of Anxiety and Depression in Patients with Early Postpartum Stress Urinary IncontinenceSemantic proximity Read

Development of multivariable models to predict perinatal depression before and after delivery using patient reported survey responses at weeks 4-10 of pregnancySemantic proximity Read

Life-course comorbidity patterns and integrated prediction of postpartum depression, multimorbidity, and symptom progressionSemantic proximity Read

Development and Validation of a Novel Culturally-Tailored Postpartum Depression Risk Scoring Scale (PDRS) in Malaysia: A Sequential Mixed-Methods StudySemantic proximity Read

An Explainable Maximum Expected Utility-Optimized Ensemble for Early Prediction of Gestational Diabetes MellitusSemantic proximity Read

An Explainable Stacking Ensemble with Cost-Sensitive Threshold Optimization for Gestational Diabetes Risk PredictionSemantic proximity Read

Adaptive Agentic AI-Driven Women's Digital Twin for Personalized High-Risk Pregnancy Prediction and Clinical Decision SupportSemantic proximity Read

Integrating Bleeding Velocity and Clinical Indicators into Machine Learning Models for Predicting Postpartum Hemorrhage: Development and External Validation StudySemantic proximity Read