Mar 26, 2024 · We developed and externally validated a machine-learning model to predict postpartum depression (PPD) using data from electronic health records (EHRs).
Sep 17, 2021 · Conclusions. PPD risk prediction using EHR data may provide a complementary quantitative and objective tool for PPD screening, allowing earlier ...
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Apr 30, 2020 · The aims of this study are to compare the effects of four different machine learning models using data during pregnancy to predict PPD.
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May 15, 2020 · Although 13% of surveyed women with a recent live birth reported depressive symptoms during the postpartum period, one in five did not report a health care ...
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Postpartum depression can be predicted using machine learning. · Predictors are from the prepartum and early antepartum periods and were easily obtainable.
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Predicting women with depressive symptoms postpartum with machine ...
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Apr 12, 2021 · In this study, we evaluated a range of different machine learning (ML) methods to predict pregnant women at risk for postpartum depressive (PPD) ...
Apr 15, 2021 · This cohort study evaluates approaches for reducing bias in machine learning models to predict postpartum depression using data from Black ...
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[PDF] Postpartum Depression - New York State Office of Mental Health
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Nov 1, 2023 · c) Screening for substance use disorders (SUD) with validated tools. ... Risk Factors Associated with Risk for Postpartum Depression: A ...
Jan 15, 2021 · We propose a machine learning framework for PPD risk prediction using data extracted from electronic health records (EHRs).
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Jul 24, 2024 · INTERVENTION: The EPDS tool was provided for self-screening at home, enabling mothers to assess their symptoms and seek timely medical ...