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Development and Validation of a Machine Learning Algorithm for Predicting the Risk of Postpartum Depression among Pregnant Women
OBJECTIVE: There is a scarcity in tools to predict postpartum depression (PPD). We propose a machine learning framework for PPD risk prediction using data extracted from electronic health records (EHRs). METHODS: Two EHR datasets containing data on 15,197 women from 2015 to 2018 at a single site, an...
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| Veröffentlicht in: | J Affect Disord |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7738412/ https://ncbi.nlm.nih.gov/pubmed/33035748 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jad.2020.09.113 |
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