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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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Podrobná bibliografie
Vydáno v:J Affect Disord
Hlavní autoři: Zhang, Yiye, Wang, Shuojia, Hermann, Alison, Joly, Rochelle, Pathak, Jyotishman
Médium: Artigo
Jazyk:Inglês
Vydáno: 2020
Témata:
On-line přístup: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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