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Prediction of Preeclampsia from Clinical and Genetic Risk Factors in Early and Late Pregnancy Using Machine Learning and Polygenic Risk Scores.
medRxiv [Preprint]. 2023 Feb 7:2023.02.03.23285385. doi: 10.1101/2023.02.03.23285385.
medRxiv. 2023.
PMID: 36798188
Free PMC article.
Updated.
Preprint.
An Interpretable Longitudinal Preeclampsia Risk Prediction Using Machine Learning.
Eberhard BW, Cohen RY, Rigoni J, Bates DW, Gray KJ, Kovacheva VP.
Eberhard BW, et al.
medRxiv [Preprint]. 2023 Aug 16:2023.08.16.23293946. doi: 10.1101/2023.08.16.23293946.
medRxiv. 2023.
PMID: 37645797
Free PMC article.
Preprint.
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Deep Survival Analysis for Interpretable Time-Varying Prediction of Preeclampsia Risk.
Eberhard BW, Gray KJ, Bates DW, Kovacheva VP.
Eberhard BW, et al.
medRxiv [Preprint]. 2024 Jan 19:2024.01.18.24301456. doi: 10.1101/2024.01.18.24301456.
medRxiv. 2024.
PMID: 38293230
Free PMC article.
Preprint.
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Preeclampsia Prediction Using Machine Learning and Polygenic Risk Scores From Clinical and Genetic Risk Factors in Early and Late Pregnancies.
Kovacheva VP, Eberhard BW, Cohen RY, Maher M, Saxena R, Gray KJ.
Kovacheva VP, et al. Among authors: eberhard bw.
Hypertension. 2024 Feb;81(2):264-272. doi: 10.1161/HYPERTENSIONAHA.123.21053. Epub 2023 Oct 30.
Hypertension. 2024.
PMID: 37901968
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