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Cell-free RNA and fully convolutional dense network-based early preeclampsia prediction.

作者信息

Zhao Zhuo, Li Bing, Xiao Xia, Liu Jinjun, Zheng Wang

机构信息

Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, P. R. China.

State Key Laboratory for Manufacturing System Engineering, Xi'an Jiaotong University, Xi'an, P. R. China.

出版信息

Clin Transl Med. 2023 Aug;13(8):e1371. doi: 10.1002/ctm2.1371.

DOI:10.1002/ctm2.1371
PMID:37581567
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10426394/
Abstract
摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/8de6c69304d5/CTM2-13-e1371-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/4b1ef4834863/CTM2-13-e1371-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/9dcd4b33b1ff/CTM2-13-e1371-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/8de6c69304d5/CTM2-13-e1371-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/4b1ef4834863/CTM2-13-e1371-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/9dcd4b33b1ff/CTM2-13-e1371-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35da/10426394/8de6c69304d5/CTM2-13-e1371-g001.jpg

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1
Cell-free RNA and fully convolutional dense network-based early preeclampsia prediction.基于无细胞RNA和全卷积密集网络的子痫前期早期预测
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[Latest Research Findings on Prediction of Preeclampsia in Pregnant Women Based on Analysis of Cell-Free RNA in Peripheral Blood].[基于外周血游离RNA分析预测孕妇子痫前期的最新研究发现]
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本文引用的文献

1
Early prediction of preeclampsia in pregnancy with cell-free RNA.用游离细胞 RNA 对妊娠子痫前期进行早期预测。
Nature. 2022 Feb;602(7898):689-694. doi: 10.1038/s41586-022-04410-z. Epub 2022 Feb 9.
2
A machine-learning-based algorithm improves prediction of preeclampsia-associated adverse outcomes.基于机器学习的算法可提高子痫前期相关不良结局的预测能力。
Am J Obstet Gynecol. 2022 Jul;227(1):77.e1-77.e30. doi: 10.1016/j.ajog.2022.01.026. Epub 2022 Feb 1.
3
RNA profiles reveal signatures of future health and disease in pregnancy.
RNA 谱揭示了妊娠中未来健康和疾病的特征。
Nature. 2022 Jan;601(7893):422-427. doi: 10.1038/s41586-021-04249-w. Epub 2022 Jan 5.
4
The competing risk approach for prediction of preeclampsia.预测子痫前期的竞争风险方法。
Am J Obstet Gynecol. 2020 Jul;223(1):12-23.e7. doi: 10.1016/j.ajog.2019.11.1247. Epub 2019 Nov 13.
5
Pre-eclampsia: pathophysiology and clinical implications.子痫前期：病理生理学与临床意义。
BMJ. 2019 Jul 15;366:l2381. doi: 10.1136/bmj.l2381.
6
Pre-eclampsia and risk of later kidney disease: nationwide cohort study.子痫前期与后期肾脏疾病风险：全国队列研究。
BMJ. 2019 Apr 29;365:l1516. doi: 10.1136/bmj.l1516.
7
Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.开发和验证一种基于深度学习的心电图预测高钾血症的模型。
JAMA Cardiol. 2019 May 1;4(5):428-436. doi: 10.1001/jamacardio.2019.0640.
8
Hypertensive Disorders of Pregnancy: ISSHP Classification, Diagnosis, and Management Recommendations for International Practice.妊娠期高血压疾病：国际实践的国际妊娠高血压研究学会分类、诊断及管理建议
Hypertension. 2018 Jul;72(1):24-43. doi: 10.1161/HYPERTENSIONAHA.117.10803.