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Synthetic data can aid the analysis of clinical outcomes: How much can it be trusted?

作者信息

Adam David

出版信息

Proc Natl Acad Sci U S A. 2024 Aug 6;121(32):e2414310121. doi: 10.1073/pnas.2414310121. Epub 2024 Jul 31.

DOI:10.1073/pnas.2414310121
PMID:39083423
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11317581/
Abstract
摘要

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本文引用的文献

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HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes.HAPNEST：高效、大规模生成和评估基因型和表型的合成数据集。
Bioinformatics. 2023 Sep 2;39(9). doi: 10.1093/bioinformatics/btad535.
2
Synthetic Data Generation by Artificial Intelligence to Accelerate Research and Precision Medicine in Hematology.人工智能生成合成数据以加速血液学研究和精准医学
JCO Clin Cancer Inform. 2023 Jun;7:e2300021. doi: 10.1200/CCI.23.00021.
3
The Use of Synthetic Electronic Health Record Data and Deep Learning to Improve Timing of High-Risk Heart Failure Surgical Intervention by Predicting Proximity to Catastrophic Decompensation.
利用合成电子健康记录数据和深度学习通过预测接近灾难性失代偿来改善高危心力衰竭手术干预的时机
Front Digit Health. 2020 Dec 7;2:576945. doi: 10.3389/fdgth.2020.576945. eCollection 2020.
4
Can synthetic data be a proxy for real clinical trial data? A validation study.合成数据能否替代真实的临床试验数据？一项验证性研究。
BMJ Open. 2021 Apr 16;11(4):e043497. doi: 10.1136/bmjopen-2020-043497.
5
Spot the difference: comparing results of analyses from real patient data and synthetic derivatives.找出差异：比较来自真实患者数据和合成衍生物的分析结果。
JAMIA Open. 2020 Dec 14;3(4):557-566. doi: 10.1093/jamiaopen/ooaa060. eCollection 2020 Dec.
6
Weaving technology and policy together to maintain confidentiality.将技术与政策相结合以维护保密性。
J Law Med Ethics. 1997 Summer-Fall;25(2-3):98-110, 82. doi: 10.1111/j.1748-720x.1997.tb01885.x.