Are Synthetic Data Derivatives the Future of Translational Medicine?
作者信息
Foraker Randi, Mann Douglas L, Payne Philip R O
机构信息
Institute for Informatics, Washington University School of Medicine, St. Louis, Missouri.
Center for Cardiovascular Research, Cardiovascular Division, Washington University School of Medicine, St. Louis, Missouri.
出版信息
JACC Basic Transl Sci. 2018 Nov 12;3(5):716-718. doi: 10.1016/j.jacbts.2018.08.007. eCollection 2018 Oct.
Abstract
摘要
相似文献
1
Are Synthetic Data Derivatives the Future of Translational Medicine?合成数据衍生物会是转化医学的未来吗？
JACC Basic Transl Sci. 2018 Nov 12;3(5):716-718. doi: 10.1016/j.jacbts.2018.08.007. eCollection 2018 Oct.
2
Synthetic Biology and the Translational Imperative.合成生物学与转化的必要性。
Sci Eng Ethics. 2019 Feb;25(1):33-52. doi: 10.1007/s11948-017-0011-3. Epub 2017 Dec 18.
3
Synthesis, reactions and biological activities of furochromones: a review.呋喃色酮的合成、反应及生物活性：综述。
Eur J Med Chem. 2015 Jan 27;90:633-65. doi: 10.1016/j.ejmech.2014.12.001. Epub 2014 Dec 2.
4
Translational synthetic biology.转化合成生物学
Syst Synth Biol. 2015 Dec;9(4):191-195. doi: 10.1007/s11693-015-9181-y. Epub 2015 Aug 18.
5
Multilevel Regulation and Translational Switches in Synthetic Biology.合成生物学中的多级调控与翻译开关
IEEE Trans Biomed Circuits Syst. 2015 Aug;9(4):485-96. doi: 10.1109/TBCAS.2015.2451707. Epub 2015 Aug 27.
6
Synthetic Gene Expression Circuits for Designing Precision Tools in Oncology.用于设计肿瘤学精准工具的合成基因表达电路
Front Cell Dev Biol. 2017 Aug 28;5:77. doi: 10.3389/fcell.2017.00077. eCollection 2017.
7
The problem with Big Data in Translational Medicine. A review of where we've been and the possibilities ahead.转化医学中的大数据问题。对我们的过往及未来可能性的回顾。
Appl Transl Genom. 2015 Aug 5;6:3-6. doi: 10.1016/j.atg.2015.07.005. eCollection 2015 Sep.
8
9
Anti-tubercular activity of a natural stilbene and its synthetic derivatives.一种天然芪及其合成衍生物的抗结核活性。
GMS Infect Dis. 2018 Feb 1;6:Doc01. doi: 10.3205/id000036. eCollection 2018.
10
[Translational dental medicine].[转化牙医学]
Hua Xi Kou Qiang Yi Xue Za Zhi. 2011 Jun;29(3):334-7.
引用本文的文献
1
2
Techniques to produce and evaluate realistic multivariate synthetic data.生成和评估逼真的多变量合成数据的技术。
Sci Rep. 2023 Jul 28;13(1):12266. doi: 10.1038/s41598-023-38832-0.
3
A Multifaceted benchmarking of synthetic electronic health record generation models.综合电子健康记录生成模型的多方面基准测试。
Nat Commun. 2022 Dec 9;13(1):7609. doi: 10.1038/s41467-022-35295-1.
4
Exploring the perceptions and acceptability of an integrated lifestyle database for public health research and service commissioning: a qualitative study.探索公众健康研究和服务委托的综合生活方式数据库的认知和可接受性：一项定性研究。
Perspect Public Health. 2024 Jul;144(4):222-231. doi: 10.1177/17579139221136726. Epub 2022 Nov 15.
5
Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.深度卷积生成对抗网络在医疗保健中的人工智能增强：以皮肤癌为例。
Sensors (Basel). 2022 Aug 17;22(16):6145. doi: 10.3390/s22166145.
6
Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research.利用人工智能和合成数据衍生物进行脊柱外科研究。
Global Spine J. 2023 Oct;13(8):2409-2421. doi: 10.1177/21925682221085535. Epub 2022 Apr 3.
7
Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C).展示一种评估合成地理空间和时间流行病学数据效用的方法：对美国国家 COVID 队列协作（N3C）中超过 180 万次 SARS-CoV-2 检测进行分析的结果。
J Am Med Inform Assoc. 2022 Jul 12;29(8):1350-1365. doi: 10.1093/jamia/ocac045.
8
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.
9
The National COVID Cohort Collaborative: Analyses of Original and Computationally Derived Electronic Health Record Data.国家 COVID 队列协作组：原始和计算衍生电子健康记录数据的分析。
J Med Internet Res. 2021 Oct 4;23(10):e30697. doi: 10.2196/30697.
10
Predicting mortality among patients with liver cirrhosis in electronic health records with machine learning.利用机器学习预测电子健康记录中肝硬化患者的死亡率。
PLoS One. 2021 Aug 31;16(8):e0256428. doi: 10.1371/journal.pone.0256428. eCollection 2021.
本文引用的文献
1
The Rising Cost of Developing Cardiovascular Therapies and Reproducibility in Translational Research: Do Not Blame It (All) on the Bench.心血管疾病治疗研发成本的上升与转化研究的可重复性：不要（全）归咎于实验台。
JACC Basic Transl Sci. 2017 Oct 30;2(5):627-629. doi: 10.1016/j.jacbts.2017.09.006. eCollection 2017 Oct.
2
The limitations of using randomised controlled trials as a basis for developing treatment guidelines.将随机对照试验作为制定治疗指南基础的局限性。
Evid Based Ment Health. 2018 Feb;21(1):4-6. doi: 10.1136/eb-2017-102701. Epub 2017 Jul 14.
3
A 'green button' for using aggregate patient data at the point of care.一个用于在医疗现场使用患者汇总数据的“绿色按钮”。
Health Aff (Millwood). 2014 Jul;33(7):1229-35. doi: 10.1377/hlthaff.2014.0099.
4
Open science and data sharing in clinical research: basing informed decisions on the totality of the evidence.临床研究中的开放科学与数据共享：基于全部证据做出明智决策。
Circ Cardiovasc Qual Outcomes. 2012 Mar 1;5(2):141-2. doi: 10.1161/CIRCOUTCOMES.112.965848.
5
A pragmatic view on pragmatic trials.关于实用性试验的务实观点。
Dialogues Clin Neurosci. 2011;13(2):217-24. doi: 10.31887/DCNS.2011.13.2/npatsopoulos.
6
The n-of-1 clinical trial: the ultimate strategy for individualizing medicine?n-of-1临床试验：个体化医疗的终极策略？
Per Med. 2011 Mar;8(2):161-173. doi: 10.2217/pme.11.7.
7
An interview with Robert S. Lane, Ph.D. Interviewed by Vicki Glaser.罗伯特·S·莱恩博士访谈录 采访者：维基·格拉泽
Vector Borne Zoonotic Dis. 2010 Mar;10(2):211-5. doi: 10.1089/vbz.2010.1502.
8
Biomedical informatics and outcomes research: enabling knowledge-driven health care.生物医学信息学与结果研究：推动知识驱动型医疗保健
Circulation. 2009 Dec 8;120(23):2393-9. doi: 10.1161/CIRCULATIONAHA.108.795526.
9
Evaluating the state-of-the-art in automatic de-identification.评估自动去识别技术的最新进展。
J Am Med Inform Assoc. 2007 Sep-Oct;14(5):550-63. doi: 10.1197/jamia.M2444. Epub 2007 Jun 28.
10
Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy.实用临床试验：提高临床研究在临床和卫生政策决策中的价值。
JAMA. 2003 Sep 24;290(12):1624-32. doi: 10.1001/jama.290.12.1624.
Zotero 插件