ERA 伦理委员会关于在肾脏研究中使用大数据和人工智能的伦理考虑。

IF 4.8 2区 医学 Q1 TRANSPLANTATION Nephrology Dialysis Transplantation Pub Date : 2024-11-21 DOI:10.1093/ndt/gfae267
Wim Van Biesen, Jadranka Buturovic Ponikvar, Monica Fontana, Peter Heering, Mehmet S Sever, Simon Sawhney, Valerie Luyckx
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引用次数: 0

摘要

在本文中,我们将重点讨论如何确保大数据能够促进肾病患者的治疗效果。与此相关的伦理问题是,作为肾脏病学界,我们是否能够以及应该如何鼓励收集患者的大数据。我们确定了使用大数据的一些伦理思考及其重要性和相关性。此外,我们还平衡了优势和缺陷,并讨论了合法、合乎伦理地使用大数据的要求。在进行任何分析之前,数据的收集、组织和整理都是最重要的工作。因此,在这一阶段必须格外注意确保数据的质量,以避免出现垃圾进垃圾出的问题,并避免此类分析导致病人护理效果不佳。对数据的访问应该有条不紊,以便正确有效地使用数据。这就意味着必须安全地储存数据,只有有权这样做的人才能访问这些数据。同时,有权获取数据的人应能够高效地获取数据,以免妨碍相关研究。对观察数据的分析本身容易出现许多错误和偏差。这些偏差最终都可能导致提供低质量的医疗服务。因此,安全平台还应确保使用正确的方法来解释现有数据。这就需要一支由医学研究专家和数据科学家组成的高技能人才队伍密切合作。只有这样,我们的患者才能充分受益于人工智能和大数据的潜力。
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Ethical considerations on the use of big Data and Artificial Intelligence in kidney research from the ERA ethics committee.

In the current paper, we will focus on requirements to ensure big data can advance the outcomes of our patients suffering from kidney disease. The associated ethical question is whether and how we as a nephrology community can and should encourage the collection of big data of our patients. We identify some ethical reflections on the use of big data, and their importance and relevance. Furthermore, we balance advantages and pitfalls and discuss requirements to make legitimate and ethical use of big data possible. The collection, organization and curation of data come upfront in the pipeline prior to any analyses. Great care must therefore be taken to ensure quality of the data at this stage, to avoid the garbage in garbage out problem and suboptimal patient care as a consequence of such analyses. Access to the data should be organized so that correct and efficient use of data is possible. This means that data must be stored safely, so that only those entitled to do so can access them. At the same time, those who are entitled to access the data should be able to do so in an efficient way, so as not to hinder relevant research. Analysis of observational data is itself prone to many errors and biases. Each of these biases can finally result in provision of low-quality medical care. Secure platforms should therefore also ensure correct methodology is used to interpret the available data. This requires close collaboration of a skilled workforce of experts in medical research and data scientists. Only then will our patients be able to benefit fully from the potential of AI and big data.

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来源期刊
Nephrology Dialysis Transplantation
Nephrology Dialysis Transplantation 医学-泌尿学与肾脏学
CiteScore
10.10
自引率
4.90%
发文量
1431
审稿时长
1.7 months
期刊介绍: Nephrology Dialysis Transplantation (ndt) is the leading nephrology journal in Europe and renowned worldwide, devoted to original clinical and laboratory research in nephrology, dialysis and transplantation. ndt is an official journal of the [ERA-EDTA](http://www.era-edta.org/) (European Renal Association-European Dialysis and Transplant Association). Published monthly, the journal provides an essential resource for researchers and clinicians throughout the world. All research articles in this journal have undergone peer review. Print ISSN: 0931-0509.
期刊最新文献
Determination of urine volume and glomerular filtration rate using d-serine and d-asparagine. Ethical considerations on the use of big Data and Artificial Intelligence in kidney research from the ERA ethics committee. Neutralizing the IL-7Rα limits injury in experimental ANCA-associated glomerulonephritis. Seasonal variations in the association between proteinuria, CKD, and kidney failure. CD38 ligation in sepsis promotes nicotinamide phosphoribosyltransferase-mediated IL-6 production in kidney stromal cells.
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