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利用公共可用数据上的人工智能辅助实施 1 型糖尿病筛查。

Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

机构信息

Diamyd Medical AB, Stockholm, Sweden.

University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia.

出版信息

Diabetologia. 2024 Jun;67(6):985-994. doi: 10.1007/s00125-024-06089-5. Epub 2024 Feb 14.

Abstract

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals. ASSET (AI for Sustainable Prevention of Autoimmunity in the Society; www.asset.healthcare ) is a public/private consortium that was established to contribute to research around screening for type 1 diabetes and particularly to how AI can drive the implementation of a precision medicine approach to disease prevention. ASSET will additionally focus on issues pertaining to operational implementation of screening. The authors of this article, researchers and clinicians active in the field of type 1 diabetes, met in an open forum to independently debate key issues around screening for type 1 diabetes and to advise ASSET. The potential use of AI in the analysis of longitudinal data from observational cohort studies to inform the design of improved, more individualised screening programmes was also discussed. A key issue was whether AI would allow the research community and industry to capitalise on large publicly available data repositories to design screening programmes that allow the early detection of individuals at high risk and enable clinical evaluation of preventive therapies. Overall, AI has the potential to revolutionise type 1 diabetes screening, in particular to help identify individuals who are at increased risk of disease and aid in the design of appropriate follow-up plans. We hope that this initiative will stimulate further research on this very timely topic.

摘要

1 型糖尿病群体围绕疾病风险早期筛查的益处和优势凝聚在一起。为了得到医疗保健提供者、监管机构和支付方的认可,筛查项目需要表明检测变量能够准确预测风险,并且建立个体化的风险知情监测计划,同时具有可操作性、成本效益和在人群层面上的可接受性。人工智能 (AI) 有潜力有助于解决这些问题,从识别和分层高危个体开始。ASSET(用于社会中自身免疫性糖尿病的可持续预防的人工智能;www.asset.healthcare)是一个公私联盟,旨在为 1 型糖尿病筛查的研究做出贡献,特别是为 AI 如何推动实施针对疾病预防的精准医学方法做出贡献。ASSET 将额外关注筛查的操作实施问题。本文的作者是活跃于 1 型糖尿病领域的研究人员和临床医生,他们在一个公开论坛上会面,就 1 型糖尿病筛查的关键问题进行独立辩论,并为 ASSET 提供建议。还讨论了在观察性队列研究的纵向数据中使用 AI 进行分析,以告知设计改进的、更个体化的筛查计划的潜在用途。一个关键问题是,AI 是否会让研究界和行业能够利用大型公共可用数据库来设计筛查计划,以便早期发现高风险个体,并能够对预防性治疗进行临床评估。总的来说,AI 有可能彻底改变 1 型糖尿病筛查,特别是有助于识别疾病风险增加的个体,并有助于设计适当的随访计划。我们希望这一举措将激发对这一非常及时的主题的进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f724/11058797/bda4202c6eba/125_2024_6089_Fig1_HTML.jpg

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