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.

Graphical Abstract

中文翻译：

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利用人工智能对公开数据协助实施1型糖尿病筛查

1 型糖尿病界正在围绕疾病风险早期筛查的好处和优势进行联合。为了被医疗保健提供者、监管机构和付款人接受，筛查计划需要证明测试变量可以进行准确的风险预测，建立个性化的风险知情监测计划，以及操作可行性、成本效益和人群接受度。人工智能 (AI) 有潜力为解决这些问题做出贡献，首先是对高危人群进行识别和分层。 ASSET（AI for Sustainable Prevention of Autoimmunity in the Society；www.asset.healthcare）是一个公共/私人联盟，其成立的目的是为围绕 1 型糖尿病筛查的研究做出贡献，特别是人工智能如何推动精准医疗的实施疾病预防的方法。 ASSET还将关注与筛查操作实施相关的问题。本文的作者、活跃于 1 型糖尿病领域的研究人员和临床医生在一个开放论坛上会面，独立辩论有关 1 型糖尿病筛查的关键问题，并为 ASSET 提供建议。还讨论了人工智能在分析观察队列研究的纵向数据中的潜在用途，以便为改进、更个性化的筛查计划的设计提供信息。一个关键问题是人工智能是否允许研究界和行业利用大型公开数据存储库来设计筛查计划，以便及早发现高风险个体并实现预防性治疗的临床评估。总体而言，人工智能有可能彻底改变 1 型糖尿病筛查，特别是帮助识别患病风险较高的个体，并帮助设计适当的后续计划。我们希望这一举措能够激发对这个非常及时的主题的进一步研究。

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