越来越多的基于人工智能 (AI) 的临床决策支持系统在临床前、计算机评估中显示出令人鼓舞的性能，但很少有人证明对患者护理有真正的获益。早期临床评估对于评估 AI 系统的小规模实际临床性能、确保其安全性、评估其使用周围的人为因素并为进一步的大规模试验铺平道路非常重要。然而，这些早期研究的报告仍然不足。本声明为人工智能驱动的决策支持系统的发展性和探索性临床研究 (DECIDE-AI) 提供了一个多利益相关者、基于共识的报告指南。
工作组进行了两轮修改的 Delphi 流程，以收集和分析专家对 AI 系统早期临床评估报告的意见。从 20 个预先定义的利益相关者类别中招募了专家。指南的最终组成和措辞 是在一次虚拟共识会议上确定的。清单和解释与详述 (E&E) 部分根据定性评估过程的反馈进行了改进。共有123名专家参加了Delphi第一轮，138名第二轮，16名共识会议和16名定性评估。 DECIDE-AI 报告指南包括 17 个 AI 特定报告项目（由 28 个子项目组成）和 10 个通用报告项目，每个项目都有一个 解释与阐述【E&E 】段落。
通过与一系列利益相关者协商和达成共识，工作组制定了一份指南，其中包含应在医疗保健中基于人工智能的决策支持系统的早期临床研究中报告的关键项目。通过提供最小报告项目的可操作清单，DECIDE-AI 指南将促进对这些研究的评估和其发现的可复制性。
A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico evaluation, but few have yet demonstrated real benefit to patient care. Early-stage clinical evaluation is important to assess an AI system's actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use and pave the way to further large-scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multi-stakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two-round, modified Delphi process to collect and analyze expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 pre-defined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. In total, 123 experts participated in the first round of Delphi, 138 in the second round, 16 in the consensus meeting and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI-specific reporting items (made of 28 subitems) and ten generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we developed a guideline comprising key items that should be reported in early-stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings.
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