使用人工智能进行诊断准确性研究的STARD-AI报告准则
Viknesh Sounderajah1,2, Ahmad Guni1,2, Xiaoxuan Liu3,4
1Institute of Global Health Innovation, Imperial College London, London, UK.
Nature medicine
|September 15, 2025
概括
新的STARD-AI声明提供了人工智能 (AI) 诊断准确性研究报告的指南. 它确保了人工智能诊断测试的透明报告,解决了偏见和可概括性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 诊断测试的准确性 诊断测试的准确性
背景情况:
- 诊断测试准确性报告标准 (STARD) 2015声明增强了诊断测试准确性研究的报告.
- 诊断测试中的人工智能 (AI) 提出了独特的报告挑战.
- 需要针对以人工智能为中心的诊断准确性研究量身定制的具体指南.
研究的目的:
- 引入STARD-AI声明,这是对以AI为中心的诊断测试准确性研究进行全面报告的最低标准.
- 为评估AI诊断工具的质量,偏见和适用性提供一个框架.
- 促进AI诊断研究报告的透明度和完整性.
主要方法:
- 开发涉及多个阶段,多个利益相关方的过程.
- 关键步骤包括文献审查,专家调查和患者/公众参与.
- 一个经过修改的Delphi共识流程,与240多个国际利益相关者一起,为最终的检查清单提供了信息.
主要成果:
- 该STARD-AI声明包括18个新的或修改的项目,基于STARD 2015.
- 它鼓励报告数据集实践和AI指数测试的评估.
- 重点是解决算法偏见和公平性.
结论:
- STARD-AI为以人工智能为中心的诊断准确性研究提供了全面和透明的报告.
- 该声明有助于利益相关者评估AI研究结果的偏见,适用性和通用性.
- 坚持STARD-AI对于在诊断中推进可靠的AI实施至关重要.
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