透明报告是可重复放射性AI研究的核心:呼吁采取行动
Samuel J White1, Kasper L Yaxley2, Minh-Son To3
1Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, South Australia, Australia; School of Dentistry and Medical Sciences, Faculty of Science and Health, Charles Sturt University, Wagga Wagga, New South Wales, Australia.
European journal of radiology
|March 10, 2026
概括
放射学人工智能 (AI) 的透明报告对于可重复性和临床使用至关重要. 解决研究设计,标准,准则和数据共享方面的挑战将提高人工智能研究的可信度和安全实施.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 医疗成像医学成像
背景情况:
- 人工智能 (AI) 放射学研究的可复制性是监管批准和临床采用的一个重要障碍.
- 在整个人工智能研究过程中,透明的报告对于验证,证据综合和安全的临床整合至关重要.
研究的目的:
- 确定放射性AI研究中透明报告的关键障碍.
- 提出可行的解决方案,以提高放射学AI研究的可复制性.
主要方法:
- 分析放射性AI研究中的报告实践.
- 确定研究设计,标准化,指南协调和数据/代码可访问性方面的挑战.
- 制定策略,以解决已识别的报告障碍.
主要成果:
- 报告往往是事后的想法,没有纳入研究设计,导致丢失的细节.
- 期刊和资助者的不一致标准阻碍了完整性评估.
- 复杂和重叠的AI报告准则造成了作者负担和报告异质性.
- 数据和代码的有限可用性阻碍了独立验证.
结论:
- 加强透明报告对于放射学中可复制和临床适用的AI至关重要.
- 将报告纳入研究设计,调整利益相关者的期望和改善资源可访问性是关键.
- 这些步骤将提高可信度,促进评估,并支持安全的临床AI实施.
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