人工智能实施对医学成像效率的影响 - - 一个系统的文献综述和元分析
Katharina Wenderott1, Jim Krups2, Fiona Zaruchas2
1Institute for Patient Safety, University Hospital Bonn, Bonn, Germany. katharina.wenderott@ukbonn.de.
NPJ digital medicine
|September 30, 2024
概括
医学成像中的人工智能 (AI) 显示出效率的前景,许多研究报告了任务时间的缩短. 然而,系统审查发现了相当大的异质性,限制了对AI的总体结论.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 临床工作流的优化 临床工作流优化
背景情况:
- 人工智能 (AI) 在医疗保健中的整合有可能提高临床医生的效率,特别是在临床成像方面.
- 现实世界的临床工作流正在越来越多地探索用于诊断支持的AI应用.
研究的目的:
- 系统地审查和评估AI在医学成像中的实施对现实世界的临床工作流效率的影响.
- 评估AI集成后任务时间和临床医生工作负载的变化.
主要方法:
- 在六个医学数据库中进行了系统审查,选了13,756条记录.
- 包括48项原始研究,两名审查员进行了双重选并评估了方法质量.
- 结果包括工作流的调整,任务时间的变化和临床医生的工作量,并对相关数据进行了元分析.
主要成果:
- 在33项测量任务时间的研究中,67%的研究报告说,人工智能实施后的任务时间减少了.
- 对12项研究的三次元分析没有显示出显著的整体效率影响.
- 确定了五种不同的AI集成工作流程,通常使用AI作为二级阅读器或用于初级案例识别.
结论:
- 临床成像中的AI应用主要在单个研究中显示效率提升.
- 研究中的大量异质性阻碍了对人工智能在成像任务中的整体有效性的强有力的推断.
- 通过标准化报告和现实数据收集进行进一步的研究对于了解人工智能对医疗保健工作流程的影响至关重要.
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