用人工智能测量胸部X射线对心胸比率的测量 - - 一个系统性审查和元分析
Jakub Kufel1, Łukasz Czogalik2,3, Michał Bielówka2,3
1Department of Radiology and Nuclear Medicine, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Medyków 14, 40-752 Katowice, Poland.
人工智能 (AI) 在自动化从胸部X射线 (CXRs) 测量心胸比率 (CTR) 中表现出高效率,在心脏巨变检测中达到0.959 AUC. 标准化人工智能方法对于医疗成像诊断的可靠临床实施至关重要.
科学领域:
- 医学成像和诊断 医学成像和诊断
- 医疗保健中的人工智能
- 心脏病学和放射学.
背景情况:
- 胸部X射线 (CXR) 对于使用心胸比率 (CTR) 诊断诸如心壮病等疾病至关重要.
- 通过人工智能 (AI) 自动化CTR确定提供了改善患者护理和诊断效率的潜力.
研究的目的:
- 在自动化CTR评估中系统地审查和元分析AI模型的性能.
- 将人工智能驱动的CTR确定与人类评估进行比较,并确定临床使用的最佳模型.
主要方法:
- 根据PICO框架,在2023年6月进行了全面的数据库搜索.
- 包括的研究重点是从过去十年出版的站立位置CXR中对AI辅助的CTR评估.
- 通过使用PRISMA 2020指南和Cochrane偏差风险评估,分析了14项研究 (70,472个CXR).
主要成果:
- 人工智能模型显示,心脏大病检测的AUC总值为0.959 (95%CI为0.944-0.975).
- 对CTR测量的综合标准化平均差异为0.0353 (95%CI为0.147-0.0760).
- 观察到显著的异质性 (I2 89.97%),没有检测到出版偏差.
结论:
- 人工智能显示出对精确的CTR测量和CXRs中心壮病检测的重大承诺.
- 标准化人工智能方法和报告对于可靠的临床整合和推进医学成像诊断至关重要.
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