人工智能在检测COVID-19肺炎的诊断性能 胸部成像
Savannah R Chapman1, Lauren Willner1, Alex Abouafech1
1School of Medicine, Lake Erie College of Osteopathic Medicine, Bradenton, USA.
Cureus
|February 19, 2026
概括
人工智能 (AI) 在使用胸部成像 (CXR和CT) 检测COVID-19肺炎方面表现有希望,其性能通常与放射科医生相匹配. 然而,普遍性和信任方面的挑战需要进一步研究以确保安全的临床整合.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 传染病诊断 传染病诊断 传染病诊断
背景情况:
- 由于COVID-19的流行,人们需要快速准确的诊断工具.
- 胸部成像 (CXR,CT) 和人工智能系统成为COVID-19诊断和工作流程的关键.
- 人工智能开发旨在支持图像解释和提高效率.
研究的目的:
- 审查使用CXR和CT检测COVID-19肺炎的AI模型的证据.
- 综合这些人工智能系统的诊断性能,局限性和临床影响.
- 评估包含的研究中的质量和偏差风险.
主要方法:
- 进行了PubMed文献搜索,截至2025年10月.
- 包括评估AI用于CXR/CT上的COVID-19肺炎检测的研究.
- 评估了诊断指标 (灵敏度,特异性,精度,AUC) 并使用QUADAS-2进行质量评估.
主要成果:
- 十一项研究符合纳入标准.
- CXR AI:灵敏度为80-98%,特异性为82-96%. CT AI:准确度在90-96%之间.
- 人工智能显示出强大的内部性能,但在外部验证上精度降低,突出了概括性问题.
结论:
- 人工智能模型在胸部成像上展示了COVID-19肺炎的有希望的诊断性能.
- 人工智能可以提高放射科医生的效率,但在概括性,适应性和临床医生的信任方面面临挑战.
- 未来的研究必须专注于外部验证和透明报告,以确保安全的AI集成.
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