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喉癌检测中的人工智能:系统性审查和元分析
Ali Alabdalhussein1, Mohammed Hasan Al-Khafaji1, Rusul Al-Busairi2
1Department of Otolaryngology, University Hospitals of Leicester, Leicester LE1 5WW, UK.
Current oncology (Toronto, Ont.)
|June 25, 2025
概括
人工智能 (AI) 有助于早期检测喉癌. 人工智能模型显示出高精度,灵敏度和特异性,改善了患者的治疗结果和喉的保存.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 早期发现喉癌对于患者的治疗结果和喉功能的保存至关重要.
- 人工智能 (AI) 可以加快可疑喉病变的分类.
- 缩短临床干预的时间是喉癌管理的一个关键目标.
研究的目的:
- 系统地评估AI在检测喉癌的诊断性能.
- 为了比较不同的AI模型的有效性,包括基于CNN的方法.
主要方法:
- 在五个主要数据库中进行了系统的文献搜索,截至2025年2月.
- 包括15项涉及17559名患者的研究.
- 使用QUADAS-2评估了偏差风险,使用Meta Disc 1.4.进行了数据合成.
主要成果:
- 人工智能在喉癌检测方面表现出高的诊断准确性,灵敏度为78%,特异性为86%.
- 对AI的综合诊断几率比为53.77 (95%CI:27.38到105.62).
- 基于卷积神经网络 (CNN) 的AI模型在图像分析和病变检测方面表现优于非CNN模型.
结论:
- 人工智能具有显著的诊断准确性,高灵敏度和喉癌检测的特异性.
- 人工智能工具适用于诊断喉癌的现实世界临床应用.
- 人工智能有助于更早,更准确地识别喉病变.
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