儿童牙科人工智能:一个系统的审查和元分析
Nevra Karamüftüoğlu1, Büşra Yavuz Üçpunar1, İrem Birben1
1Department of Pediatric Dentistry, Gülhane Faculty of Dentistry, Health Sciences University, 06830 Ankara, Türkiye.
Children (Basel, Switzerland)
|January 28, 2026
概括
人工智能 (AI) 在改善儿科牙科的诊断准确性方面显示出很大的前景,特别是在虫检测方面. 然而,诸如有限的验证和方法的变化等挑战阻碍了即时的临床使用.
科学领域:
- 儿科牙科 儿科牙科
- 人工智能的人工智能
- 诊断的准确性 诊断的准确性
背景情况:
- 人工智能 (AI) 在儿童牙科中越来越重要,以改善诊断.
- 人工智能应用包括虫检测,风险预测和发育评估.
研究的目的:
- 系统地审查和元分析儿童牙科应用中人工智能模型的诊断性能.
- 评估当前AI证据的临床翻译潜力.
主要方法:
- 在主要数据库 (PubMed,Scopus,Web of Science,Embase) 进行系统搜索,遵循PRISMA-DTA的指导方针.
- 包括儿童群体 (≤18岁) 的AI诊断/预测模型研究.
- 使用随机效应模型计算聚合灵敏度,特异性和AUC,检查异质源.
主要成果:
- 包括32项研究进行了定性综合,15项研究进行了定量分析.
- 放射性虫检测:聚合灵敏度为0.91,特异性为0.97,AUC为0.98.
- 人工智能预测模型:聚合灵敏度0.86,特异性0.82,AUC0.89;深度学习优于传统的ML.
结论:
- 人工智能显示出显著的潜力,可以提高儿科牙科的诊断准确性.
- 临床实施受到外部验证不足和方法不一致的限制.
- 未来的研究应该集中在多中心数据集,协调的工作流程和可解释的AI (XAI) 临床翻译上.
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