在牙科实践中进行骨质疏松症查的深度学习:系统性审查
Raiza Querrer1, Lorena S Vieira2, Ana Beatriz Teodoro1
1Department of Dentistry, Faculty of Health Sciences, University of Brasília, Brasília, DF, 70910-900, Brazil.
Dento maxillo facial radiology
|June 28, 2025
概括
深度学习 (DL) 工具显示出使用牙科成像进行骨质疏松症查的前景. 然而,有限的外部验证和缺乏临床整合阻碍了它们在牙科实践中的实际应用.
科学领域:
- 人工智能在牙科中的应用
- 医学成像分析 医学成像分析
- 骨质疏松症的诊断 骨质疏松症的诊断
背景情况:
- 骨质疏松症查对于早期干预至关重要.
- 牙科成像提供了一个潜在的,非侵入性查模式.
- 深度学习 (DL) 模型越来越多地被用于医学图像分析.
研究的目的:
- 通过牙科成像系统地审查DL工具在骨质疏松症查中的性能.
- 评估这些DL模型在牙科实践中的临床实施情况.
主要方法:
- 在七个数据库和灰色文献中进行了系统的搜索.
- 研究包括DL算法应用于牙科放射或CT扫描用于骨质疏松症查.
- 参考标准包括双能X射线吸收度 (DXA) 或专家评估.
主要成果:
- 13项研究符合纳入标准;DXA是共同的参考标准.
- 全景放射是主要的成像方式;准确度是主要的度量.
- 虽然ResNet和EfficientNet架构表现出卓越的性能,但没有报告外部验证或临床实施.
结论:
- 在牙科中,DL模型显示了支持性骨质疏松症查的潜力.
- 缺乏外部验证和临床整合限制了现实世界的适用性.
- 未来的研究应该优先考虑标准化和开发验证的,牙科实践可访问的系统.
关键词:
人工智能是一种人工智能.圆束计算机断层扫描技术牙科 牙科 牙科 牙科 牙科 牙科 牙科 牙科骨质疏松症是一种骨质疏松症.全景射线图 (Panoramic Radiography) 是一个全景射线图.更多相关视频
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