在诊断垂直根骨折时使用人工智能 - - 一项系统性审查
Abdulmajeed Saeed Alshahrani1, Ahmed Ali Alelyani1, Ahmad Jabali2
1Department of Restorative Dentistry, Division of Endodontics, College of Dentistry, Najran University, Najran 61441, Saudi Arabia.
Diagnostics (Basel, Switzerland)
|February 13, 2026
概括
人工智能 (AI) 在检测牙科成像模式中的垂直根骨折 (VRF) 方面表现有前途. 形束计算断层扫描 (CBCT) 与人工智能相结合,产生了最高的准确性,尽管需要更多的研究.
科学领域:
- 牙科 牙科是指牙科的专业.
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 垂直根骨折 (VRFs) 由于微妙的放射性迹象,难以诊断.
- 现有的成像技术和跨模式的人工智能性能尚未成熟.
研究的目的:
- 系统地审查和比较人工智能辅助的VRF检测在周围放射学,全景放射学和CBCT.
- 评估诊断性能,方法质量和AI在VRF检测中的局限性.
主要方法:
- 在主要数据库中,系统的文献审查至2025年1月.
- 包括使用人工智能用于在周围,全景或CBCT图像中检测VRF的研究.
- 数据提取侧重于人工智能模型,数据集,成像,验证和诊断指标;偏差风险使用QUADAS-2进行评估.
主要成果:
- 十项研究主要使用基于CNN的AI模型.
- 基于CBCT的AI获得了最高的准确性 (91.4-97.8%) 和特异性 (90.7-100%).
- 周周放射模型显示高精度 (高达95.7%),而全景放射模型具有较低的灵敏度但高精度.
结论:
- 人工智能辅助的VRF检测是有希望的,特别是CBCT.
- 目前的证据受到方法异质性和临床验证不足的限制.
- 需要使用标准化方法和临床验证进行进一步的研究.
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