开发用于牙编号和检测的人工智能模型:系统审查
Prabhadevi C Maganur1, Satish Vishwanathaiah1, Mohammed Mashyakhy2
1Division of Pediatric Dentistry, Department of Preventive Dental Science, College of Dentistry, Jazan university, Jazan, Saudi Arabia.
International dental journal
|June 9, 2024
概括
人工智能 (AI) 模型在牙科放射学中显示出高精度的自动牙检测 (99.4%) 和编号 (98%). 这种人工智能技术在牙科放射学中提供了作为补充诊断工具的巨大潜力.
科学领域:
- 牙科 牙科是指牙科的专业.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 牙科放射是牙科实践中至关重要的工具,也是推进人工智能 (AI) 技术的宝贵资源.
- 人工智能越来越多地被用于牙科放射学中的应用,特别是用于图像分析和解释.
研究的目的:
- 系统地审查和批判性地评估人工智能模型的开发和性能,用于使用牙-口-面部放射图像检测和编号牙.
- 评估人工智能在牙科放射学中的应用的诊断准确性和证据确定性.
主要方法:
- 一个系统的审查,遵守PRISMA-DTA诊断测试准确性标准.
- 在多个数据库 (PubMed,Scopus,Embase,Cochrane,Web of Science,Google Scholar,沙特数字图书馆) 进行全面的电子搜索,查找2018年至2023年间发表的文章.
- 使用 QUADAS-2 的偏差风险评估和使用 GRADE 方法对 16 篇选定的文章进行证据确定性评估.
主要成果:
- 人工智能主要应用于自动牙检测和编号,包括在圆束计算机断层扫描 (CBCT) 图像中的识别和牙科治疗模式识别.
- 审查的AI模型在牙检测方面达到99.4%的最高精度,在牙编号方面达到98%的最高精度.
- 在这个领域对AI应用的证据确定性使用GRADE方法进行了评估.
结论:
- 人工智能技术展示了高度准确性和牙科放射学中自动牙检测和编号的潜力.
- 人工智能可以作为一种有价值的补充诊断工具,增强牙科放射学的能力.
- 进一步的研究和验证得到了当前人工智能模型有希望的性能指标的支持.
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