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人工智能从口腔内照片中检测牙周病:系统性审查
Kaijing Mao1, Khaing Myat Thu1, Kuo Feng Hung1
1Faculty of Dentistry, The University of Hong Kong, Hong Kong Special Administrative Region, China.
International dental journal
|July 10, 2025
概括
人工智能 (AI) 显示出从牙科照片中检测牙周病的前景,但临床应用需要改进报告,标准化指标和增强数据质量,以便可靠地使用.
科学领域:
- 牙科诊断 牙科诊断 牙科诊断
- 医疗保健中的人工智能
- 牙周病学 牙周病学
背景情况:
- 牙周病的诊断依赖于临床检查和放射学.
- 数字口内摄影为疾病检测提供了一个非侵入性的数据源.
- 人工智能 (AI) 模型越来越多地被用于自动诊断工具.
研究的目的:
- 系统地审查使用口腔内照片检测牙周病的AI模型的方法质量和临床性能.
- 为了确定当前的趋势,局限性,以及未来的研究方向在这个领域.
主要方法:
- 对同行评审的出版物和会议记录进行系统审查.
- 包括使用数字口内摄影用于AI模型培训和验证的临床研究.
- 分析AI模型特征,任务 (分类,检测,细分) 和性能指标.
主要成果:
- 26项研究符合纳入标准,使用各种图像采集设备和参考标准.
- 人工智能模型的性能差异很大,分类准确度从0.46到1.00不等,检测准确度从0.56到0.78,细分IOU得分从0.43到0.70.
- 有限的研究采用了多个口内视图或专家验证的数据集.
结论:
- 人工智能模型展示了从口内照片中检测牙周病的潜力.
- 临床实施受到不一致的报告,评估指标,数据质量和缺乏外部验证的阻碍.
- 未来的研究必须优先考虑标准化,透明度,可解释性和使用临床黄金标准进行强有力的验证.
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