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超越算法潜力:人工智能时代的正牙拔牙决策
Samer Mheissen1, Carlos Flores-Mir2
1Private Practice, Anderson, SC, USA. mheissen@yahoo.com.
Evidence-based dentistry
|February 9, 2026
概括
人工智能 (AI) 模型在预测正义牙提取方面表现出中度至高精度. 卷积神经网络 (CNN) 显示出有前途的诊断性能,有助于治疗规划.
科学领域:
- 矯正牙科 矯正牙科是一種矯正牙科.
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- ортодонтика治疗规划往往涉及牙提取的复杂决策.
- 评估AI在预测提取需求中的准确性对于临床应用至关重要.
研究的目的:
- 系统地审查和元分析人工智能模型的诊断准确性,以预测在正治疗规划中需要提取的需求.
主要方法:
- 进行了观察性研究的系统审查.
- 搜索了四个数据库,资格标准集中在将人工智能模型与正牙医的决定进行比较的研究上.
- 对灵敏度和特异性的元分析使用随机效应和混合效应模型进行.
主要成果:
- 包括七项横截面研究,利用各种人工智能模型,如CNN (ResNet,VGG),随机森林和决策树.
- 对AI模型的聚合灵敏度为70% (95% CI:0.61-0.78),聚合特异性为90% (95% CI:0.87-0.92).
- 基于CNN的模型,特别是ResNet和VGG,表现相似,尽管差异在统计学上并不显著.
结论:
- 人工智能模型,特别是CNN模型,在预测正牙切除术时表现出中度至高的诊断准确度.
- 这些发现表明,人工智能可以在正牙治疗规划中成为一种有价值的工具,尽管确定性很低.
- 进一步的研究可能会完善AI的作用并提高诊断精度.
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