在非综合征性低牙症儿童中延迟牙发育:使用机器学习方法估计牙年龄的横截面研究.
Marine Crosnier1, Pierre-Hadrien Decaup1,2,3, Frédéric Santos2
1UFR des Sciences Odontologiques, Univ. De Bordeaux, Bordeaux, France.
Orthodontics & craniofacial research
|December 29, 2025
概括
缺牙症或牙缺失与牙发育时间的改变有关. 机器学习准确地估计了缺牙儿童的牙年龄,有助于正牙和法医应用.
科学领域:
- 儿科牙科 儿科牙科
- 牙科发展 牙科发展
- 法医牙科 法医牙科
背景情况:
- 非综合征性下牙会影响牙发育.
- 准确的牙年龄估计对于临床和法医评估至关重要.
- 机器学习为复杂的发育分析提供了新的方法.
研究的目的:
- 为了研究下牙对放射性牙发育的影响.
- 通过机器学习估计双边下生殖的儿童的牙年龄.
- 分析牙发育延迟与生长模式的关系.
主要方法:
- 对626名儿童 (6-15岁) 的回顾性横截面研究.
- 使用Demirjian方法评估牙年龄;机器学习 (随机森林) 用于在生长病例中估计年龄.
- 计算牙发育延迟 (DA-CA);多重线性回归用于识别预测因子.
主要成果:
- 机器学习模型实现了牙年龄预测的高精度 (R2 > 0.95).
- 与对照组相比,患有低牙的儿童表现出牙发育显著延迟 (0.77年).
- 代理状态,性别和时间年龄是牙发育迟缓的重要预测因素.
结论:
- 牙下垂症与牙发育时间的改变有关.
- 机器学习提供了一种可靠的方法,用于在牙缺失的情况下估计牙年龄.
- 这种方法在矯正牙科和法医科学中具有潜在的应用,用于年龄估计.
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