应用机器学习来评估雕塑牙的形态
Fang-Yu Fan1, Wei-Chun Lin1,2,3, Huei-Yu Huang4,5
1School of Dental Technology, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan.
Journal of dental sciences
|February 2, 2024
概括
这项研究开发了一种机器学习方法,以评估牙冠形态质量,准确度为70-75%. 该工具帮助牙科技术人员评估手工雕刻的牙假体.
科学领域:
- 牙科技术 牙科技术
- 生物医学工程 生物医学工程
- 在牙科领域的机器学习
背景情况:
- 牙冠形态对于牙科修复的可接受性至关重要.
- 对牙形态的准确评估对于牙科的质量控制至关重要.
- 目前用于评估牙形态的方法可能是主观的,耗时的.
研究的目的:
- 开发和验证基于机器学习的程序,用于评估牙冠形态.
- 量化机器学习在评估手工雕刻牙假肢质量的准确性.
- 提供一个工具,以协助牙科技术人员进行客观的质量评估.
主要方法:
- 数据收集涉及扫描621个牙石膏样本.
- 程序包括牙采集,扫描,数学分析和机器学习计算.
- 机器学习模型经过训练,并使用曲线下的面积 (AUC),精度和回忆等指标进行评估.
主要成果:
- 机器学习模型在评估牙形态方面实现了大约70%-75%的准确率.
- 曲线下的面积 (AUC) 值达到了0.72.
- 微平均和宏平均的精度和回忆率分别在0.75和0.72-0.73左右.
结论:
- 建立了使用机器学习来判断牙形态质量的可靠程序.
- 开发的方法显示了协助牙科技术人员评估手工雕刻的牙和石膏棒的潜力.
- 这项技术可以提高牙科技术人员掌握牙形态的学习过程和效率.
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