Division of Forensic Odontology and Disaster Oral Medicine, Department of Forensic Science, Iwate Medical University, Iwate, 028-3694, Japan.
Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul, 03080, Republic of Korea.
Sci Rep. 2023 Jan 13;13(1):726. doi: 10.1038/s41598-023-28086-1.
Teeth are known to be the most accurate age indicators of human body and are frequently applied in forensic age estimation. We aimed to validate data mining-based dental age estimation, by comparing the accuracy of the estimation and classification performance of 18-year thresholds with conventional methods and with data mining-based age estimation. A total of 2657 panoramic radiographs were collected from Koreans and Japanese populations aged 15 to 23 years. They were subdivided into a training and internal test set of 900 radiographs each from Koreans, and an external test set of 857 radiographs from Japanese. We compared the accuracy and classification performance of the test sets from conventional methods with those from the data mining models. The accuracy of the conventional method with the internal test set was slightly higher than that of the data mining models, with a slight difference (mean absolute error < 0.21 years, root mean square error < 0.24 years). The classification performance of the 18-year threshold was also similar between the conventional method and the data mining models. Thus, conventional methods can be replaced by data mining models in forensic age estimation using second and third molar maturity of Korean juveniles and young adults.
牙齿被认为是人体最准确的年龄指标，经常被用于法医年龄估计。我们旨在通过比较基于数据挖掘的牙齿年龄估计的准确性和分类性能，来验证 18 岁年龄阈值的准确性和分类性能，以验证基于数据挖掘的年龄估计。从年龄在 15 至 23 岁的韩国人和日本人中收集了总共 2657 张全景 X 光片。它们被分为来自韩国的 900 张训练和内部测试集，以及来自日本的 857 张外部测试集。我们比较了常规方法和数据挖掘模型的测试集的准确性和分类性能。内部测试集的常规方法的准确性略高于数据挖掘模型，差异较小（平均绝对误差<0.21 岁，均方根误差<0.24 岁）。18 岁年龄阈值的分类性能在常规方法和数据挖掘模型之间也相似。因此，在使用韩国青少年和年轻人的第二和第三磨牙成熟度进行法医年龄估计时，可以用数据挖掘模型代替常规方法。
