Department of Orthodontics and Craniofacial Anomalies, Poznań University of Medical Sciences, Collegium Maius, Fredry 10, 61-701 Poznan, Poland.
Department of Biosystems Engineering, Poznan University of Life Sciences, Wojska Polskiego 50, 60-627 Poznan, Poland.
Int J Environ Res Public Health. 2022 Mar 3;19(5):2952. doi: 10.3390/ijerph19052952.
Determining the chronological age of children or adolescents is becoming an extremely necessary and important issue. Correct age-assessment methods are especially important in the process of international adoption and in the case of immigrants without valid documents confirming their identity. It is well known that traditional, analog methods widely used in clinical evaluation are burdened with a high error rate and are characterized by low accuracy. On the other hand, new digital approaches appear in medicine more and more often, which allow the increase of the accuracy of these estimates, and thus equip doctors with a tool for reliable estimation of the chronological age of children and adolescents. In this study, the work on a fast and effective metamodel is continued. Metamodels have one great advantage over all other analog and quasidigital methods-if they are well trained, a priori, on a representative set of samples, then in the age-assessment phase, results are obtained in a fraction of a second and with little error (reduced to ±7.5 months). In the here-proposed method, the standard deviation for each estimate is additionally obtained, which allows the assessment of the certainty of each result. In this study, 619 pantomographic photos of 619 patients (296 girls and 323 boys) of different ages were used. In the numerical procedure, on the other hand, a metamodel based on the Proper Orthogonal Decomposition (POD) and Gaussian processes (GP) were utilized. The accuracy of the trained model was up to 95%.
确定儿童或青少年的年龄变得极其必要和重要。在国际收养过程中以及在没有有效文件证明其身份的移民情况下，正确的年龄评估方法尤为重要。众所周知，传统的模拟方法在临床评估中被广泛使用，但存在很高的错误率，并且准确性低。另一方面，新的数字方法在医学中越来越多地出现，这使得这些估计的准确性得到提高，从而为医生提供了一种可靠估计儿童和青少年实际年龄的工具。在本研究中，继续研究快速有效的元模型。与所有其他模拟和准数字方法相比，元模型有一个巨大的优势——如果它们经过良好的训练，可以提前对一组有代表性的样本进行训练，那么在评估年龄阶段，结果可以在几分之一秒内获得，并且误差很小（减少到±7.5 个月）。在本研究中，还获得了每个估计值的标准偏差，这允许评估每个结果的确定性。在这项研究中，使用了 619 名不同年龄的患者（296 名女孩和 323 名男孩）的 619 张 X 光照片。在数值程序中，另一方面，使用了基于 Proper Orthogonal Decomposition（POD）和 Gaussian processes（GP）的元模型。训练后的模型的准确率高达 95%。
