Dental Age Estimation: A Machine Learning Perspective

2019 ◽  
pp. 722-733 ◽  
Author(s):  
Jiang Tao ◽  
Jian Wang ◽  
Andrew Wang ◽  
Zhangqian Xie ◽  
Ziheng Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Age Estimation ◽  
Dental Age ◽  
Dental Age Estimation

scholarly journals Machine learning assisted Cameriere method for dental age estimation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shihui Shen ◽  
Zihao Liu ◽  
Jian Wang ◽  
Linfeng Fan ◽  
Fang Ji ◽  
...  
Keyword(s):  
Machine Learning ◽  
Mean Square Error ◽  
Age Estimation ◽  
Estimation Method ◽  
Permanent Teeth ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
Mean Square ◽  
Dental Age ◽  
Dental Age Estimation

Abstract Background Recently, the dental age estimation method developed by Cameriere has been widely recognized and accepted. Although machine learning (ML) methods can improve the accuracy of dental age estimation, no machine learning research exists on the use of the Cameriere dental age estimation method, making this research innovative and meaningful. Aim The purpose of this research is to use 7 lower left permanent teeth and three models [random forest (RF), support vector machine (SVM), and linear regression (LR)] based on the Cameriere method to predict children's dental age, and compare with the Cameriere age estimation. Subjects and methods This was a retrospective study that collected and analyzed orthopantomograms of 748 children (356 females and 392 males) aged 5–13 years. Data were randomly divided into training and test datasets in an 80–20% proportion for the ML algorithms. The procedure, starting with randomly creating new training and test datasets, was repeated 20 times. 7 permanent developing teeth on the left mandible (except wisdom teeth) were recorded using the Cameriere method. Then, the traditional Cameriere formula and three models (RF, SVM, and LR) were used to estimate the dental age. The age prediction accuracy was measured by five indicators: the coefficient of determination (R2), mean error (ME), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). Results The research showed that the ML models have better accuracy than the traditional Cameriere formula. The ME, MAE, MSE, and RMSE values of the SVM model (0.004, 0.489, 0.392, and 0.625, respectively) and the RF model (− 0.004, 0.495, 0.389, and 0.623, respectively) were lower with the highest accuracy. In contrast, the ME, MAE, MSE and RMSE of the European Cameriere formula were 0.592, 0.846, 0.755, and 0.869, respectively, and those of the Chinese Cameriere formula were 0.748, 0.812, 0.890 and 0.943, respectively. Conclusions Compared to the Cameriere formula, ML methods based on the Cameriere’s maturation stages were more accurate in estimating dental age. These results support the use of ML algorithms instead of the traditional Cameriere formula.

Accuracy of the Demirjian, Willems and Nolla methods for dental age estimation in a northern Chinese population

2020 ◽  
Vol 118 ◽  
pp. 104875
Author(s):  
Meng-qi Han ◽  
Si-xuan Jia ◽  
Chen-Xu Wang ◽  
Guang Chu ◽  
Teng Chen ◽  
...  
Keyword(s):  
Age Estimation ◽  
Chinese Population ◽  
Dental Age ◽  
Dental Age Estimation ◽  
Northern Chinese ◽  
Northern Chinese Population

scholarly journals Application of Cameriere’s method for dental age estimation in children in South China

2021 ◽  
pp. 1-9
Author(s):  
Zedeng Yang ◽  
Dan Wen ◽  
Jiao Xiao ◽  
Qianying Liu ◽  
Shule Sun ◽  
...  
Keyword(s):  
South China ◽  
Age Estimation ◽  
Dental Age ◽  
Dental Age Estimation

Validity and accuracy of three radiographic dental age estimation methods in Brazilians

2018 ◽  
Vol 283 ◽  
pp. 128-135 ◽  
Author(s):  
Eduardo Novaes Benedicto ◽  
Alana Cássia Silva Azevedo ◽  
Edgard Michel-Crosato ◽  
Maria Gabriela Haye Biazevic
Keyword(s):  
Age Estimation ◽  
Estimation Methods ◽  
Dental Age ◽  
Dental Age Estimation

Dental age estimation from the developmental stage of the third molars in western Chinese population

2012 ◽  
Vol 219 (1-3) ◽  
pp. 158-164 ◽  
Author(s):  
Guo Li ◽  
Jiayin Ren ◽  
Shuping Zhao ◽  
Yuanyuan Liu ◽  
Na Li ◽  
...  
Keyword(s):  
Developmental Stage ◽  
Age Estimation ◽  
Chinese Population ◽  
Dental Age ◽  
Third Molars ◽  
Dental Age Estimation ◽  
The Third

scholarly journals A Comparative Evaluation of Three Different Dental Age Estimation Methods in India: A Test of Ethnic Variability

2020 ◽  
Vol 13 (1) ◽  
pp. 16-20
Author(s):  
Manjit Talwar ◽  
Kirti Chaudhry ◽  
Ashish Choudhary ◽  
Arun K Patnana ◽  
Narasimha RV Vanga ◽  
...  
Keyword(s):  
Age Estimation ◽  
Comparative Evaluation ◽  
Estimation Methods ◽  
Dental Age ◽  
Dental Age Estimation ◽  
Ethnic Variability
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