Applicability of Willems method for age estimation in Brazilian children: performance of multiple linear regression and artificial neural network
Background Dental age estimation of children may be necessary in the clinical and forensic fields. In the former, it may contribute to the investigation of dental development and biological maturation. In the latter, dental age estimation may support the Court in several circumstances, such as adopt...
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| Published in: | Egyptian journal of forensic sciences Vol. 12; no. 1; pp. 1 - 9 |
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| Main Authors: | , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01-02-2022
Springer Nature B.V SpringerOpen |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Background
Dental age estimation of children may be necessary in the clinical and forensic fields. In the former, it may contribute to the investigation of dental development and biological maturation. In the latter, dental age estimation may support the Court in several circumstances, such as adoption and unidentified bodies of deceased children. This study aimed to apply Willems method for dental age estimation of children from Southeastern Brazil. The second aim of the study was to test the performance of the method modeled with multiple linear regression (MLR) and artificial neural network (ANN). The sample consisted of 1000 panoramic radiographs of female (
n
= 500) and male (n = 500) Brazilian children. The individuals were evenly distributed through ten age intervals of 1 year from 6 to 15.99 years. Dental development was classified with the 7-teeth technique of Demirjian et al. (
1973
), followed by age calculation with Willems method (2001). The difference between chronological and estimated ages was quantified for the original Willems model and for the MLR and ANN models.
Results
For females and males, the overall difference found with Willems original model was 0.27 and 0.28, respectively. With MLR and ANN, the overall differences were 0.54 and 0.35, and 0.26 and 0.24, respectively. The ANN was able to reduce half of the mean error of female age predictions up to 100%. The same phenomenon occurred in 1/3 of the males. Despite the improvements of the ANN model to specific age groups, the original Willems model performed similar or better in 40% of the studied age intervals. All the models showed the worse age predictions in the interval between 15 and 15.99 years (
p
< 0.001).
Conclusions
Willems method remains optimal and applicable after 20 years since original development. The ANN model might be an option for future improvements (depending on sex and age interval). |
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| ISSN: | 2090-5939 2090-536X 2090-5939 |
| DOI: | 10.1186/s41935-022-00271-9 |