Machine learning analysis evaluates dental development for predicting chronological age in adolescents, highlighting forensic utility for personal identification.
Age estimation plays a critical role in personal identification, especially when determining compliance with the age of consent for adolescents. The age of consent refers to the minimum age at which an individual is legally considered capable of providing informed consent for sexual activities. The purpose of this study is to determine whether adolescents meet the age of 14 or 18 by using dental development combined with machine learning.
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Shen et al. (2024) studied this question.
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