ArticleScientific reports2024
Binary decisions of artificial intelligence to classify third molar development around the legal age thresholds of 14, 16 and 18 years.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Comparative Analysis of Third Molar Segmentation Performance Across Dental Developmental Stages and the 18-Year Age Threshold Using Deep Learning Models.Diagnostics (Basel, Switzerland) · 2026Article
- Does increased staging complexity influence expert agreement in dental age estimation?International journal of legal medicine · 2026Article
- Computed tomography as a tool in the analysis of dentomaxillofacial characteristics for human identification: A bibliometric analysis of the most cited publications.Forensic science, medicine, and pathology · 2026Article
- Forensic performance of dental age estimation methods at legal age thresholds in Latin America: a scoping review.Forensic science, medicine, and pathology · 2026Review
- Maxillary sinus classification for sex and age using 23 artificial intelligence architectures.Scientific reports · 2026Article
- Radiographic legal age estimation based on third molar development using Machine-learning algorithms.PloS one · 2026Article
- End-to-end vs. human-defined feature extraction: comparing deep learning approaches for age classification using mandibular third molars.The Journal of forensic odonto-stomatology · 2025Article
- YOLO11m-cls applied to sex and age classification based on the radiographic analysis of the nasal aperture.Scientific reports · 2025Article
- A Deep Learning-Based Approach to Detect Lamina Dura Loss on Periapical Radiographs.Journal of imaging informatics in medicine · 2025Article
- Insights into dental age estimation: introducing multiple regression data from a Black South African population on modified gustafson's criteria.International journal of legal medicine · 2025Article
- A probability model for estimating age in young individuals relative to key legal thresholds: 15, 18 or 21-year.International journal of legal medicine · 2025Article
- Reliability of artificial intelligence algorithms in automated age estimation using orthopantomograms: A scoping review.Digital healthReview
- Geometric morphometric analysis of mandibular morphology for age classification in Indonesian adolescents and adults.Journal of oral biology and craniofacial researchArticle
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Authors and funding
13 authors.
Funding
Abstract
Third molar development is used for dental age estimation when all the other teeth are fully mature. In most medicolegal facilities, dental age estimation is an operator-dependent procedure. During the examination of unaccompanied and undocumented minors, this procedure may lead to binary decisions around age thresholds of legal interest, namely the ages of 14, 16 and 18 years. This study aimed to test the performance of artificial intelligence to classify individuals below and above the legal age thresholds of 14, 16 and 18 years using third molar development. The sample consisted of 11,640 panoramic radiographs (9680 used for training and 1960 used for validation) of males (n = 5400) and females (n = 6240) between 6 and 22.9 years. Computer-based image annotation was performed with V7 software (V7labs, London, UK). The region of interest was the mandibular left third molar (T38) outlined with a semi-automated contour. DenseNet121 was the Convolutional Neural Network (CNN) of choice and was used with Transfer Learning. After Receiver-operating characteristic curves, the area under the curve (AUC) was 0.87 and 0.86 to classify males and females below and above the age of 14, respectively. For the age threshold of 16, the AUC values were 0.88 (males) and 0.83 (females), while for the age of 18, AUC were 0.94 (males) and 0.83 (females). Specificity rates were always between 0.80 and 0.92. Artificial intelligence was able to classify male and females below and above the legal age thresholds of 14, 16 and 18 years with high accuracy.
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