ArticleScientific reports2023
Validation of data mining models by comparing with conventional methods for dental age estimation in Korean juveniles and young adults.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy of the methods of age determination using artificial intelligence in panoramic radiographs - a systematic review.International journal of legal medicine · 2024Pooled it
- Dental age estimation: a scoping review comparing the manual application of the Demirjian method and artificial intelligence modalities.International journal of legal medicine · 2026Article
- Forensic age estimation and legal age thresholds classification based on the elbow MRI and data mining in a Chinese population.International journal of legal medicine · 2026Article
- Machine learning approach for adult age estimation using dental characteristics on panoramic radiographs.Scientific reports · 2026Article
- Demirjian's and Cameriere's methods for estimating the 18-year legal age threshold using third molar maturity in a Northern Thai population.Scientific reports · 2026Article
- Review
- Dental Versus Skeletal Methods for Age Estimation in Growing Individuals: A Systematic Review.Cureus · 2025Review
- Development and validation of an age estimation model based on dental characteristics using panoramic radiographs.Scientific reports · 2025Article
- Comparison of different dental age estimation methods with deep learning: Willems, Cameriere-European, London Atlas.International journal of legal medicine · 2025Article
- Performance of Artificial Intelligence Models Designed for Automated Estimation of Age Using Dento-Maxillofacial Radiographs-A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Adult age estimation from the sternum using maximum intensity projection images of CT and data mining in a Chinese population.International journal of legal medicine · 2024Article
- Dental characteristics on panoramic radiographs as parameters for non-invasive age estimation: a pilot study.Anatomy & cell biology · 2023Article
- Validation of London Atlas for forensic age estimation in Koreans by comparing with Lee's and Willems' methods.Heliyon · 2023Article
- Contemporary Role and Applications of Artificial Intelligence in Dentistry.F1000Research · 2023Review
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6 authors.
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Abstract
Teeth are known to be the most accurate age indicators of human body and are frequently applied in forensic age estimation. We aimed to validate data mining-based dental age estimation, by comparing the accuracy of the estimation and classification performance of 18-year thresholds with conventional methods and with data mining-based age estimation. A total of 2657 panoramic radiographs were collected from Koreans and Japanese populations aged 15 to 23 years. They were subdivided into a training and internal test set of 900 radiographs each from Koreans, and an external test set of 857 radiographs from Japanese. We compared the accuracy and classification performance of the test sets from conventional methods with those from the data mining models. The accuracy of the conventional method with the internal test set was slightly higher than that of the data mining models, with a slight difference (mean absolute error < 0.21 years, root mean square error < 0.24 years). The classification performance of the 18-year threshold was also similar between the conventional method and the data mining models. Thus, conventional methods can be replaced by data mining models in forensic age estimation using second and third molar maturity of Korean juveniles and young adults.
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