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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/10372

Title: Human dental age estimation using third molar developmental stages: does a Bayesian approach outperform regression models to discriminate between juveniles and adults?
Authors: Thevissen, P. W.
FIEUWS, Steffen
Willems, G.
Issue Date: 2010
Publisher: SPRINGER
Abstract: Dental age estimation methods based on the radiologically detected third molar developmental stages are implemented in forensic age assessments to discriminate between juveniles and adults considering the judgment of young unaccompanied asylum seekers. Accurate and unbiased age estimates combined with appropriate quantified uncertainties are the required properties for accurate forensic reporting. In this study, a subset of 910 individuals uniformly distributed in age between 16 and 22 years was selected from an existing dataset collected by Gunst et al. containing 2,513 panoramic radiographs with known third molar developmental stages of Belgian Caucasian men and women. This subset was randomly split in a training set to develop a classical regression analysis and a Bayesian model for the multivariate distribution of the third molar developmental stages conditional on age and in a test set to assess the performance of both models. The aim of this study was to verify if the Bayesian approach differentiates the age of maturity more precisely and removes the bias, which disadvantages the systematically overestimated young individuals. The Bayesian model offers the discrimination of subjects being older than 18 years more appropriate and produces more meaningful prediction intervals but does not strongly outperform the classical approaches.
Notes: [Thevissen, P. W.; Willems, G.] Katholieke Univ Leuven, Sect Forens Odontol, Dept Dent Oral Pathol & Maxillofacial Surg, B-3000 Louvain, Belgium. [Fieuws, S.] Katholieke Univ Leuven, I BioStat, B-3000 Louvain, Belgium. [Fieuws, S.] Univ Hasselt, B-3000 Louvain, Belgium. guy.willems@med.kuleuven.be
URI: http://hdl.handle.net/1942/10372
DOI: 10.1007/s00414-009-0329-8
ISI #: 000272903800006
ISSN: 0937-9827
Category: A1
Type: Journal Contribution
Validation: ecoom, 2011
Appears in Collections: Research publications

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