Advancing estimation of chronological age by utilizing available evidence based on two radiographical methods

Abstract

This paper describes a strategy for estimating chronological age of individuals based on age indicators of X-ray of the hand and the third molar tooth. The great majority of studies in the field provide group-wise data of different formats, which makes them difficult to compare and utilize in a model. In this paper, we have provided a framework to utilize different types of data formats to build a common model for estimating chronological age. We used transition analysis to describe the relationship between the age indicators and chronological age. Further, likelihood ratio weight of evidence and posterior distribution of chronological age were used to model the distribution of chronological age given the observed age indicators. Being able to utilize such a large amount of data, with different data formats, from different studies, as presented in this paper improves previous age estimation methods.

Multi-factorial age estimation: A Bayesian approach combining dental and skeletal magnetic resonance imaging

“…Correspondingly, several authors rejected the conditional independence assumption, and stated that conditional dependence should be accounted for [9,39,43], which is supported by the current findings. Nevertheless, some authors did assume conditional independence between the different anatomical sites [8,10,44]. For instance, Bleka et al…”

“…Numerous studies on single anatomical sites are available (single site age estimation = SSA), with large reference studies mostly based on retrospective data [4][5][6][7]. Attempts to combine the information from single site studies have been made [8], but controversies about the appropriate statistical approach are remaining [9,10]. By contrast, studying multiple anatomical sites in the same reference population (multi-factorial age estimation = MFA) allows for more relevant conclusions about combined age estimation and the relative contribution of each site.…”

Age estimation of living persons: A coherent approach to inference and decision

“…In the framework suggested by the AGFAD, the prior probability distribution could be assigned by the expert based on information collected during an interview or the physical examination of the person under investigation, since it is generally acknowledged that data gathered in this initial step of the examination sequence should not be used for the effective age estimation (Schmeling et al, 2006a, Schmeling et al, 2011. Due to the lack of available information, many authors have proposed adopting so-called non-informative or vague prior probability distributions, such as a uniform distribution over a given age range, according to which all possible age values are considered, a priori, equally likely (Braga et al, 2005, Thevissen et al, 2010, Cameriere et al, 2016, Bleka et al, 2018. This way of thinking should result in posterior conclusions that will be minimally dependent on prior distribution.…”

Técnicas de identificação humana em Odontologia Legal

“…Diferentes métodos para a identificação humana são utilizados pelos odontolegistas, sendo alguns deles: exame de registros odontológicos, que confronta a documentação odontológica prévia de um suspeito com o indivíduo a ser identificado, por comparação de exames radiológicos (Page et al, 2018), tomográficos e clínicos, análise de modelos de gesso, dos dados dos tratamentos realizados com aspectos da cavidade bucal da vítima (Afify et al, 2014); marcas de mordida (Freeman, Senn & Arendt, 2005); análise dos seios da face (Bangi et al, 2017) ; análise de saliva (Tsai et al, 2018); análise de rugas palatinas (Santos, Fernandes & Serra, 2011;Poojya et al, 2015); estimativa de idade por estágios de mineralização dentária (Bleka et al, 2019),impressões labiais (Sharma, Saxena & Rathod, 2009;Herrera, Fernandes & Serra, 2013;Herrera, Fernandes & Serra, 2018) e marcas de orelha (Silva, Fernandes & Serra, 2012).…”