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Automated age‐at‐death estimation by cementochronology: Essential application or additional complication?

It has been repeatedly acknowledged that age‐at‐death estimation based on dental cementum represents a partial and time‐consuming method that hinders adoption of this histological approach. User‐friendly micrograph analysis represents a growing request of cementochronology. This article evaluates th...

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Detalles Bibliográficos
Autores principales: Bertrand, Benoit, Vercauteren, Martine, Cunha, Eugenia, Bécart, Anne, Gosset, Didier, Hédouin, Valery
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9804312/
https://www.ncbi.nlm.nih.gov/pubmed/36790742
http://dx.doi.org/10.1002/ajpa.24612
Descripción
Sumario:It has been repeatedly acknowledged that age‐at‐death estimation based on dental cementum represents a partial and time‐consuming method that hinders adoption of this histological approach. User‐friendly micrograph analysis represents a growing request of cementochronology. This article evaluates the feasibility of using a module to accurately quantify cementum deposits and compares the module's performance to that of a human expert. On a dental collection (n = 200) of known‐age individuals, precision and accuracy of estimates performed by a developed program (101 count/tooth; n = 20,200 counts) were compared to counts performed manually (5 counts/tooth; n = 975 counts). Reliability of the software and agreement between the two approaches were assessed by intraclass correlation coefficient and Bland Altman analysis. The automated module produced reliable and reproducible counts with a higher global precision than the human expert. Although the software is slightly more precise, it shows higher sensitivity to taphonomic damages and does not avoid the trajectory effect described for age‐at‐death estimation in adults. Likewise, for human counts, global accuracy is acceptable, but underestimations increase with age. The quantification of the agreement between the two approaches shows a minor bias, and 94% of individuals fall within the intervals of agreement. Automation gives an impression of objectivity even though the region of interest, profile position and parameters are defined manually. The automated system may represent a time‐saving module that can allow an increase in sample size, which is particularly stimulating for population‐based studies.