Abstract
Human identification is the core component of Forensic Odontology. The process of identification of unknown remains generally starts with the reconstruction of the skeletal biological profile, which provides a general description of the individual that is used to narrow down the candidates for the identity. Once one or more candidates are given for the identity, forensic odontologists conduct the comparison between the antemortem and postmortem records. The postmortem vs. the antemortem data comparison implies the evaluation of the consistencies and inconsistencies found in the data sets. This comparison is highly affected by the quality and completeness of the antemortem records, as well as the condition of the remains. The principles of the odontological comparison are based on the differences in the dental and maxillofacial structures due to human variation, development and pathology, and the alteration caused by dental treatment, which can be visually and radiographically observed. Restorative treatment, osseointegrated dental implants, fixed orthodontic and prosthetic appliances, along with dental and maxillofacial anatomy are the most informative features for the postmortem vs. antemortem comparison. The process of comparison consists of an objective identification of the consistencies and discrepancies. However, their interpretation and the final conclusion relies on the forensic odontologist knowledge and proficiency. Computer software packages such as WinID, DVI System International and UVIS can assist in the comparisons, connecting the postmortem and antemortem information and creating a ranking of possible matches. Moreover, deep machine learning models are being explored automate the comparison process. However, all comparison procedures still require the expert’s final assessment.
Cite
CITATION STYLE
Adserias-Garriga, J., Rettger, J., & D. Hostetler, S. (2024). Principles in Identification of Human Remains through Forensic Odontology. Perspectives in Legal and Forensic Sciences, 1(1), 10006–10006. https://doi.org/10.70322/plfs.2024.10006
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