Modernizing Forensic Anthropology: A Data-driven Pipeline for Human Identification and Profiling

Forensic odontology has traditionally relied on dental morphology and odontometric measurements for identification and profiling purposes. Innovations in imaging technologies (high-resolution two-dimensional [2D] radiography, cone-beam computed tomography [CBCT], and intraoral three-dimensional [3D] scanning), geometric morphometrics analysis (GMA), and artificial intelligence (AI) have revolutionized the collection, analysis, and interpretation of dental data. Relevant literature was identified through searches in PubMed, Scopus, and Web of Science using the keywords forensic odontology, CBCT, GMA, AI segmentation, and human identification, focusing on English-language studies published between 2010 and 2025. This narrative review consolidates the existing evidence regarding (1) the enhancement of data acquisition and comparability through 2D and 3D imaging; (2) the quantification of dental sexual dimorphism by GMA and its application in machine learning (ML) classifiers; (3) recent advancements in sex-prediction models derived from tooth metrics and 3D shape data; and (4) the facilitation of dental model creation and identification workflows through AI-driven segmentation. The discussion encompasses practical benefits, existing limitations, validation requirements, and prospective directions for the adoption of this technique in forensic applications.

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Publication Details

Journal
European Journal of Dentistry
Published
2026-02-25
DOI
https://doi.org/10.1055/s-0046-1816537
Primary Topic
Forensic Anthropology and Bioarchaeology Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Modernizing Forensic Anthropology: A Data-driven Pipeline for Human Identification and Profiling

Sadia Syed, Saira Atif, Sanjida Haque, Samiya Riaz et al.
European Journal of Dentistry
Forensic Anthropology and Bioarchaeology Studies
article

Modernizing Forensic Anthropology: A Data-driven Pipeline for Human Identification and Profiling

Sadia Syed, Saira Atif, Sanjida Haque, Samiya Riaz, Muhammad Sohail Zafar, Kawthar M. A. Bukhari
article en

Abstract

Forensic odontology has traditionally relied on dental morphology and odontometric measurements for identification and profiling purposes. Innovations in imaging technologies (high-resolution two-dimensional [2D] radiography, cone-beam computed tomography [CBCT], and intraoral three-dimensional [3D] scanning), geometric morphometrics analysis (GMA), and artificial intelligence (AI) have revolutionized the collection, analysis, and interpretation of dental data. Relevant literature was identified through searches in PubMed, Scopus, and Web of Science using the keywords forensic odontology, CBCT, GMA, AI segmentation, and human identification, focusing on English-language studies published between 2010 and 2025. This narrative review consolidates the existing evidence regarding (1) the enhancement of data acquisition and comparability through 2D and 3D imaging; (2) the quantification of dental sexual dimorphism by GMA and its application in machine learning (ML) classifiers; (3) recent advancements in sex-prediction models derived from tooth metrics and 3D shape data; and (4) the facilitation of dental model creation and identification workflows through AI-driven segmentation. The discussion encompasses practical benefits, existing limitations, validation requirements, and prospective directions for the adoption of this technique in forensic applications.

European Journal of Dentistry
University of Jordan (JO), Prince Sultan University (SA), Ajman University (AE), Taibah University (SA), CMH Lahore Medical College and Institute of Dentistry (PK), International Islamic University Malaysia (MY), Shifa International Hospital (PK)
International Islamic University Malaysia, Prince Sultan University
Gender equality
Openalex Percentile: Top 44%
Forensic Anthropology and Bioarchaeology Studies
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