Artificial intelligence fosters forensic odontology-a narrative review

This review aims to evaluate the advancements in Forensic Odontology (FO), focusing on the integration of digital technologies and artificial intelligence (AI) to improve human identification through dental characteristics, particularly in the context of forensic investigations and mass disaster scenarios. The review draws on published literature, scientific reports, and case studies that document the evolution of FO. Studies were selected based on their focus on innovations in dental materials, laboratory techniques, and AI applications. Special emphasis was placed on research demonstrating practical applications of these technologies in forensic investigations, with measurable improvements in accuracy, efficiency, and reliability. Recent advancements in digital imaging, database management, and AI have significantly enhanced FO. AI techniques, including deep neural networks and Machine Learning (ML), have improved the analysis of dental records, bite marks, age and sex estimation, and facial reconstruction. Automated image analysis has also increased the speed and precision of forensic identifications, making the process more efficient and reliable. In conclusion, the integration of AI into FO has significantly advanced the field by enhancing analytical precision, accelerating data processing, and improving reliability in human identification. These technological advancements are setting new standards in forensic practice, with the potential to significantly impact legal investigations and human identification processes in both routine cases and mass disaster events.

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Publication Details

Journal
Egyptian Journal of Forensic Sciences
Published
2026-03-28
DOI
https://doi.org/10.1186/s41935-026-00536-7
Primary Topic
Forensic Anthropology and Bioarchaeology Studies
Type
article
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article

Artificial intelligence fosters forensic odontology-a narrative review

Samah Mehanny, Varun Surya, Nour Ammar, Mostafa Abuelhamed et al.
Egyptian Journal of Forensic Sciences
Forensic Anthropology and Bioarchaeology Studies
article

Artificial intelligence fosters forensic odontology-a narrative review

Samah Mehanny, Varun Surya, Nour Ammar, Mostafa Abuelhamed, aya mohammed gaber, Akhilanand Chaurasia, Al-Hassan Soliman Wadan
article en

Abstract

This review aims to evaluate the advancements in Forensic Odontology (FO), focusing on the integration of digital technologies and artificial intelligence (AI) to improve human identification through dental characteristics, particularly in the context of forensic investigations and mass disaster scenarios. The review draws on published literature, scientific reports, and case studies that document the evolution of FO. Studies were selected based on their focus on innovations in dental materials, laboratory techniques, and AI applications. Special emphasis was placed on research demonstrating practical applications of these technologies in forensic investigations, with measurable improvements in accuracy, efficiency, and reliability. Recent advancements in digital imaging, database management, and AI have significantly enhanced FO. AI techniques, including deep neural networks and Machine Learning (ML), have improved the analysis of dental records, bite marks, age and sex estimation, and facial reconstruction. Automated image analysis has also increased the speed and precision of forensic identifications, making the process more efficient and reliable. In conclusion, the integration of AI into FO has significantly advanced the field by enhancing analytical precision, accelerating data processing, and improving reliability in human identification. These technological advancements are setting new standards in forensic practice, with the potential to significantly impact legal investigations and human identification processes in both routine cases and mass disaster events.

Egyptian Journal of Forensic SciencesVol. 16(1)
Suez University (EG), Cairo University (EG), King George's Medical University (IN), Galala University, All India Institute of Medical Sciences (IN), Ludwig-Maximilians-Universität München (DE), Alexandria University (EG), Minia University (EG)
Climate action
Openalex Percentile: Top 3%
Forensic Anthropology and Bioarchaeology Studies
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