Forensic odontology publications: insights into research trajectories and emerging trends through bibliometric study
Introduction: Forensic odontology (FO), an interdisciplinary field at the intersection of dentistry and legal investigations, has witnessed significant growth and evolution in theory and methodology since its inception.Objectives: This study aimed to analyze this evolution through bibliometric analysis of FO publications, providing insights into research trajectories and highlighting emerging areas of interest.Material and methods: Sampling was conducted in the Scopus database on October 20 th , 2023.Data collection spanned from inception to the search date, encompassing solely research and review articles for inclusion in the study.All bibliometric analyses were conducted via RStudio.Results: The dataset comprised of 6,416 studies conducted between 1945 and 2023, demonstrating an annual growth rate of 7.17%.Over 13,646 unique authors contributed to FO studies, with 12.34% being international collaborations.Notably, there are 1,574 single-authored documents, with an average of 3.44 authors per document.Major sub-fields in FO studies include dental age estimation, dental human identification, and other areas, such as bite marks and cheiloscopy (lip prints).The latest trend in FO studies involves the utilization of cone beam computed tomography and machine learning.Conclusions: Our analysis indicates a consistent rise in research output and a growing emphasis on dental age estimation within FO.This study provides a comprehensive overview of current FO research, highlighting key themes and methodologies.By identifying trends and impactful contributions, it offers guidance for future research and identifies areas for further exploration in forensic odontology.
Authors
- Rizky Merdietio Boedi (ORCID: https://orcid.org/0000-0002-5045-6773)
- Nikolaos Angelakopoulos (ORCID: https://orcid.org/0000-0001-8511-4645)
Publication Details
- Journal
- Journal of Stomatology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.5114/jos.2025.148479
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31