From tradition to technology: artificial intelligence advancements in dental age estimation

Authors

  • Arofi Kurniawan Department of Forensic Odontology Faculty of Dental Medicine, Universitas Airlangga
  • Samith Taqiasha Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Ivan Rachman Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Tiara Lathifah Riyadi Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Michelle Liong Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Widya Ayu Pratiwi Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Marvin Hidayat Undergraduate student Faculty of Dental Medicine Universitas Airlangga, Surabaya, Indonesia
  • Anand Marya Department Department of Orthodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh, Cambodia

Abstract

Forensic odontology often necessitates the utilization of either visual or clinical methods for identification. Forensic experts may sometimes use established techniques, such as employing dental age estimation through atlases. Nevertheless, when confronted with large-scale incidents, particularly in mass disasters, the conventional methods can prove to be intricate and time-consuming, making forensic identification more challenging. Consequently, this challenge has prompted many experts to explore the integration of automation into their current practices to enhance overall efficiency and accuracy. This literature review discusses the application of artificial intelligence (AI) as a supporting method in dental age estimation. Based on the studied literature, AI in dental age estimation has the advantage of determining the maturity score of a tooth with a variety of populations and characteristics.

 

Keywords: artificial intelligence, dental age estimation, forensic odontology, legal identity

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Published

2024-12-21

How to Cite

Kurniawan, A., Taqiasha, S., Rachman, I., Riyadi, T. L., Liong, M., Pratiwi, W. A., Hidayat, M., & Marya, A. (2024). From tradition to technology: artificial intelligence advancements in dental age estimation. Bulletin of the International Association for Paleodontology, 18(2). Retrieved from https://hrcak.srce.hr/ojs/index.php/paleodontology/article/view/28239

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