Artificial Intelligence in Forensic Odontology: Advancing Accuracy in Victim Identification and Crime Solving - Fauziah, Yessy Andriani; Narmada, Ida Bagus; Yudianto, Ahmad; Darmadi, Eveline Yulia (Journal of Syiah Kuala Dentistry Society, 2025)
Background: Forensic odontology plays a pivotal role in human identification, particularly in criminal investigations and mass disaster scenarios. Traditionally, this field has relied on manual techniques, which are often limited by human error, subjectivity, and time constraints. Recent advances in artificial intelligence (AI) offer new solutions to overcome these challenges. Objective: This review aims to explore and synthesize the current knowledge regarding the integration of AI in forensic odontology, focusing on its role in victim identification, bite mark analysis, and age and sex estimation. Method: A narrative literature review was conducted using electronic databases, including PubMed, Scopus, Web of Science, and Google Scholar. Articles published between 2015 and 2023 were retrieved using relevant keywords such as artificial intelligence, forensic odontology, victim identification, bite mark analysis, and age estimation. Inclusion criteria encompassed original research, systematic reviews, and high-quality narrative reviews in English discussing AI or machine learning applications in forensic dentistry. Exclusion criteria were non-English publications, unrelated studies, and papers lacking methodological clarity. Results: The integration of AI, particularly machine learning and neural networks, has significantly improved the accuracy and efficiency of forensic odontology procedures. AI systems demonstrate superior performance in dental image recognition, bite mark pattern analysis, and age/sex prediction compared to conventional methods. These tools facilitate rapid data processing and reduce examiner bias, making them especially valuable in time-sensitive situations like disaster victim identification. Furthermore, AI contributes to more reliable and consistent forensic evidence in legal settings. Conclusion: AI is revolutionizing forensic odontology by enhancing precision, objectivity, and speed in identification processes. Despite its advantages, ethical concerns regarding data privacy and the need for standardization remain critical. Continued interdisciplinary research and validation are essential to ensure the responsible and effective adoption of AI in forensic science.