A DIGITAL TRANSFORMATION OF FORENSIC IDENTIFICATION USING INTRAORAL SCANNERS, CAD/CAM, AND AI

Abstract

Introduction: Digital dental technologies have been proposed as alternatives to conventional casts for the creation of ante-mortem (AM) records in forensic identification. However, their accuracy and forensic applicability require systematic evaluation. Aim: This systematic review evaluated original research on intraoral scanners, CAD/CAM systems, and AI-assisted technologies for generating ante-mortem (AM) dental records and their potential forensic applicability, with emphasis on dimensional accuracy, reproducibility, advantages, and limitations. Review: The literature search was conducted through two major scientific databases, namely Google Scholar and PubMed, to identify relevant studies on digital dental records in forensic contexts. The search strategy was developed using structured keyword combinations related to forensic dentistry, digital dental records, intraoral scanners, CAD/CAM systems, and artificial intelligence. The inclusion and exclusion criteria were determined using the SPIDER framework, which consists of Sample (S), Phenomenon of Interest (PI), Design (D), Evaluation (E), and Research Type (R), to ensure that the selected studies were relevant to the objectives of this review and aligned with the research questions. Conclusion: Existing studies demonstrate that digital dental technologies provide high morphometric accuracy, with three-dimensional deviations remaining within clinically acceptable ranges. STL-based comparisons, surface deviation mapping, and three-dimensional superimposition offer objective analytical approaches that show strong potential for forensic application. However, direct validation under simulated forensic conditions remains limited, and further research is required before full implementation in forensic practice.