Forensic Science in the Asia-Pacific: Artificial Intelligence trends and clinical applications

Abstract

The Asian Forensic Sciences Network (AFSN) and the Asia Pacific Medico-Legal Agencies (APMLA) Annual Meeting 2025 took place in the Republic of Korea (September 15–19, 2025), celebrating the 70th anniversary of Korea’s National Forensic Service (NFS). This report summarizes the key scientific and technological trends presented, alongside a personal reflection on the hospital's research contribution. Materials and Methods: This special article reviewed and analyzed data from a total of 332 technical abstracts (160 oral and 172 e-poster presentations) delivered across various Working Groups.
A quantitative assessment of the application of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) technologies was performed. Results: A total of 39 presentations were identified as related to AI/ML/DL, predominantly focusing on Digital Forensics and Forensic Medicine. The author's research, “Using Machine Learning Models to Identify Key Clinical Clues in Forensic Detection of Nasal Bone Fractures” (FMWG-PP-15), was the sole abstract from the Ministry of Public Health (MOPH)  and the only e-poster applying ML to clinical forensic diagnosis. The Random Forest model achieved high predictive ability (AUC 0.95) by identifying nasal ridge crepitation/stepping as the key clinical predictor. Conclusion: A prevailing trend in the Asia-Pacific region is the significant transition toward AI-driven forensics, presenting a crucial opportunity to incorporate machine learning technologies into hospital-based clinical forensic diagnostics. This integration aims to improve the accuracy and standardization of injury assessments and advance the development of forensic sciences.