AI-driven transformation in forensic medicine education: applications, pedagogical shifts, and future challenges
Year: 2026
Type: article
Abstract: Forensic medicine, as an interdisciplinary field featuring a high degree of practicality and technological integration, is currently faced with several challenges, including limited teaching resources, few practical training opportunities, and slow adoption of emerging technologies. With the rapid advancement of artificial intelligence (AI), its growing application in medical education has significantly transformed the landscape of traditional teaching approaches in forensic medicine, opening up new possibilities for innovations in pedagogical models. Against this backdrop, this study examines the potential of AI technology in forensic medicine from the perspectives of pedagogical model innovation, content delivery, and evaluation system reform, with specific emphasis on virtual simulation instruction, intelligent case analysis, and personalized learning pathways. Furthermore, it discusses existing ethical, technical, and resource-related limitations in current research. Based on this study, the paper proposes strategies and practical pathways to promote the application of AI in forensic medicine education, aiming to provide theoretical insights for cultivating high-quality forensic medicine professionals.
Source: Frontiers in Medicine
Authors: Yin-qi Wu, Yu Du
Institution: Criminal Investigation Police University of China
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7126097041