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<p>Innovation is a central driver of progress in forensic medicine, enabling the development of new methodologies for the analysis and interpretation of forensic findings. Artificial intelligence (AI)-based injury detection and three-dimensional (3D) forensic documentation represent emerging approaches with the potential to enhance injury analysis, visualization, and workflow integration. Such developments should be understood within a broader translational framework, in which innovation initiates technological advancement and subsequent validation ensures their reliable application in medico-legal contexts. The integration of AI-driven methodologies into forensic workflows follows an established pattern observed across forensic science, where innovations originating from adjacent disciplines are progressively adapted and incorporated into practice. Comparable trajectories have been demonstrated in the adoption of DNA profiling and postmortem imaging, both of which evolved from experimental concepts to essential forensic tools. AI-assisted 3D documentation may further support triage-oriented workflows and contribute to multimodal forensic systems. Advancing forensic medicine toward courtroom-grade digital twins therefore depends on the continuous interplay between innovation and validation, with innovation providing the foundation for future developments. These approaches represent essential steps toward the responsible integration of AI-based technologies into forensic practice.</p>

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Advancing forensic medicine through AI-based injury detection: innovation as the catalyst for forensic 3D avatars and translation as the pathway toward courtroom-grade digital twins

  • 期刊论文

  • 发表日期：

    2026年4月14日

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  • Michael Thali,
  • Dominic Gascho

摘要

Innovation is a central driver of progress in forensic medicine, enabling the development of new methodologies for the analysis and interpretation of forensic findings. Artificial intelligence (AI)-based injury detection and three-dimensional (3D) forensic documentation represent emerging approaches with the potential to enhance injury analysis, visualization, and workflow integration. Such developments should be understood within a broader translational framework, in which innovation initiates technological advancement and subsequent validation ensures their reliable application in medico-legal contexts. The integration of AI-driven methodologies into forensic workflows follows an established pattern observed across forensic science, where innovations originating from adjacent disciplines are progressively adapted and incorporated into practice. Comparable trajectories have been demonstrated in the adoption of DNA profiling and postmortem imaging, both of which evolved from experimental concepts to essential forensic tools. AI-assisted 3D documentation may further support triage-oriented workflows and contribute to multimodal forensic systems. Advancing forensic medicine toward courtroom-grade digital twins therefore depends on the continuous interplay between innovation and validation, with innovation providing the foundation for future developments. These approaches represent essential steps toward the responsible integration of AI-based technologies into forensic practice.