The Evolving Role of Artificial Intelligence in Forensic Medicine: A Systematic Review
Organized by: International Forensic Scientist Awards
Website: forensicscientist.org
17th Edition of Forensic Scientist Awards 29-30 December 2025 | Dubai, United Arab Emirates
Artificial Intelligence (AI) has emerged as one of the most transformative technologies in modern forensic medicine. Its rapid advancements are redefining how forensic experts analyze evidence, interpret findings, and deliver objective medico-legal conclusions. This systematic review examines the current landscape of AI applications across multiple branches of forensic science, highlighting key innovations, benefits, challenges, and future opportunities.
AI in Forensic Pathology
AI-assisted tools are revolutionizing forensic autopsy procedures. Deep-learning models now support injury detection, wound classification, time-since-death estimation, and automated pattern recognition from postmortem imaging. Virtual autopsy techniques, including postmortem CT and MRI, combined with AI algorithms, enhance diagnostic accuracy and provide non-invasive alternatives to traditional autopsies.
AI in Forensic Radiology
Postmortem radiology has seen remarkable progress with machine-learning systems capable of identifying fractures, internal injuries, gas distribution, and forensic markers that help in reconstructing events leading to death. AI improves the efficiency and objectivity of radiological interpretation while reducing human error.
AI in Forensic Toxicology
AI-based predictive models assist in detecting toxic substances, interpreting drug metabolism patterns, and forecasting toxicological outcomes. Machine learning simplifies the analysis of complex biochemical data, streamlining forensic toxicology workflows and improving case accuracy.
AI in Forensic Anthropology
From skeletal age estimation to facial reconstruction, AI enhances the precision of anthropological evaluations. Algorithms can quickly analyze bone morphology, predict biological profiles, and assist in identifying unknown remains with higher reliability.
AI in Forensic Genetics
Genomic technologies powered by AI have redefined forensic DNA analysis. New models enable phenotype prediction, ancestry estimation, and rapid genotype profiling. AI tools are increasingly used to interpret complex DNA mixtures, offering greater clarity in criminal investigations.
AI in Digital and Cyber Forensics
In the age of digital crime, AI has become essential for analyzing large volumes of electronic data. It supports malware detection, anomaly tracking, image and voice recognition, and automated evidence extraction. AI-driven tools accelerate digital investigations and enhance threat detection capabilities.
AI in Crime Scene Investigation
AI supports 3D reconstruction of crime scenes, pattern mapping, trajectory analysis, and automated evidence detection. These technologies enable investigators to visualize crime scenes accurately, preserving details that may be overlooked during manual inspection.
Ethical, Legal, and Practical Challenges
While AI offers significant benefits, several challenges persist. These include data privacy concerns, model bias, lack of standardized datasets, validation issues, and ethical considerations surrounding medico-legal decision-making. Establishing guidelines for AI integration and ensuring transparency in algorithmic processes are crucial for future adoption.
Future Directions
AI is expected to become an integral part of forensic workflows worldwide. Advancements in multimodal AI models, explainable artificial intelligence (XAI), automated decision support systems, and integration with digital health records will greatly enhance forensic accuracy and efficiency. Continued research, technological development, and interdisciplinary collaboration will shape the future of forensic medicine.
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