The Evolving Role of Artificial Intelligence in Forensic Medicine: A Systematic Review Perspective
Organized by: World Research Awards
Website: forensicscientist.org
18th Edition of Forensic Scientist Awards 26-27 January 2026 | Bangkok, Thailand
Artificial intelligence (AI) is rapidly transforming the landscape of forensic medicine, introducing new tools and methods that enhance accuracy, efficiency, and objectivity in medico-legal investigations. From crime scene analysis to courtroom evidence interpretation, AI is reshaping how forensic experts work and how justice is delivered.
AI in Modern Forensic Practice
In forensic pathology, AI-powered imaging and pattern-recognition systems are now being used to assist in injury interpretation, wound age estimation, and cause-of-death analysis. Deep learning algorithms can analyze post-mortem CT scans and histopathological images with remarkable precision, supporting forensic pathologists in complex or ambiguous cases.
Forensic toxicology has also benefited from AI through automated compound detection, spectral analysis, and predictive modeling of drug interactions. These tools improve the speed and reliability of toxicological screenings, which are often critical in suspicious deaths and poisoning cases.
Digital and Biometric Forensics
In digital forensics, machine learning algorithms help investigators process massive volumes of electronic data, detect cybercrime patterns, and identify manipulated images or videos. AI is also widely used in biometric identification, including facial recognition, fingerprint matching, and voice analysis, improving identification accuracy while reducing human error.
Forensic anthropology and odontology are adopting AI for skeletal age estimation, sex determination, and dental identification. These applications are especially valuable in mass disaster victim identification and missing-person investigations.
Ethical and Legal Challenges
Despite its promise, the integration of AI into forensic medicine raises important ethical and legal concerns. Issues such as algorithmic bias, lack of transparency (“black-box” models), data privacy, and admissibility of AI-generated evidence in court must be carefully addressed. Ensuring that AI systems are validated, explainable, and legally defensible is essential to maintaining trust in forensic conclusions.
Future Directions
The future of forensic medicine lies in a collaborative model where AI supports—not replaces—human expertise. Continued research, standardized validation protocols, and interdisciplinary training will be key to maximizing AI’s benefits while minimizing risks. Policymakers, forensic professionals, and technologists must work together to create ethical frameworks and legal guidelines for responsible AI use.
Conclusion
Artificial intelligence is no longer a futuristic concept in forensic medicine—it is an emerging reality. This systematic review perspective highlights how AI is revolutionizing forensic pathology, toxicology, anthropology, odontology, and digital forensics. While challenges remain, the thoughtful and ethical adoption of AI has the potential to significantly strengthen medico-legal investigations and the pursuit of justice.
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