Artificial intelligence in forensic medicine and forensic nursing: A systematic review of clinical applications,...

Artificial intelligence (AI) is reshaping healthcare, and forensic medicine and nursing are no exception. From automated wound pattern analysis to natural language processing (NLP) in medicolegal documentation, AI tools are entering a field situated at the intersection of clinical care, legal accountability, and human rights. This systematic review with narrative synthesizes contemporary clinical, forensic, and AI ethics literature to examine current and emerging applications of AI in forensic practice, with particular attention to injury interpretation, postmortem interval estimation, forensic imaging, survivor documentation, and medicolegal reporting. Forensic nursing practice, including sexual assault nurse examiner (SANE) programs, domestic violence assessment, and paediatric abuse evaluation, is a central focus. The review critically evaluates ethical risks associated with deploying algorithmic decision-making in high-stakes forensic contexts where outputs may influence criminal outcomes and judicial proceedings. Issues of algorithmic bias, chain-of-custody integrity, explainability, and the potential displacement of clinical judgment are examined alongside practical considerations for implementation. Given the still-emerging forensic-specific evidence base, this review draws selectively on adjacent clinical disciplines while emphasizing the distinct medicolegal demands of forensic practice. Responsible integration of AI, the review concludes, requires interdisciplinary governance, equity-stratified validation, and preservation of the clinician-examiner's primary interpretive authority.