APPLICATION OF ARTIFICIAL INTELLIGENCE TOOLS IN SOLVING APPLIED PROBLEMS IN FORENSIC MEDICINE

Abstract

One of the most actively and rapidly developing contemporary analytical research methods in recent years is undoubtedly artificial intelligence. In a relatively short period, it has progressively permeated all spheres of human life. Forensic medicine is no exception, as its progressive medical component dynamically evolves over time alongside scientific and technological progress. The aim of the study. To analyze recent scientific works and global literature on the implementation of artificial intelligence tools for solving various applied problems in forensic medicine. Materials and methods. The authors analyzed all accessible sources from global scientific literature in databases such as PubMed, Scopus, and Web of Science, selected based on keywords. The most relevant among them were subjected to detailed comparative analysis to assess their effectiveness in solving key applied tasks of forensic medicine. Scientific research. This study constitutes a fragment of a comprehensive research work conducted by the Department of Forensic Medicine and Medical Law of the Bukovinian State Medical University, titled "Utilization of modern morphological and physical methods for diagnosing the time and cause of death, the occurrence of bodily injuries, and the development of their remote and immediate consequences, aimed at addressing urgent tasks of law enforcement agencies and current issues of forensic medical science and practice" (State registration number 0123U101978, implementation period: January 2023-December 2027). Bioethics. The research materials have been reviewed and approved by the Bioethics Commission of Bukovinian State Medical University (Protocol No. 2 dated October 16, 2025). Results. The conducted study revealed that the application of artificial intelligence tools is already widely reflected in solving applied problems within the main branches of forensic medicine. Most researchers emphasize the necessity of critical consideration, a balanced approach, and expert supervision when implementing elements of artificial intelligence (machine learning, deep learning) in the process of conducting forensic medical examinations. Conclusions. Most models employed by researchers in the field of forensic medicine for solving various expert tasks are at initial stages of implementation and training, requiring further verification and legal assessment. Promising areas for the further implementation of artificial intelligence tools encompass most branches (directions) of forensic medicine, including estimation of the time since death, determination of different types of death, differential diagnosis of various mechanisms of bodily injury, firearm and explosive trauma, personal identification, forensic toxicology, histology, and criminalistics

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