In recent years, the rapid development of artificial intelligence (AI) has brought unprecedented opportunities and challenges to scientific and technological research in various fields. The cross-integration of forensic toxicology and AI has increasingly become a research hotspot of forensic science, providing new ideas and methods to solve the problems of traditional forensic toxicology. In this paper, relevant researches in recent years have been reviewed, focusing on the research progress of AI in toxicological research such as on-site investigation of poisoning, toxicant screening and qualitative and quantitative detection, toxicity prediction, toxicokinetics, toxicants interaction, as well as the identification and characterization of involved personnel in cases, and the challenges faced by AI technology in the field of forensic toxicology have also been analyzed, in order to provide reference for AI technology to better serve the research and application of forensic toxicology.
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Open Access
Review
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Open Access
Review
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Human body odor arises from the secretion of various glands on the skin’s surface, which, when acted upon by microorganisms, evaporate to produce a distinct scent. This odor contains valuable biological information, with certain compounds exhibiting strong stability and individual specificity, serving as “odor fingerprinting” that can distinguish between different populations. Machine learning is an important method for human odor research, which can not only explore the characteristic components of odor in different populations, but also investigate the differences between different individuals. This paper discusses the application of “odor fingerprinting” in individual identification and feature characterization, drawing upon recent literature. It outlines the data processing procedures involved in human odor analysis, highlights the challenges encountered, and explores current research trends. Finally, the application trends of the recognition of human odor are discussed in order to provide reference for odor recognition research.
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