Mohammad ShokatiSayyad - Department of Toxicology and Pharmacology, Faculty of Pharmacy, Mazandaran University of Medical Sciences, Sari, Iran.
Mohammad Seyedabadi - Department of Toxicology and Pharmacology, Faculty of Pharmacy, Mazandaran University of Medical Sciences, Sari, Iran.
Vida Motamed Nia - Department of Toxicology and Pharmacology, Faculty of Pharmacy, Mazandaran University of Medical Sciences, Sari, Iran.
Mohammad Hossein Sadeghian - Department of Forensic Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Background: Poisoning is a significant public health concern, encompassing a broad range of sudden and severe health issues resulting from the ingestion, inhalation, or contact with toxic substances. The potential for injury or fatality necessitates urgent medical attention and care. With the ongoing advancements in artificial intelligence (AI) and its increasing integration into medical and pharmaceutical domains, there is a growing interest in exploring the role of AI in the context of poisonings. This study aims to investigate the potential applications of AI in the management and treatment of poisoning.Materials and methods: This research is a review by searching the keywords ("Artificial intelligence") [TIAB] AND (poisoning [TIAB] OR toxicity[TIAB] OR intoxication[TIAB] OR Toxin[TIAB] OR poison[TIAB]) was searched in the internet databases PubMed, Scopus, and Google Scholar search engine in ۲۰۱۶-۲۰۲۴.Conclusion: Enhancing system management and treatment approaches is crucial in preventing accidental and intentional poisoning. This can be achieved by incorporating cutting-edge medical equipment, such as those equipped with AI. AI technology can recognize complex patterns beyond predefined rules and process large amounts of data, exceeding human capabilities. In the future, more progress in AI will likely affect various areas of healthcare, including poison prevention and treatment, to improve patient outcomes and reduce the burden of poisoning on healthcare systems.

Artificial intelligence, Machine Learning, Poisoning, Toxicity