Luigi La Via , Antonino Maniaci , David Gage , Giuseppe Cuttone , Giovanni Misseri , Mario Lentini , Daniele Salvatore Paternò , Federico Pappalardo , Massimiliano Sorbello
{"title":"Exploring the potential of artificial intelligence in airway management","authors":"Luigi La Via , Antonino Maniaci , David Gage , Giuseppe Cuttone , Giovanni Misseri , Mario Lentini , Daniele Salvatore Paternò , Federico Pappalardo , Massimiliano Sorbello","doi":"10.1016/j.tacc.2024.101512","DOIUrl":null,"url":null,"abstract":"<div><div>This review examines the integration of Artificial Intelligence (AI) language models, particularly Chat GPT, in airway management. It explores AI's potential applications in education, clinical decision support, patient communication, and research, as well as its integration with existing medical technologies. The review highlights AI's benefits, including rapid access to current information, care standardization, and potential improvements in patient outcomes. However, it also addresses limitations and ethical considerations such as data security, algorithm bias, and the risk of over-reliance on AI systems. Looking forward, the review discusses AI's potential to revolutionize airway management through predictive analytics, augmented reality, and personalized learning platforms, while acknowledging implementation challenges. The broader implications of AI in healthcare are explored, including its impact on learning, innovation, and the balance between error-free decision-making and human creativity. The review concludes that while AI shows great promise in enhancing airway management, its implementation requires careful consideration of ethical implications and ongoing research. The future of AI in this field lies in its judicious use alongside skilled clinical judgment, potentially leading to significant improvements in patient care and outcomes.</div></div>","PeriodicalId":44534,"journal":{"name":"Trends in Anaesthesia and Critical Care","volume":"59 ","pages":"Article 101512"},"PeriodicalIF":1.4000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Anaesthesia and Critical Care","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210844024001813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This review examines the integration of Artificial Intelligence (AI) language models, particularly Chat GPT, in airway management. It explores AI's potential applications in education, clinical decision support, patient communication, and research, as well as its integration with existing medical technologies. The review highlights AI's benefits, including rapid access to current information, care standardization, and potential improvements in patient outcomes. However, it also addresses limitations and ethical considerations such as data security, algorithm bias, and the risk of over-reliance on AI systems. Looking forward, the review discusses AI's potential to revolutionize airway management through predictive analytics, augmented reality, and personalized learning platforms, while acknowledging implementation challenges. The broader implications of AI in healthcare are explored, including its impact on learning, innovation, and the balance between error-free decision-making and human creativity. The review concludes that while AI shows great promise in enhancing airway management, its implementation requires careful consideration of ethical implications and ongoing research. The future of AI in this field lies in its judicious use alongside skilled clinical judgment, potentially leading to significant improvements in patient care and outcomes.