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大语言模型在急诊医学和重症监护中的应用。

Large language model application in emergency medicine and critical care.

作者信息

Hwai Haw, Ho Yi-Ju, Wang Chih-Hung, Huang Chien-Hua

机构信息

Department of Emergency Medicine, National Taiwan University Hospital, National Taiwan University Medical College, Taipei, Taiwan.

出版信息

J Formos Med Assoc. 2024 Aug 28. doi: 10.1016/j.jfma.2024.08.032.

Abstract

In the rapidly evolving healthcare landscape, artificial intelligence (AI), particularly the large language models (LLMs), like OpenAI's Chat Generative Pretrained Transformer (ChatGPT), has shown transformative potential in emergency medicine and critical care. This review article highlights the advancement and applications of ChatGPT, from diagnostic assistance to clinical documentation and patient communication, demonstrating its ability to perform comparably to human professionals in medical examinations. ChatGPT could assist clinical decision-making and medication selection in critical care, showcasing its potential to optimize patient care management. However, integrating LLMs into healthcare raises legal, ethical, and privacy concerns, including data protection and the necessity for informed consent. Finally, we addressed the challenges related to the accuracy of LLMs, such as the risk of providing incorrect medical advice. These concerns underscore the importance of ongoing research and regulation to ensure their ethical and practical use in healthcare.

摘要

在快速发展的医疗保健领域,人工智能(AI),尤其是大语言模型(LLMs),如OpenAI的聊天生成预训练变换器(ChatGPT),已在急诊医学和重症监护中展现出变革潜力。这篇综述文章重点介绍了ChatGPT的进展和应用,从诊断辅助到临床文档记录以及患者沟通,展示了其在医学检查中与专业人员表现相当的能力。ChatGPT可协助重症监护中的临床决策和药物选择,显示出其优化患者护理管理的潜力。然而,将大语言模型整合到医疗保健中引发了法律、伦理和隐私方面的担忧,包括数据保护和知情同意的必要性。最后,我们探讨了与大语言模型准确性相关的挑战,例如提供错误医疗建议的风险。这些担忧凸显了持续研究和监管的重要性,以确保它们在医疗保健中的道德和实际应用。

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