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[大语言模型的临床应用:ChatGPT是否会取代医学报告撰写?一份经验报告]

[Clinical application of large language models : Does ChatGPT replace medical report formulation? An experience report].

作者信息

Zernikow Jasmin, Grassow Leonhard, Gröschel Jan, Henrion Philippe, Wetzel Paul J, Spethmann Sebastian

机构信息

Klinik für Kardiologie, Angiologie und Intensivmedizin, Deutsches Herzzentrum der Charité (DHZC), Charitéplatz 1, 10117, Berlin, Deutschland.

Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Deutschland.

出版信息

Inn Med (Heidelb). 2023 Nov;64(11):1058-1064. doi: 10.1007/s00108-023-01600-3. Epub 2023 Oct 16.

DOI:10.1007/s00108-023-01600-3
PMID:37843579
Abstract

Artificial intelligence (AI)-based language models, such as ChatGPT offer an enormous potential for research and medical care but also for clinical workflow optimization by making medical documentation easier and more efficient in taking over standardized routine tasks. With their ability to guess a text's content using word statistics and thus outputting contextually relevant results in chat dialogues, large language models (LLM) can provide appropriate summaries of medical documentation for different target groups. For instance, text generation in easy to understand language could potentially contribute to an increase in patients' health literacy and, consequently, to increased adherence to treatment. Subsequent, the function of AI-based chatbot models to improve user experiences and enhance competence in the use of AI-based language models will be adressed. Current limitations and chances in creating epicrises are presented as an experience report. In the future, the implementation of local LLMs in medical management systems (hospital information systems, HIS and practice administration systems, PAS) and in conjunction with the electronic patient records (ePA) can fundamentally change clinical and outpatient care.

摘要

基于人工智能(AI)的语言模型,如ChatGPT,在研究和医疗护理方面具有巨大潜力,在优化临床工作流程方面也有潜力,它能使医疗文档更轻松、高效地完成标准化常规任务。凭借利用词统计来猜测文本内容并在聊天对话中输出上下文相关结果的能力,大型语言模型(LLM)可为不同目标群体提供适当的医疗文档摘要。例如,用通俗易懂的语言生成文本可能有助于提高患者的健康素养,从而提高治疗依从性。随后,将探讨基于AI的聊天机器人模型在改善用户体验和增强使用基于AI的语言模型能力方面的作用。作为一份经验报告,还介绍了撰写病情记录时当前存在的局限性和机遇。未来,在医疗管理系统(医院信息系统、HIS和诊所管理系统、PAS)中以及与电子病历(ePA)结合实施本地LLM,可能会从根本上改变临床和门诊护理。

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本文引用的文献

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Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum.比较医生和人工智能聊天机器人对发布在公共社交媒体论坛上的患者问题的回复。
JAMA Intern Med. 2023 Jun 1;183(6):589-596. doi: 10.1001/jamainternmed.2023.1838.