Foundation Models, Generative AI, and Large Language Models: Essentials for Nursing.

IF 1.3 4区 医学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cin-Computers Informatics Nursing Pub Date : 2024-05-01 DOI:10.1097/CIN.0000000000001149
Angela Ross, Kathleen McGrow, Degui Zhi, Laila Rasmy
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Abstract

We are in a booming era of artificial intelligence, particularly with the increased availability of technologies that can help generate content, such as ChatGPT. Healthcare institutions are discussing or have started utilizing these innovative technologies within their workflow. Major electronic health record vendors have begun to leverage large language models to process and analyze vast amounts of clinical natural language text, performing a wide range of tasks in healthcare settings to help alleviate clinicians' burden. Although such technologies can be helpful in applications such as patient education, drafting responses to patient questions and emails, medical record summarization, and medical research facilitation, there are concerns about the tools' readiness for use within the healthcare domain and acceptance by the current workforce. The goal of this article is to provide nurses with an understanding of the currently available foundation models and artificial intelligence tools, enabling them to evaluate the need for such tools and assess how they can impact current clinical practice. This will help nurses efficiently assess, implement, and evaluate these tools to ensure these technologies are ethically and effectively integrated into healthcare systems, while also rigorously monitoring their performance and impact on patient care.

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基础模型、生成式人工智能和大型语言模型:护理要点》。
我们正处于一个人工智能蓬勃发展的时代,尤其是随着可以帮助生成内容的技术(如 ChatGPT)的日益普及。医疗机构正在讨论或已经开始在工作流程中使用这些创新技术。主要的电子健康记录供应商已经开始利用大型语言模型来处理和分析大量的临床自然语言文本,在医疗机构中执行各种任务,帮助减轻临床医生的负担。尽管此类技术在患者教育、起草对患者问题和电子邮件的回复、病历摘要和促进医学研究等应用中很有帮助,但人们对这些工具在医疗保健领域的使用准备情况和现有员工的接受程度仍存在担忧。本文旨在让护士们了解目前可用的基础模型和人工智能工具,使他们能够评估对这些工具的需求,并评估它们如何影响当前的临床实践。这将有助于护士有效地评估、实施和评价这些工具,确保这些技术符合道德规范并有效地融入医疗保健系统,同时严格监控其性能和对患者护理的影响。
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来源期刊
Cin-Computers Informatics Nursing
Cin-Computers Informatics Nursing 工程技术-护理
CiteScore
2.00
自引率
15.40%
发文量
248
审稿时长
6-12 weeks
期刊介绍: For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.
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