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亚洲护理领域的人工智能展望

Perspectives on Artificial Intelligence in Nursing in Asia.

作者信息

Lukkahatai Nada, Han Gyumin

机构信息

School of Nursing, Johns Hopkins University, Baltimore, MD, United States.

College of Nursing, Research Institute of Nursing Science, Pusan National University, Busan, Republic of Korea.

出版信息

Asian Pac Isl Nurs J. 2024 Jun 19;8:e55321. doi: 10.2196/55321.

DOI:10.2196/55321
PMID:38896473
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11222764/
Abstract

Artificial intelligence (AI) is reshaping health care, including nursing, across Asia, presenting opportunities to improve patient care and outcomes. This viewpoint presents our perspective and interpretation of the current AI landscape, acknowledging its evolution driven by enhanced processing capabilities, extensive data sets, and refined algorithms. Notable applications in countries such as Singapore, South Korea, Japan, and China showcase the integration of AI-powered technologies such as chatbots, virtual assistants, data mining, and automated risk assessment systems. This paper further explores the transformative impact of AI on nursing education, emphasizing personalized learning, adaptive approaches, and AI-enriched simulation tools, and discusses the opportunities and challenges of these developments. We argue for the harmonious coexistence of traditional nursing values with AI innovations, marking a significant stride toward a promising health care future in Asia.

摘要

人工智能(AI)正在重塑包括护理在内的整个亚洲医疗保健领域,为改善患者护理和治疗结果带来了机遇。本文观点阐述了我们对当前人工智能格局的看法和解读,认可其在增强处理能力、海量数据集和优化算法推动下的发展。新加坡、韩国、日本和中国等国家的显著应用展示了聊天机器人、虚拟助手、数据挖掘和自动风险评估系统等人工智能技术的整合。本文进一步探讨了人工智能对护理教育的变革性影响,强调个性化学习、适应性方法和富含人工智能的模拟工具,并讨论了这些发展带来的机遇和挑战。我们主张传统护理价值观与人工智能创新和谐共存,这标志着亚洲迈向充满希望的医疗保健未来的重要一步。

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本文引用的文献

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Agendas on Nursing in South Korea Media: Natural Language Processing and Network Analysis of News From 2005 to 2022.韩国媒体中的护理议题:2005 年至 2022 年新闻的自然语言处理和网络分析。
J Med Internet Res. 2024 Mar 19;26:e50518. doi: 10.2196/50518.
2
Predictive Models for Palliative Care Needs of Advanced Cancer Patients Receiving Chemotherapy.预测接受化疗的晚期癌症患者姑息治疗需求的模型。
J Pain Symptom Manage. 2024 Apr;67(4):306-316.e6. doi: 10.1016/j.jpainsymman.2024.01.009. Epub 2024 Jan 11.
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AI maturity in health care: An overview of 10 OECD countries.人工智能在医疗保健中的成熟度:10 个经合组织国家概述。
Health Policy. 2024 Feb;140:104938. doi: 10.1016/j.healthpol.2023.104938. Epub 2023 Nov 8.
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Introducing the "AI Language Models in Health Care" Section: Actionable Strategies for Targeted and Wide-Scale Deployment.介绍“医疗保健中的人工智能语言模型”部分:针对性和大规模部署的可行策略。
JMIR Med Inform. 2023 Dec 21;11:e53785. doi: 10.2196/53785.
5
Engaging nurses in developing generative artificial intelligence-based technologies can enhance their work motivation, engagement and satisfaction.让护士参与基于生成式人工智能技术的开发可以提高他们的工作积极性、参与度和满意度。
Evid Based Nurs. 2024 Jun 20;27(3):94. doi: 10.1136/ebnurs-2023-103783.
6
Artificial Intelligence for Multiple Sclerosis Management Using Retinal Images: Pearl, Peaks, and Pitfalls.基于视网膜图像的多发性硬化症管理中的人工智能:珍珠、高峰和陷阱。
Semin Ophthalmol. 2024 May;39(4):271-288. doi: 10.1080/08820538.2023.2293030. Epub 2023 Dec 13.
7
The application of Chat Generative Pre-trained Transformer in nursing education.Chat生成式预训练变换器在护理教育中的应用。
Nurs Outlook. 2023 Nov-Dec;71(6):102064. doi: 10.1016/j.outlook.2023.102064. Epub 2023 Oct 23.
8
Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging.伤口护理中的增强决策:评估深度学习模型用于压力性损伤分期的临床效用。
Int J Med Inform. 2023 Dec;180:105266. doi: 10.1016/j.ijmedinf.2023.105266. Epub 2023 Oct 17.
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A holistic approach to remote patient monitoring, fueled by ChatGPT and Metaverse technology: The future of nursing education.基于 ChatGPT 和元宇宙技术的远程患者监测整体方法:护理教育的未来。
Nurse Educ Today. 2023 Dec;131:105972. doi: 10.1016/j.nedt.2023.105972. Epub 2023 Sep 12.
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Artificial Intelligence and liver: Opportunities and barriers.人工智能与肝脏:机遇与障碍。
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