人工智能在重症护理领域中应用的范围综述

doi:10.3761/j.issn.2096-7446.2026.09.008

中华急危重症护理杂志 ›› 2026, Vol. 7 ›› Issue (9): 1082-1088.doi: 10.3761/j.issn.2096-7446.2026.09.008

• 急危重症智慧护理专题 • 上一篇下一篇

人工智能在重症护理领域中应用的范围综述

余严超¹(), 高欣², 翁峰霞¹^,^*(), 卫建华¹, 桑明¹, 朱永康¹, 陈小艳¹

¹ 浙江大学医学院附属第一医院外科监护室杭州市 310003
² 英国爱丁堡大学社会科学健康学院爱丁堡市 EH8 9RQ

收稿日期:2025-09-20 出版日期:2026-09-10 发布日期:2026-08-31
通讯作者: *翁峰霞，E-mail：wengfengxia@zju.edu.cn
作者简介:余严超：男，本科，护师，E-mail：yyc1092527822@qq.com
作者贡献声明
余严超、高欣：选题设计、文献检索、整理与分析、论文撰写及修改；翁峰霞、卫建华、陈小艳：研究指导、论文修改；桑明、朱永康：论文审阅修改
基金资助:
浙大一院护理学科建设项目(2022ZYHL033)

Application of artificial intelligence in critical care：a scoping review

YU Yanchao¹(), GAO Xin², WENG Fengxia¹^,^*(), WEI Jianhua¹, SANG Ming¹, ZHU Yongkang¹, CHEN Xiaoyan¹

¹ Surgical Intensive Care Unit， the First Affiliated Hospital，Zhejiang University School of Medicine， Hangzhou 310003， China
² School of Health in Social Science， University of Edinburgh， Edinburgh EH8 9RQ， UK

Received:2025-09-20 Online:2026-09-10 Published:2026-08-31
Contact: * WENG Fengxia，E-mail：wengfengxia@zju.edu.cn
Supported by:
Zhejiang University First Hospital Nursing Discipline Development Project(2022ZYHL033)

摘要/Abstract

摘要：

目的系统梳理人工智能在重症护理领域的研究现状、应用场景、技术挑战及未来发展方向，为人工智能与重症护理的深度融合提供研究方向和理论依据，推动患者预后改善和医疗质量提升。方法采用Arksey等提出的范围综述框架，检索PubMed、Web of Science、中国知网、万方数据库等数据库中的相关文献，检索时限为建库至2025年4月30日，最终纳入17篇文献。结果人工智能在重症护理中的应用主要集中在监测预警系统、临床决策支持系统、文档记录自动化、资源分配优化及预测分析模型五大领域。主要挑战包括人工智能模型数据碎片化、泛化能力不足、医护人员对人工智能工具的接受度与使用能力有待提升和伦理隐私等问题。结论人工智能应用于重症护理领域可显著改善工作流程、提高工作效率，未来研究应着重于多中心数据共享平台的构建、跨学科协作机制的完善，以及以患者为中心的人工智能系统设计，以充分发挥其在提升重症护理质量和效率方面的价值。

关键词: 人工智能, 重症护理, 机器学习, 临床决策支持, 范围综述

Abstract:

Objective To systematically synthesize the current research status，application scenarios，technical challenges，and future development directions of artificial intelligence（AI） in the field of critical care. This review aims to provide novel research perspectives and theoretical foundations for the in-depth integration of AI and critical care，thereby promoting improvements in patient prognosis and healthcare quality. Methods Using the scoping review framework proposed by Arksey et al.，relevant literature was searched in databases such as PubMed，Web of Science，CNKI，and Wanfang Database，with the search period up to April 30，2025，and a total of 17 articles were ultimately included. Results The applications of AI in critical care primarily focus on five core domains，including monitoring and early warning systems，clinical decision support systems，documentation automation，resource allocation optimization，and predictive analysis models. The primary challenges include data fragmentation in AI models，limited generalization capability，the need to improve medical staff’s acceptance and practical skills with AI tools，as well as ethical and privacy concerns. Conclusion The integration of AI into critical care can significantly optimize workflow efficiency and enhance work performance. Future research should prioritize the establishment of multi-center data sharing platforms，the refinement of interdisciplinary collaboration mechanisms，and the design of patient-centered AI systems，to fully unleash the value of AI in improving the quality and efficiency of critical care services.

Key words: Artificial Intelligence, Critical Care, Machine Learning, Clinical Decision Support, Scoping Review

余严超, 高欣, 翁峰霞, 卫建华, 桑明, 朱永康, 陈小艳. 人工智能在重症护理领域中应用的范围综述[J]. 中华急危重症护理杂志, 2026, 7(9): 1082-1088.

YU Yanchao, GAO Xin, WENG Fengxia, WEI Jianhua, SANG Ming, ZHU Yongkang, CHEN Xiaoyan. Application of artificial intelligence in critical care：a scoping review[J]. Chinese Journal of Emergency and Critical Care Nursing, 2026, 7(9): 1082-1088.

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人工智能在重症护理领域中应用的范围综述

Application of artificial intelligence in critical care：a scoping review

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