Chinese Journal of Emergency and Critical Care Nursing ›› 2026, Vol. 7 ›› Issue (9): 1082-1088.doi: 10.3761/j.issn.2096-7446.2026.09.008
• Special Planning-Intelligent Nursing Care for Emergency and Critical Illnesses • Previous Articles Next Articles
YU Yanchao1(
), GAO Xin2, WENG Fengxia1,*(
), WEI Jianhua1, SANG Ming1, ZHU Yongkang1, CHEN Xiaoyan1
Received:2025-09-20
Online:2026-09-10
Published:2026-08-31
Contact:
* WENG Fengxia,E-mail:wengfengxia@zju.edu.cn
Supported by: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.
| [1] | Martinez-Ortigosa A, Martinez-Granados A, Gil-Hernández E, et al. Applications of artificial intelligence in nursing care:a systematic review[J]. J Nurs Manag, 2023, 2023:3219127. |
| [2] | 夏浩然, 陈小艳, 赵慧明, 等. 搭载ChatGPT的人工机械瓣膜置换术后患者自我监测随访大数据平台的建设与实践[J]. 中国实用护理杂志, 2023, 39(29):2276-2284. |
| Xia HR, Chen XY, Zhao HM, et al. Construction and practice of a big data platform for self-monitoring follow-up of patients after mechanical valve replacement using ChatGPT[J]. Chin J Pract Nurs, 2023, 39(29):2276-2284. | |
| [3] |
徐春健, 蔡婷婷, 谢逸菲, 等. 机器学习模型在安宁疗护中应用的范围综述[J]. 中华护理杂志, 2025, 60(12):1524-1531.
doi: 10.3761/j.issn.0254-1769.2025.12.019 |
| Xu CJ, Cai TT, Xie YF, et al. Machine learning models in hospice care:a scope review[J]. Chin J Nurs, 2025, 60(12):1524-1531. | |
| [4] |
Park Y, Chang SJ, Kim E. Artificial intelligence in critical care nursing:a scoping review[J]. Aust Crit Care, 2025, 38(4):101225.
doi: 10.1016/j.aucc.2025.101225 |
| [5] |
Arksey H, O’Malley L. Scoping studies:towards a methodological framework[J]. Int J Soc Res Methodol, 2005, 8(1):19-32.
doi: 10.1080/1364557032000119616 |
| [6] |
Wang SR, Liu XY, Yuan SH, et al. Artificial intelligence based multispecialty mortality prediction models for septic shock in a multicenter retrospective study[J]. NPJ Digit Med, 2025, 8(1):228.
doi: 10.1038/s41746-025-01643-w pmid: 40295871 |
| [7] | 李梦珂, 孙焱, 刘鸿齐, 等. 基于机器学习算法的非计划重返ICU风险预测模型研究[J]. 护理研究, 2024, 38(22):3976-3982. |
| Li MK, Sun Y, Liu HQ, et al. Research on risk prediction model for unplanned return to ICU based on machine learning algorithm[J]. Chin Nurs Res, 2024, 38(22):3976-3982. | |
| [8] | Zhang S, Cui W, Ding S, et al. A cluster-randomized controlled trial of a nurse-led artificial intelligence assisted prevention and management for delirium(AI-AntiDelirium) on delirium in intensive care unit:study protocol[J]. PLoS One, 2024, 19(2):e0298793. |
| [9] |
Milliren CE, Ozonoff A, Fournier KA, et al. Enhancing pressure injury surveillance using natural language processing[J]. J Patient Saf, 2024, 20(2):119-124.
doi: 10.1097/PTS.0000000000001193 pmid: 38147064 |
| [10] | Gu SY, Lee EW, Zhang WH, et al. Evaluating natural language processing packages for predicting hospital-acquired pressure injuries from clinical notes[J]. Comput Inform Nurs, 2024, 42(3):184-192. |
| [11] | 李世玫, 余爱华, 王苗苗, 等. 基于人工智能压力性损伤图片分析系统的精细干预在神经内科重症患者中的应用[J]. 河北医药, 2024, 46(20):3194-3196,3200. |
| Li SM, Yu AH, Wang MM, et al. Application of fine intervention based on artificial intelligence stress injury imaging analysis system to critically ill patients in the neurology department[J]. Hebei Med J, 2024, 46(20):3194-3196,3200. | |
| [12] |
Tran A, Topp R, Tarshizi E, et al. Predicting the onset of sepsis using vital signs data:a machine learning approach[J]. Clin Nurs Res, 2023, 32(7):1000-1009.
doi: 10.1177/10547738231183207 |
| [13] |
Sotoodeh M, Zhang WH, Simpson RL, et al. A comprehensive and improved definition for hospital-acquired pressure injury classification based on electronic health records:comparative study[J]. JMIR Med Inform, 2023, 11:e40672.
doi: 10.2196/40672 |
| [14] |
Lei L, Zhang S, Yang L, et al. Machine learning-based prediction of delirium 24 h after pediatric intensive care unit admission in critically ill children:a prospective cohort study[J]. Int J Nurs Stud, 2023, 146:104565.
doi: 10.1016/j.ijnurstu.2023.104565 |
| [15] |
Im S, Lee SM. Development of mortality prediction model using electronic health record(EHR) data and machine learning algorithm in intensive care unit(ICU)[J]. Korean Data Anal Soc, 2023, 25(5):1977-1992.
doi: 10.37727/jkdas. |
| [16] |
Mulkey M, Albanese T, Kim S, et al. Delirium detection using GAMMA wave and machine learning:a pilot study[J]. Res Nurs Health, 2022, 45(6):652-663.
doi: 10.1002/nur.v45.6 |
| [17] |
Xu J, Chen DX, Deng XF, et al. Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit[J]. Int Wound J, 2022, 19(7):1637-1649.
doi: 10.1111/iwj.13764 pmid: 35077000 |
| [18] |
Huang KX, Gray TF, Romero-Brufau S, et al. Using nursing notes to improve clinical outcome prediction in intensive care patients:a retrospective cohort study[J]. J Am Med Inform Assoc, 2021, 28(8):1660-1666.
doi: 10.1093/jamia/ocab051 |
| [19] |
Ladios-Martin M, Fernández-de-Maya J, Ballesta-López FJ, et al. Predictive modeling of pressure injury risk in patients admitted to an intensive care unit[J]. Am J Crit Care, 2020, 29(4):e70-e80.
doi: 10.4037/ajcc2020237 |
| [20] |
Korach ZT, Yang J, Rossetti SC, et al. Mining clinical phrases from nursing notes to discover risk factors of patient deterioration[J]. Int J Med Inform, 2020, 135:104053.
doi: 10.1016/j.ijmedinf.2019.104053 |
| [21] |
Tawfik DS, Profit J, Lake ET, et al. Development and use of an adjusted nurse staffing metric in the neonatal intensive care unit[J]. Health Serv Res, 2020, 55(2):190-200.
doi: 10.1111/1475-6773.13249 pmid: 31869865 |
| [22] | 任国奇. 深度逆强化学习在脓毒症中的应用[D]. 大连: 大连理工大学, 2020. |
| Ren GQ. Application of deep inverse reinforcement learning in sepsis[D]. Dalian: Dalian University of Technology, 2020. | |
| [23] | 穆兰, 徐文博, 王学通. 类ChatGPT大语言模型在护理教育中应用的实证探讨与前景展望[J]. 卫生职业教育, 2024, 42(20):4-7. |
| Mu L, Xu WB, Wang XT. Empirical exploration and prospect on the application of ChatGPT-like large language model in nursing education[J]. Health Vocat Educ, 2024, 42(20):4-7. | |
| [24] | 马应卓, 王俊, 刘彤, 等. 大语言模型在护理学领域应用的范围综述[J]. 护理学杂志, 2024, 39(19):124-129. |
| Ma YZ, Wang J, Liu T, et al. A scoping review of the applications of large language models in nursing science[J]. J Nurs Sci, 2024, 39(19):124-129. | |
| [25] |
Bomrah S, Uddin M, Upadhyay U, et al. A scoping review of machine learning for sepsis prediction-feature engineering strategies and model performance:a step towards explainability[J]. Crit Care, 2024, 28(1):180.
doi: 10.1186/s13054-024-04948-6 |
| [26] | 袁力蓉, 谭文君, 朱皓阳, 等. 智能吸痰机器人安全性和有效性的实验研究[J]. 临床医学研究与实践, 2020, 5(17):5-8. |
| Yuan LR, Tan WJ, Zhu HY, et al. Experimental study on safety and effectiveness of intelligent sputum-sucking robot[J]. Clin Res Pract, 2020, 5(17):5-8. | |
| [27] |
Woodnutt S, Allen C, Snowden J, et al. Could artificial intelli-gence write mental health nursing care plans[J]. J Psychiatr Ment Health Nurs, 2024, 31(1):79-86.
doi: 10.1111/jpm.v31.1 |
| [28] | 李丹彤, 梁会营, 刘广建. 临床科研数据库建设中的数据标准化问题探讨[J]. 中国数字医学, 2021, 16(1):29-34. |
| Li DT, Liang HY, Liu GJ. Discussion on data standardization in the construction of clinical research database[J]. China Digit Med, 2021, 16(1):29-34. | |
| [29] |
赵永信, 顾莺, 张晓波, 等. 基于临床护理分类系统的患儿体温过高护理程序知识库的构建[J]. 中华护理杂志, 2020, 55(12):1808-1812.
doi: 10.3761/j.issn.0254-1769.2020.12.009 |
|
Zhao YX, Gu Y, Zhang XB, et al. Construction of nursing procedures knowledge base for pediatric hyperthermia based on clinical care classification[J]. Chin J Nurs, 2020, 55(12):1808-1812.
doi: 10.3761/j.issn.0254-1769.2020.12.009 |
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