{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T17:13:22Z","timestamp":1791652402064,"version":"4.3.4"},"reference-count":46,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Nursing in Critical Care"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) and machine learning (ML) are emerging as transformative tools in healthcare, with significant potential to enhance nursing practice, particularly in intensive care units (ICUs). ICUs pose complex challenges, including high patient acuity, ICU delirium, and nurse workload. These factors demand innovative technological solutions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>This scoping review comprehensively explores the current picture of AI and ML applications in critical care nursing, focusing on decision support systems, predictive analytics, workflow automation, and patient engagement tools.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A search of Four databases (Scopus, PubMed\/MEDLINE, Science Direct, and CINAHL) was conducted for original peer\u2010reviewed studies published between January 2019 and September 2025. The 2019 start date was selected to capture the contemporary wave of AI applications in critical care nursing, coinciding with the documented exponential growth in AI\u2010related ICU publications following widespread EHR adoption and the maturation of deep learning architectures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Five key themes were identified: predictive analytics and early warning systems, clinical decision\u2010support tools, automation and workflow enhancements, monitoring combined with human\u2013AI collaboration, and implementation challenges. Findings reveal that AI can reduce administrative burden and improve care quality. However, significant gaps persist, especially in evaluating long\u2010term outcomes, nurse involvement, and ethical implementation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This scoping review provides a contemporary, integrated thematic synthesis of machine learning and AI applications in critical care nursing. While not claiming absolute novelty, this review addresses a distinct and timely gap by simultaneously mapping predictive analytics, clinical decision support, workflow automation, and implementation challenges within a single evidence synthesis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Relevance to Clinical Practice<\/jats:title>\n                    <jats:p>AI and machine learning may support critical care nurses by facilitating earlier recognition of patient deterioration, strengthening clinical decision\u2010making, and reducing repetitive workload. Successful implementation requires nurse involvement in system design, appropriate training, transparent algorithms, and integration with existing clinical workflows.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/nicc.70629","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T04:17:57Z","timestamp":1787631477000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Role of Machine Learning and Artificial Intelligence in Enhancing Critical Care Nursing Practice: A Scoping Review"],"prefix":"10.1111","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-9760-651X","authenticated-orcid":false,"given":"Omar","family":"Alqaisi","sequence":"first","affiliation":[{"name":"Faculty of Nursing Al\u2010Zaytoonah University  Amman Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8345-0140","authenticated-orcid":false,"given":"Suhair","family":"Al\u2010Ghabeesh","sequence":"additional","affiliation":[{"name":"Faculty of Nursing Al\u2010Zaytoonah University  Amman Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7324-264X","authenticated-orcid":false,"given":"Mohammed","family":"Dibas","sequence":"additional","affiliation":[{"name":"Department of Medicine, Faculty of Medicine and Health Sciences An\u2010Najah National University  Nablus Palestine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9309-9959","authenticated-orcid":false,"given":"Lorent","family":"Sijarina","sequence":"additional","affiliation":[{"name":"Faculty of Medicine University of Prishtina  Prishtina Kosovo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7700-776X","authenticated-orcid":false,"given":"Patricia","family":"Tai","sequence":"additional","affiliation":[{"name":"Department of Oncology University of Saskatchewan  Saskatoon Saskatchewan Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"e_1_2_17_2_1","doi-asserted-by":"publisher","DOI":"10.3233\/SHTI240140"},{"key":"e_1_2_17_3_1","doi-asserted-by":"publisher","DOI":"10.3389\/fdgth.2025.1552372"},{"key":"e_1_2_17_4_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0298793"},{"key":"e_1_2_17_5_1","doi-asserted-by":"publisher","DOI":"10.57239\/PJLSS\u20102024\u201022.2.00643"},{"key":"e_1_2_17_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e25718"},{"key":"e_1_2_17_7_1","doi-asserted-by":"publisher","DOI":"10.3390\/nursrep15020055"},{"issue":"4","key":"e_1_2_17_8_1","first-page":"415","article-title":"Artificial Intelligence: A Valuable and Effective Tool to Improve Nursing Care of Patients Admitted to the Intensive Care Unit","volume":"3","author":"Khani A.","year":"2024","journal-title":"Journal of Nursing Reports in Clinical Practice"},{"key":"e_1_2_17_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12912\u2010024\u201002363\u20104"},{"key":"e_1_2_17_10_1","doi-asserted-by":"publisher","DOI":"10.2196\/28781"},{"key":"e_1_2_17_11_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2303.06252"},{"key":"e_1_2_17_12_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2024.0084"},{"key":"e_1_2_17_12_2","doi-asserted-by":"crossref","unstructured":"Erratum in: JAMA Internal Medicine 2024;184(9):1137 https:\/\/doi.org\/10.1001\/jamainternmed.2024.3693.","DOI":"10.1001\/jamainternmed.2024.3553"},{"key":"e_1_2_17_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41591\u2010025\u201003609\u20107"},{"key":"e_1_2_17_14_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2025.22866"},{"key":"e_1_2_17_15_1","doi-asserted-by":"publisher","DOI":"10.1080\/1364557032000119616"},{"key":"e_1_2_17_16_1","doi-asserted-by":"publisher","DOI":"10.11124\/JBIES\u201020\u201000167"},{"key":"e_1_2_17_17_1","doi-asserted-by":"crossref","DOI":"10.1111\/nicc.70629","volume-title":"The role of machine learning and artificial intelligence in enhancing critical care nursing practice: a scoping review [Internet]","author":"Alqaisi O. 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