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REVIEW article

Front. Public Health
Sec. Digital Public Health
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1439412
This article is part of the Research Topic Extracting Insights from Digital Public Health Data using Artificial Intelligence, Volume III View all 4 articles

AI Frontiers in Emergency Care: The Next Evolu(on of Nursing Interven

Provisionally accepted
Zakaria Mani Zakaria Mani 1*Bander Saad Albagawi Bander Saad Albagawi 2
  • 1 Jazan University, Jizan, Saudi Arabia
  • 2 University of Hail, Ha'il, Hail, Saudi Arabia

The final, formatted version of the article will be published soon.

    This scoping review explores the utilization of artificial intelligence in emergency nursing, assessing its impact, potential benefits, and the obstacles faced in its adoption. It covers the scope of AI from advanced triage protocols to continuous monitoring of patients, assistance in diagnosis, and providing support for clinical decisions. The review notes that AI in emergency healthcare can lead to more efficient care and timely, data-driven actions, but also highlights significant issues such as safeguarding patient data, the necessity for dependable infrastructure, and concerns over discriminatory algorithms. The promise of AI in improving emergency healthcare practices and patient care is clear, yet the identified challenges must be carefully navigated to promote safe and ethical use. Further empirical research is called for to confirm the effectiveness of AI applications in the dynamic environment of emergency care setups.

    Keywords: Ar3ficial Intelligence, machine learning, Emergency Nursing, emergency department, Pa3ent Monitoring, Clinical decision support, Ethical Considera3ons

    Received: 27 May 2024; Accepted: 29 Oct 2024.

    Copyright: © 2024 Mani and Albagawi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Zakaria Mani, Jazan University, Jizan, Saudi Arabia

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.