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European Health Evidence

The European alternative to PubMed

EUVIMED is the European alternative to PubMed: a central, multilingual research platform for medicine, nursing, life sciences and healthcare. It brings together international and European literature sources, study registries, open-access full texts, citations and retraction notices in one search. Unlike pure bibliographic databases, EUVIMED supports the entire research process – from discovery and appraisal with LIVIA and CLARA to traceable evidence synthesis. European in focus, transparent, interoperable and designed for science and healthcare.

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Lokaler Crossref-Datenbestand · journal-article

ARTIFICIAL INTELLIGENCE AND NURSING: CLINICAL APPLICATIONS, PATIENT SAFETY, HUMANIZATION, AND ETHICAL GOVERNANCE

Heloísa de Oliveira Nascimento

Nexus Science Review · 2026

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Artificial intelligence (AI) is increasingly reshaping nursing practice by supporting clinical decision-making, patient monitoring, documentation, education, workflow management, and patient safety. This integrative literature review critically examines the principal applications, benefits, limitations, and ethical implications of AI in nursing, with emphasis on emergency triage, hospital data management, clinical decision support, humanized care, and safety governance. A structured search of PubMed/MEDLINE and major peer-reviewed journal platforms was conducted, prioritizing literature published from 2020 onward while retaining seminal works required for the theoretical framework. Peer-reviewed original studies, systematic and integrative reviews, umbrella reviews, and authoritative institutional guidance were considered. The evidence indicates that AI can improve risk stratification, early recognition of clinical deterioration, medication-safety processes, documentation quality, and access to simulation-based education. Nevertheless, the literature remains heterogeneous, and many applications lack prospective validation across diverse health systems and populations. Major concerns include algorithmic bias, privacy, opacity, automation bias, alert fatigue, unequal technological access, and unclear accountability. The findings support a human-in-the-loop model in which AI augments rather than replaces nursing judgment. Sustainable adoption therefore requires local validation, continuous performance monitoring, AI literacy, interdisciplinary governance, and explicit protection of patient autonomy and relational care. For Brazil, further multicenter research is needed to evaluate AI under the organizational, demographic, and infrastructural conditions of the Unified Health System. AI should ultimately be assessed not only by technical performance, but by its capacity to strengthen safe, equitable, evidence-based, and person-centered nursing care.

Bibliografischer Nachweis

Publikationsdaten

Autor:innen
Heloísa de Oliveira Nascimento
Quelle
Nexus Science Review
Publikation
2026-01-01
Band / Ausgabe
Nicht angegeben
Seiten
Nicht angegeben
ISSN / ISBN
3086-5476
Zitationen
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Zitierfähiger Nachweis

Heloísa de Oliveira Nascimento (2026). ARTIFICIAL INTELLIGENCE AND NURSING: CLINICAL APPLICATIONS, PATIENT SAFETY, HUMANIZATION, AND ETHICAL GOVERNANCE. Nexus Science Review. https://doi.org/10.66104/4xwn8e04
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