Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Generative AI Applications in Nursing Practice and Clinical Decision-Making
0
Zitationen
6
Autoren
2026
Jahr
Abstract
Generative AI in Clinical Documentation represents one of the most transformative intersections of machine intelligence and healthcare delivery, reconfiguring how clinicians record, interpret, and operationalise patient information in increasingly complex care environments. As global health systems grapple with rising administrative burdens, workforce shortages, and the escalating complexity of multimorbidity, generative AI functions not merely as a digital scribe but as an adaptive, context-aware partner that enhances the cognitive and operational capacity of clinical teams. At its core, generative AI leverages large-scale language models capable of parsing unstructured inputs—such as physician-patient conversations, fragmented notes across disparate electronic health record (EHR) environments, and evolving diagnostic narratives—to produce coherent, accurate, and contextually aligned documentation in real time. This shift from manual charting to dynamic, AI-assisted documentation not only minimises clerical load but also reshapes.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.250 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.109 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.482 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.434 Zit.