Generative AI Applications in Nursing Practice and Clinical Decision-Making

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Authors: P. Selvakumar, R Parthiban, T. C. Manjunath, S. Saradha, Syed Muqthadar Ali, K. K. Naresh
Cited by: 0
References: 32

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.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Nursing Diagnosis and Documentation Electronic Health Records Systems

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
21–48
Publication date
4 March 2026
Language
EN
Document type
Book chapter