Convergence of Artificial Intelligence and Neurological Nursing Care: A Narrative Review of Recent Advancements (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Artificial intelligence (AI) has the potential to optimize neurological nursing cares by enhancing caring support, improving patient monitoring, enabling early intervention, and personalizing care for patients with neurological conditions. </sec> <sec> <title>OBJECTIVE</title> This narrative review aimed to analyze studies on the convergence of AI and neurological nursing cares. </sec> <sec> <title>METHODS</title> Relevant data bases such as including PubMed, Scopus, and Science Direct and Google scholar were searched from 2015 up to 2024; 15 studies were finally selected from a total of 733 founded studies and outcomes were extracted. Studies were selected based on their relevance to AI applications in diagnostic support, patient monitoring, treatment planning and Advances in AI ethics with a focus on neuroscience nursing practice. </sec> <sec> <title>RESULTS</title> The review identified key domain where AI can support nurses: 1] AI enhances diagnostic support through advanced imaging and data analysis techniques, 2) AI-driven monitoring tools facilitate early intervention by predicting adverse events, 3) AI models aid in personalized care, optimizing treatment plans for patients with neurodegenerative conditions, and 4) challenges include technological limitations, ethical concerns, and a need for nurse education. </sec> <sec> <title>CONCLUSIONS</title> Although AI is improving nursing practice in neurological fields, successful integration requires addressing barriers such as infrastructure limitations, data privacy issues, and workforce readiness. </sec> <sec> <title>CLINICALTRIAL</title> Not Applicable </sec>

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