Artificial Intelligence (AI) Supported Decision-Making in Intensive Care Units: Implications for Nursing and Medical Practice

Abstract

Artificial intelligence (AI) is transforming intensive care medicine by enabling data-driven, real-time decision-making in complex and high-acuity clinical environments. However, its rapid incorporation into healthcare presents profound ethical, clinical, and professional challenges that warrant comprehensive evaluation. This structured narrative review synthesises literature published between 2015 and 2025 to explore how artificial intelligence supports diagnostic, prognostic, monitoring, and therapeutic decision-making in intensive care units (ICUs) and to assess its implications for nursing and medical practice. The findings reveal that AI enhances diagnostic precision, predictive accuracy, and workflow efficiency while improving patient safety and optimising resource utilisation. Nonetheless, ongoing concerns about interpretability, accountability, data quality, and algorithmic bias underscore the necessity for transparent governance, ethical oversight, and multidisciplinary collaboration. Distinctively, this review integrates technological, ethical, and interprofessional perspectives to present a holistic framework for understanding human-artificial intelligence collaboration in critical care. It emphasises that sustainable adoption depends on explainable, context-sensitive systems, clinician engagement, and the inclusion of AI literacy in professional training. This review advances the discourse by framing AI not as a replacement but as a transformative partner, arguing that the future of intensive care lies in harmonising computational precision with clinical empathy to deliver ethical, equitable, and patient-centred outcomes.

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