<![CDATA[The integration of artificial intelligence (AI) into critical care medicine represents one of the most transformative developments of the modern era, particularly in the domain of nutritional support. Nutrition in critically ill patients is a complex, dynamic, and individualized component of care, intimately linked with outcomes such as morbidity, mortality, length of stay, and recovery trajectories. Historically, the approach to nutritional management in intensive care units (ICUs) has been guided by static protocols, clinician experience, and limited data-driven personalization. However, the advent of AI has heralded a new paradigm—one where algorithms are capable of synthesizing massive volumes of patient-specific and population-level data to optimize nutritional strategies in real-time. This abstract explores the evolving role of AI in the nutritional management of critically ill patients, elucidating its current capabilities, transformative potential, and the nuanced challenges inherent in its implementation.]]>
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