This narrative review explores the transformative role of artificial intelligence (AI) in critical care nephrology, focusing on the early detection, risk prediction, and management of acute kidney injury (AKI) and the optimization of renal replacement therapies in intensive care settings. Drawing from recent valid-indexed studies, the review highlights AI’s ability to enhance clinical decision-making through advanced machine learning models that predict AKI onset hours to days before traditional biomarkers indicate injury. The integration of explainable AI frameworks improves clinician trust and fosters personalized treatment strategies. Additionally, AI applications in continuous renal replacement therapy (CRRT) facilitate individualized dosing and timing, reducing complications and supporting better outcomes. Challenges in data quality, ethical considerations, and clinical implementation are discussed, alongside future directions such as multi-modal data integration and adaptive learning systems. The review underscores AI’s potential to bridge intensive care and nephrology, ultimately aiming to improve patient prognosis in critically ill populations.
Abniki et al. (Thu,) studied this question.