Integration, challenges, and future of artificial intelligence in critical care medicine: comprehensive applications from predictive models to clinical integration.

Artificial intelligence (AI) in intensive care units (ICUs) has advanced rapidly since 2018, with core applications in sepsis prediction, mechanical ventilation management, and acute kidney injury (AKI) early warning, utilizing machine learning and deep learning models on multimodal data such as vital signs and electronic health records to achieve high predictive accuracy, including AUROC values up to 0.96 for sepsis. Despite these developments, widespread clinical adoption faces significant challenges, including limited prospective multicenter validation, the "black-box" nature of algorithms, integration into clinical workflows, and ethical concerns regarding fairness and transparency, necessitating rigorous evaluation and multidisciplinary collaboration to translate AI into routine critical care practice.