Abstract:

The explosive growth of artificial intelligence （AI） technology has brought revolutionary opportunities to critical care medicine. This study systematically explores the key applications of AI in critical care informatization，including intelligent electronic medical record （EMR） analysis，multimodal data integration，AI-assisted clinical decision-making，optimization of tele-intensive care unit （Tele-ICU），and the synergistic integration of emerging technologies such as the Internet of Things （IoT），blockchain，and virtual reality/augmented reality （VR/AR）. By analyzing current AI-driven practices in critical care，this research highlights its core value in enhancing diagnostic precision，optimizing resource allocation，and reducing healthcare costs. Furthermore，the study delves into the challenges hindering AI adoption，such as insufficient data standardization，model explainability gaps，privacy security risks，and limitations in clinical adaptability. It proposes breakthrough solutions through federated learning，explainable AI （ⅩAI） techniques，policy refinement，and interdisciplinary collaboration. The study also envisions future directions，including deep integration of AI with bedside terminals，construction of a lifecycle monitoring system，and innovation in precision medicine paradigms. The primary objective of this research is to provide theoretical and practical guidance for the intelligent transformation of critical care medicine，facilitating the evolution of AI from an auxiliary tool to a core decision-making engine. Ultimately，this aims to achieve comprehensive improvements in the quality and efficiency of critical care，promote equitable access to medical resources，and enhance patient outcomes.

Key words: Critical care medicine, Information technology, Artificial intelligence, Data security