Artificial intelligence (AI) has great potential to improve the field of critical care and enhance
patient outcomes. This paper provides an overview of current and future applications of AI in …

Sepsis, a critical condition marked by systemic inflammation, profoundly impacts both innate
and adaptive immunity, often resulting in lymphopenia. This immune alteration can spare …

Background Interest in critical care–related artificial intelligence (AI) research is growing
rapidly. However, the literature is still lacking in comprehensive bibliometric studies that …

Background: An early diagnosis model with clinical phenotype classification is key for the
early identification and precise treatment of sepsis-associated acute respiratory distress …

Providing timely intervention to critically ill patients is a challenging task in emergency
departments (ED). Our study aimed to predict early critical interventions (CrIs), which can be …

AI writing assistants that are capable of offering rapid, automatic, and corrective feedback
are becoming increasingly powerful, providing accurate and automatic feedback to …

This scoping review focuses on the essential role of models for causal inference in shaping
actionable artificial intelligence (AI) designed to aid clinicians in decision-making. The …

Over the last several decades, the cardiac intensive care unit (CICU) has seen a substantial
evolution in the patient population, comorbidities, and diagnoses. However, the generation …

Fluid overload, while common in the ICU and associated with serious sequelae, is hard to
predict and may be influenced by ICU medication use. Machine learning (ML) approaches …

Since the advent of critical care in the twentieth century, the core elements that are the
foundation for critical care systems, namely to care for critically ill and injured patients and to …