Topic: Artificial Intelligence in Acute Care Surgery

Acute Care Surgery (ACS), including trauma surgery, emergency general surgery, and surgical critical care, requires rapid decision-making under complex and uncertain clinical conditions. Recent advances in artificial intelligence (AI), including machine learning, deep learning, computer vision, and multimodal foundation models, provide new opportunities to enhance diagnosis, risk prediction, surgical planning, and real-time clinical decision support.

The integration of AI with medical imaging, electronic health records, physiological monitoring, and surgical data has the potential to transform acute surgical care from experience-driven decision-making toward data-driven, personalized, and proactive management. However, challenges remain regarding clinical validation, workflow integration, model interpretability, data heterogeneity, and regulatory implementation.

This Special Issue aims to highlight emerging AI technologies and translational research in Acute Care Surgery, covering AI-assisted diagnosis, predictive analytics, intelligent monitoring, surgical decision support, critical care applications, and future directions for AI-enabled emergency and trauma surgery. By bringing together surgeons, engineers, and data scientists, this issue seeks to accelerate the safe and effective adoption of AI in acute surgical practice and improve patient outcomes.