Artificial intelligence for perioperative risk assessment in minimally invasive cardiac surgery: current applications and future perspectives

Abstract

Minimally invasive cardiac surgery (MICS) represents a significant advancement in cardiac surgical care, offering benefits such as reduced trauma, shorter hospital stays, and faster recovery. However, the complexity of perioperative management in MICS demands highly accurate risk stratification and decision-making. Artificial intelligence (AI) technologies are increasingly being integrated into perioperative workflows, providing clinicians with data-driven tools to enhance patient selection, predict complications, and optimize outcomes. This review explores current applications of AI in the perioperative assessment of patients undergoing minimally invasive cardiac procedures, with a focus on preoperative risk prediction, intraoperative monitoring, and postoperative management. It discusses the potential of AI to support precision medicine in MICS, highlights the technical and ethical challenges associated with its implementation, and outlines future directions for research and clinical integration. By bridging surgical innovation and computational intelligence, AI is poised to reshape the landscape of perioperative cardiac care.

Keywords

Artificial intelligence / cardiac surgery / minimally invasive surgery / perioperative risk / machine learning / risk stratification / surgical planning / clinical decision support

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