Artificial intelligence in extracorporeal technology: Current applications and future directions-A narrative review

Artificial intelligence (AI) has rapidly emerged as a transformative force across multiple scientific and clinical domains, demonstrating remarkable capabilities in data analysis, pattern recognition, and predictive modeling. In the realm of healthcare, AI offers the potential to revolutionize patient management, diagnostics, and therapeutic strategies. Among its many applications, extracorporeal technology-encompassing cardiopulmonary bypass (CPB), extracorporeal membrane oxygenation (ECMO), and ventricular assist devices (VADs)-stands to benefit significantly from AI-driven innovations. By integrating real-time physiological data, predictive algorithms, and automated decision-support systems, AI can enhance the safety, precision, and efficiency of extracorporeal circulation, potentially reducing complications and improving patient outcomes. This article provides a comprehensive overview of the fundamental concepts of AI, tracing its historical development and examining its core subfields, including machine learning, deep learning, and cognitive computing. Furthermore, it highlights current applications of AI in extracorporeal technology and explores future possibilities for integrating intelligent systems into perfusion practice, aiming to optimize clinical performance and support personalized patient care.