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

Area of Science:

• Medical Technology
• Artificial Intelligence
• Healthcare Informatics

Background:

• Artificial intelligence (AI) is a transformative technology with significant potential in healthcare.
• Extracorporeal technologies, including cardiopulmonary bypass (CPB), extracorporeal membrane oxygenation (ECMO), and ventricular assist devices (VADs), are critical in managing severe physiological compromise.
• Integrating AI into these technologies can enhance patient management, diagnostics, and therapeutic strategies.

Purpose of the Study:

• To provide a comprehensive overview of AI concepts and their relevance to extracorporeal technology.
• To examine current applications of AI in perfusion practice.
• To explore future possibilities for AI integration in extracorporeal circulation.

Main Methods:

• Review of fundamental AI concepts (machine learning, deep learning, cognitive computing).
• Analysis of current AI applications in extracorporeal technologies (CPB, ECMO, VADs).
• Exploration of future integration strategies for intelligent systems in perfusion.

Main Results:

• AI demonstrates capabilities in data analysis, pattern recognition, and predictive modeling applicable to healthcare.
• AI can enhance the safety, precision, and efficiency of extracorporeal circulation by integrating real-time data and predictive algorithms.
• Potential for AI to reduce complications and improve patient outcomes in extracorporeal procedures.

Conclusions:

• AI offers significant potential to revolutionize extracorporeal technology and perfusion practice.
• Intelligent systems can optimize clinical performance and support personalized patient care.
• Future integration of AI in extracorporeal circulation is poised to improve patient outcomes and advance medical interventions.