AI innovations in anaesthesia: A systematic review of clinical application

Abstract

AI innovations in anaesthesia: A systematic review of clinical application - Artificial Intelligence (AI) has emerged as a transformative technology with significant potential to enhance the precision and efficiency of anaesthetic treatments. Utilizing AI-driven predictive analytics and machine learning algorithms, healthcare providers may optimize multiple facets of anaesthetic administration, enhancing resource efficiency and superior patient care. AI can markedly enhance the efficiency of anaesthetic workflow optimization. AI algorithms can scrutinize extensive datasets to discern patterns and trends, allowing anaesthesiologists to enhance operation scheduling, resource distribution, and workflow administration. This systematic review, adhering to PRISMA standards, evaluated AI applications in anaesthesiology across critical care and emergency settings, focusing on ultrasound-guided regional anaesthesia (UGRA) and the integration of AI for improved decision-making and patient outcomes, clinical accuracy, operator efficiency, and hemodynamic management. Systematic review findings reveal significant improvements across multiple domains, including clinical decision support systems that enable more accurate event detection, reduced complications, and enhanced hemodynamic management. In ultrasound-guided regional anaesthesia (UGRA), AI systems such as ScanNav demonstrated high accuracy in identifying anatomical structures, reducing complications, and standardizing procedures. While the potential is immense, the review also highlights the need for further validation, standardization, and exploration of deep learning for seamless clinical integration, highlighting AI’s transformative potential in modern anaesthetic practices while also acknowledging associated health risks. Keywords: Anaesthesiology, Systematic review, AI, Clinical decision support systems.

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