Necessity and Importance of Developing AI in Anesthesia from the Perspective of Clinical Safety and Information Security

Abstract

The rapid development of artificial intelligence (AI) technology is due to the significant progress in big data, databases, algorithms, and computing power, and medical research is a vital application direction of AI. The integrated development of AI and medicine has improved medical technology, and the efficiency of medical services and equipment has enabled doctors to better serve patients. The tasks and characteristics of the anesthesia discipline also make AI necessary for its development, and AI has also been initially applied in different fields of anesthesia. Our review aims to clarify the current situation and challenges of AI application in anesthesiology to provide clinical references and guide the future development of AI in anesthesiology. This review summarizes progress in the application of AI in perioperative risk assessment and prediction, deep monitoring and regulation of anesthesia, essential anesthesia skills operation, automatic drug administration systems, and teaching and training in anesthesia. Also discussed herein are the accompanying risks and challenges of applying AI in anesthesia: patient privacy and information security, data sources, and ethical issues, lack of capital and talent, and the “black box” phenomenon.

Revitalizing Postoperative Pain Management in Enhanced Recovery After Surgery via Inter-departmental Collaboration Toward Precision Medicine: A Narrative Review

“…However, beyond these foundational aspects, a tantalizing prospect emerges as AI assimilates and scrutinizes historical patient data, encompassing anesthesia or procedural sedation history, and delves into pathophysiological information. This not only holds the promise of enhancing anesthesia medicine but also positions AI to play a pivotal role in advancing precision medicine to the forefront of postoperative pain management [ 43 , 44 ].…”

Personalized anesthesia and precision medicine: a comprehensive review of genetic factors, artificial intelligence, and patient-specific factors

“…The development of artificial intelligence in all aspects of anesthesia has brought significant benefits, including airway management, ultrasound-guided interventions, intelligent drug infusion systems, accurate intraoperative monitoring, and perioperative risk assessment ( 120 ). A randomized trial evaluating the performance of an automated inspired oxygen concentration (FiO2 closed-loop system) using a narrower SpO2 target range found that the time spent within the clinically determined alarm limit (86–94%) was as good as with two wider target ranges ( 121 ).…”

“…These models enhance the interpretation of EEG signals, facilitating nuanced analyzes of complex data streams for depth of anesthesia (DoA) monitoring. Studies have highlighted the efficacy of direct EEG signal analysis through AI and spectral analysis ( 120 ). Park et al ( 145 ) developed a DoA system utilizing real-time EEG and deep neural network algorithms that surpass traditional bispectral index (BIS) systems in performance.…”

“…The application of artificial intelligence (AI) extends beyond monitoring anesthesia depth, fundamentally enhancing perioperative ultrasound imaging. AI’s ability to swiftly and accurately process ultrasound images promises to revolutionize anesthesiologists’ workflows by improving the precision of perioperative diagnostics and reducing the time required for assessment analysis ( 120 ). Hayasaka et al ( 150 ) successfully used AI to predict difficult intubations, while Hetherington et al ( 151 ) designed a neural network model that identifies anatomical landmarks with up to 95% accuracy.…”

Scope of artificial intelligence in airway management

“…[ 10 ] Thus, mastering AI for anticipation and planning in airway management has the potential to surpass the traditional methods of airway management. [ 11 ]…”