Artificial Intelligence and Machine Learning in Perioperative Monitoring: A Narrative Review

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing the medical profession, particularly in the field of anaesthesia. A recent narrative review published in the Indian Journal of Anaesthesia delves into the role of AI in perioperative monitoring during anaesthesia, highlighting the potential benefits and applications of these technologies.

AI and ML can assist anesthesiologists in various tasks, including pain management, medication distribution, perioperative monitoring, and intensive care unit care. By utilizing ML algorithms such as fuzzy logic, classical ML, neural networks, deep learning, and Bayesian methods, AI can combine different models to enhance decision-making and workflow patterns.

Natural language processing enables computers to interpret human language, facilitating the creation of organized databases and data retrieval from free text fields. Computer vision allows for the automation of visual input processing, including ultrasound images and diagnostic procedures.

In the realm of anaesthesia, AI can improve judgement and solve clinical problems more efficiently. AI is categorized into depth of anaesthesia monitoring, pharmaceutical and mechanical robotic applications, and Clinical Decision Support Systems (CDSS). CDSS plays a crucial role in perioperative monitoring by analyzing patient data and procedural knowledge to determine appropriate anaesthesia dosages and manage perioperative care.

The development of AI-powered cognitive robots in anaesthesia practice can help reduce false alarms and operator fatigue during perioperative monitoring. AI algorithms can be trained to carry out tasks and provide automated suggestions on various topics, ultimately enhancing patient safety and reducing pharmaceutical errors.

Overall, AI has proven to be safer, more advanced, and less unpredictable than human decision-making in medicine. The adoption of AI in perioperative care requires careful consideration to ensure optimal outcomes for patients. The integration of AI and ML technologies in anaesthesia monitoring holds great promise for improving patient care and outcomes in the future.