Artificial intelligence and anesthesia: a narrative review

Abstract

Background and objective: The aim of this narrative review is to analyze whether or not artificial intelligence (AI) and its subsets are implemented in current clinical anesthetic practice, and to describe the current state of the research in the field. AI is a general term which refers to all the techniques that enable computers to mimic human intelligence. AI is based on algorithms that gives machines the ability to reason and perform functions such as problem-solving, object and word recognition, inference of world states, and decision-making. It includes machine learning (ML) and deep learning (DL).

Methods: We performed a narrative review of the literature on Scopus, PubMed and Cochrane databases. The research string comprised various combinations of "artificial intelligence", "machine learning", "anesthesia", "anesthesiology". The databases were searched independently by two authors. A third reviewer would mediate any disagreement the results of the two screeners.

Key content and findings: The application of AI has shown excellent results in both anesthesia and in operating room (OR) management. In each phase of the perioperative process, pre-, intra- and postoperative ones, it is able to perform different and specific tasks, using various techniques.

Conclusions: Thanks to the use of these new technologies, even anesthesia, as it is happening for other disciplines, is going through a real revolution, called Anesthesia 4.0. However, AI is not free from limitations and open issues. Unfortunately, the models created, provided they have excellent performance, have not yet entered daily practice. Clinical impact analyzes and external validations are needed before this happens. Therefore, qualitative research will be needed to better understand the ethical, cultural, and societal implications of integrating AI into clinical workflows.

Keywords: Artificial intelligence (AI); anesthesia; deep learning (DL); machine learning (ML); perioperative medicine.

Figure 1

Parallelism between the industrial revolution and the anesthesiological one. From numbers 1 to 4 all the stages in progression are identified. It should be noted that in the fourth revolution, both disciplines are characterized by the use of intelligent tools.

Figure 2

The new technologies in OR management, in addition to being able to optimize resources from an economic point of view, are able to improve both the quality and the safety of the services provided. PACU, post anesthesia care unit; OR, operating room.

Figure 3

Logical architecture diagram of the BLOC-OP study. BLE sensors worn by patient are detected using Raspberry Pi v4 modules, positioned in each OR and recovery room. All data flows into a single server that will be used to create an intelligent scheduling model of surgical procedures using AI techniques. BLE, Bluetooth low energy; AI, artificial intelligence.

Figure 4

Graphic representation of the fields of anesthesiology affected by new technologies. Advanced simulation techniques, telemedicine and AI are the main culprits of the current technological revolution of anesthesia. AI, artificial intelligence.