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      Artificial Intelligence in Anesthesiology

      1 , 1 , 1 , 1 , 1

      Anesthesiology

      Ovid Technologies (Wolters Kluwer Health)

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          Abstract

          Artificial intelligence has been advancing in fields including anesthesiology. This scoping review of the intersection of artificial intelligence and anesthesia research identified and summarized six themes of applications of artificial intelligence in anesthesiology: (1) depth of anesthesia monitoring, (2) control of anesthesia, (3) event and risk prediction, (4) ultrasound guidance, (5) pain management, and (6) operating room logistics. Based on papers identified in the review, several topics within artificial intelligence were described and summarized: (1) machine learning (including supervised, unsupervised, and reinforcement learning), (2) techniques in artificial intelligence (e.g., classical machine learning, neural networks and deep learning, Bayesian methods), and (3) major applied fields in artificial intelligence.

          The implications of artificial intelligence for the practicing anesthesiologist are discussed as are its limitations and the role of clinicians in further developing artificial intelligence for use in clinical care. Artificial intelligence has the potential to impact the practice of anesthesiology in aspects ranging from perioperative support to critical care delivery to outpatient pain management.

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          Most cited references 104

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          Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
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            Fuzzy sets

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              A logical calculus of the ideas immanent in nervous activity

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                Author and article information

                Journal
                Anesthesiology
                Ovid Technologies (Wolters Kluwer Health)
                0003-3022
                February 01 2020
                February 01 2020
                : 132
                : 2
                : 379-394
                Affiliations
                [1 ]From the Surgical Artificial Intelligence and Innovation Laboratory (D.A.H., E.W., O.M., G.R.) and Department of Anesthesia, Critical Care, and Pain Medicine (L.G.), Massachusetts General Hospital, Boston, Massachusetts; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts (G.R.).
                Article
                10.1097/ALN.0000000000002960
                7643051
                31939856
                © 2020

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