ABSTRACT
Background and Aim: Artificial intelligence plays a crucial role in predicting patient conditions, optimizing drug doses, monitoring clinical status, and providing clinical decision support during anesthesia. This narrative review examines the applications of artificial intelligence in the field of anesthesia.
Materials and Methods: This review article was conducted in 2023 by searching the external database Scopus. PubMed. IEEE Explore. WOS and internal Iran Doc, SID in the period 2019-2024.
Results: Types of artificial intelligence applied in anesthesia include Infuse-O. R system that works with magnetic codes, Stan pump software that reduces the role of expert human resources in the anesthesia process, and machine learning that determines the level of anesthetic drug according to the values and conditions of the input data set. Use neural network algorithms to determine the dose of anesthetic drugs. An LSTM neural network is used to analyze and predict anesthesia performance and to recognize the signal class during anesthesia. 32 convolutional filters in the convolutional neural network, a layer with maximum pooling, a second convolutional layer of 32 filters, a secondary pooling layer, and a fully connected final layer are used.
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Conclusion: Integrating artificial intelligence into anesthesia enhances the quality of medical care, improves diagnostic accuracy, and increases patient safety. However, this integration also presents several challenges, including the need to protect patient privacy, ensure responsible AI decision-making, prevent discrimination, increase the transparency of algorithms, clarify physician responsibility, and address the impact of artificial intelligence on the role of physicians.