REVIEW article
Front. Med.
Sec. Intensive Care Medicine and Anesthesiology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1571725
Artificial Intelligence Revolutionizing Anesthesia Management: Advances and Prospects in Intelligent Anesthesia Technology
Provisionally accepted
- 1Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
- 2Dalian University of Technology, Dalian, China
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With the development of artificial intelligence (AI), AI-related technologies are being applied in many fields of medicine. Anesthesia is now widely used in surgery, emergency resuscitation, pain treatment and other fields. However, different from some other common biomedical signals, such as the electrocardiogram (ECG), electroencephalogram (EEG), and some other medical imaging or biomarkers could be easily processed and analyzed by AI-related models, how to collect the relevant data in the anesthesia process is still a challenge, that has led to few current work on combining AI and anesthesia. However, it can be foreseen that the combination of AI and anesthesia will become increasingly important. This paper presents a comprehensive review of anesthesia with AI based methods which have been now used in the preoperative phase, intraoperative phase, and postoperative phase. We first overview some crucial concepts of artificial intelligence, then discuss the related applications of artificial intelligence used in different phases of the anesthesia period, finally, we look forward to the future development of intelligent anesthesia. We hope through this review, we can provide comprehensive and objective guidance in AI-related anesthesia process to help anesthesiologists use more advanced AI techniques to diagnose and treat patients during the anesthesia period.
Keywords: Anesthesia, artificial intelligence, perioperative anesthesia management, machine learning, neural networks
Received: 14 Feb 2025; Accepted: 30 May 2025.
Copyright: © 2025 Cao, Wang, Liu and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yixin Wang, Dalian University of Technology, Dalian, China
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