国际麻醉学与复苏杂志   2025, Issue (7): 0-0
    
机器学习在优化围术期麻醉管理中的应用探索
李芳, 刘娟, 许月明, 林红, 王顺宏, 张琼, 夏芸, 康永建1()
1.中国人民解放军陆军第九五八医院(西南医院江北院区)
Application of machine learning in optimizing perioperative anesthesia management
 全文:
摘要:

随着人工智能技术的蓬勃发展,机器学习作为其核心驱动力,正深刻改变着医疗领域的面貌,特别是在围术期麻醉方面展现了前所未有的应用进展。为了深入了解机器学习在围术期麻醉中的应用现状及其创新成果,本文综述了机器学习在多个围术期麻醉管理中的最新应用,包括术前风险的精准评估、气道管理的智能化辅助、区域麻醉的精准定位,以及决策支持系统的智能化升级。同时,也审视了机器学习在该领域应用时面临的局限性和挑战,以期为未来研究与应用提供新的思路与方向。

关键词: 机器学习;围术期;麻醉管理;应用进展;综述
Abstract:

With the vigorous development of artificial intelligence technology, machine learning, as its core driving force, is profoundly changing the face of the medical field, especially in the perioperative anesthesia has shown unprecedented application progress. In order to further understand the application status and innovation achievements of machine learning in peri- operative anesthesia, this paper reviews the latest applications of machine learning in multiple perioperative procedures, including accurate assessment of preoperative risk, intelligent assistance of airway management, accurate positioning of regional anesthesia, and intelligent upgrade of decision support system. At the same time, it also examines the limitations and challenges faced by machine learning in the application of this field, in order to provide new ideas and directions for future research and application.

Key words: machine learning; perioperative; anesthesia management; application progress; review