临床麻醉学杂志2024,Vol.40Issue(6) :634-638.DOI:10.12089/jca.2024.06.014

机器学习在麻醉学领域的应用前景

Application prospect of machine learning in field of anesthesiology

胡小义 王迪 纪木火 杨建军
临床麻醉学杂志2024,Vol.40Issue(6) :634-638.DOI:10.12089/jca.2024.06.014

机器学习在麻醉学领域的应用前景

Application prospect of machine learning in field of anesthesiology

胡小义 1王迪 1纪木火 1杨建军2
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作者信息

  • 1. 210000 南京医科大学第二附属医院麻醉科
  • 2. 郑州大学第一附属医院麻醉与围术期医学部
  • 折叠

摘要

机器学习(ML)技术已逐步被用于临床麻醉中,在围术期的应用及研究日益增多.ML在术前可以预警高危事件的发生,辅助困难气道的诊断以及超声显像;在术中可以预测低血压、低氧血症、心搏骤停以及麻醉深度等,帮助实现麻醉的精准和安全控制;在术后可以预测麻醉相关不良结局等.本文总结麻醉学领域常用的ML模型,回顾ML应用于围术期各个阶段的相关研究.ML的应用可改善围术期麻醉管理,有助于预警高危事件的发生,降低麻醉相关风险.

Abstract

Machine learning(ML)technology has been gradually applied in clinical anesthesia,and the application and research in the perioperative period are increasing.ML can warn occurrence of high-risk events,assist the diagnosis of difficult airway and ultrasound imaging in the perioperative period.Intrao-peratively,ML can predict hypotension,hypoxemia,cardiac arrest,and depth of anesthesia to help achieve precise and safe control of anesthesia.Postoperatively,ML can predict anesthesia-related adverse outcomes.This article summarizes the ML models commonly used in the field of anesthesiology,and reviews the rele-vant studies of ML application in all stages of the perioperative period.The application of ML can improve the perioperative anesthesia management,help to warn the occurrence of high-risk events and reduce anes-thesia-related risks.

关键词

机器学习/人工智能/围术期管理/疾病预测/麻醉学

Key words

Machine learning/Artificial intelligence/Perioperative management/Disease predic-tion/Anesthesiology

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出版年

2024
临床麻醉学杂志
中华医学会南京分会

临床麻醉学杂志

CSTPCD北大核心
影响因子:2.225
ISSN:1004-5805
参考文献量38
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