机器学习算法在术后谵妄风险评估中的应用进展

doi:10.20223/j.cnki.1000-8535.2025.01.006

摘要/Abstract

摘要： 近年来,人工智能技术（AI）的发展正在逐渐改变传统的医疗行业,机器学习作为人工智能技术中的主流被越来越多地应用于分析复杂的医学数据,为疾病的诊断、预后风险评估、诊疗决策的制定等方面提供了便利。文章对国内外机器学习算法在术后谵妄中的应用进行综述,以期为术后谵妄预测模型的构建提供新的思路,为临床早期评估术后谵妄提供新的依据。

关键词: 术后谵妄, 机器学习算法, 风险预测模型, 综述

Abstract: In recent years,the development of artificial intelligence（AI）is gradually changing the traditional medical industry．Machine learning,as the mainstream of artificial intelligence technology,is increasingly applied to analyze complex data in medical research．It provides convenience for disease diagnosis,risk assessment and diagnosis and treatment decision making．This paper reviews the application of machine learning algorithms in postoperative delirium at home and abroad,in order to provide a new idea for the construction of postoperative delirium prediction model and a new basis for early clinical evaluation of postoperative delirium．

Key words: postoperative delirium, machine learning alogrithms, risk models, reviews

江竹月, 孙洲华, 张庆庆, 张成欢, 陈雯. 机器学习算法在术后谵妄风险评估中的应用进展[J]. 广州医药, 2025, 56(1): 42-47.

JIANG Zhuyue, SUN Zhouhua, ZHANG Qingqing, ZHANG Chenghuan, CHEN Wen. Progress in the application of machine learning algorithms in the risk assessment of postoperative delirium[J]. Guangzhou Medical Journal, 2025, 56(1): 42-47.

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