诊断学理论与实践2026，Vol.25Issue(4)：413-418,6.DOI:10.16150/j.1671-2870.2026.04.004
人工智能在慢性阻塞性肺疾病全程管理中的应用
Application of artificial intelligence in comprehensive management of chronic obstructive pulmonary disease:interpretation of GOLD 2026
摘要
Abstract
The 2026 Global Initiative for Chronic Obstructive Lung Disease(GOLD)has,for the first time,inte-grated artificial intelligence(AI)technology into the comprehensive management framework of COPD.AI models encom-pass four major categories:traditional machine learning,deep learning,large foundation models,and generative AI.They demonstrate potential in phenotyping,early warning of acute exacerbations,and prediction of treatment response.AI identi-fies multiple imaging subtypes of emphysema through unsupervised learning,with different subtypes significantly associa-ted with mortality risk and hospitalization risk.Deep learning models outperform traditional tools in long-term and short-term prediction of acute exacerbations,and early warning systems can effectively reduce hospitalization rates.Machine learning models perform well in predicting the effectiveness of inhaled corticosteroids,improving adherence to pulmonary rehabilitation,and predicting the success rate of lung volume reduction surgery.Additionally,AI applications face ethical challenges such as misdiagnosis,algorithmic bias,data privacy,and attribution of responsibility,which need to be addressed through strategies including full-process validation,dynamic informed consent,and fairness assessment.Overall,AI-empowered COPD management drives a paradigm shift from passive treatment to active prevention,yet a balance still needs to be achieved among innovation,evidence,and ethics.关键词
人工智能/慢性阻塞性肺疾病/个性化风险预测Key words
Artificial intelligence/Chronic obstructive pulmonary disease/Personalized risk prediction分类
医药卫生引用本文复制引用
孙娴雯,李庆云..人工智能在慢性阻塞性肺疾病全程管理中的应用[J].诊断学理论与实践,2026,25(4):413-418,6.基金项目
上海市科委(23Y11904400) （23Y11904400）
国家科技部重大专项(2023ZD0506303) （2023ZD0506303）
国家科技部重大专项(2024ZD0536602) （2024ZD0536602）
