数字健康技术和人工智能算法的COPD应用:系统性审查
Zhenli Chen1, Jie Hao1, Haixia Sun1
1Institute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
BMC medical informatics and decision making
|February 13, 2025
概括
人工智能 (AI) 和数字健康技术 (DHT) 正在彻底改变慢性阻塞性肺病 (COPD) 管理. 机器学习模型显示了通过各种数据分析改善COPD预测,诊断和患者监测的重大前景.
科学领域:
- 数字健康数字健康
- 人工智能的人工智能
- 肺部病理学 肺部病理学
背景情况:
- 慢性阻塞性肺病 (COPD) 是全球健康的重大负担.
- 数字健康技术 (DHT) 和人工智能 (AI) 为提高COPD护理提供了新的途径.
- 本综述系统地检查了用于COPD管理的DHT中的AI应用.
研究的目的:
- 通过DHTs探索COPD管理中使用的数据类型.
- 为了识别应用到COPD数据的AI算法.
- 在COPD文献中确定AI的关键应用领域.
主要方法:
- 在PubMed和Web of Science进行系统搜索,截至2024年12月.
- 包含针对COPD的AI和DHT的原始研究;不包括评论.
- 两个独立的审查员选并选择了研究.
主要成果:
- 41项研究符合纳入标准,分析了各种数据 (临床,患者报告,环境).
- 机器学习 (ML) 在34项研究中使用,深度学习 (DL) 在16项研究中使用;常见的模型包括SVM,增强,DNN,CNN.
- 主要应用:查/诊断 (10),恶化预测 (22),患者监测 (9),有希望的疾病进展预测.
结论:
- 人工智能和DHT显示出改善COPD管理的广泛潜力.
- 机器学习模型在增强COPD数字健康解决方案方面特别有前途.
- 未来的研究应该优先考虑全球合作,成本效益,数据共享,AI可解释性和临床验证.
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