人工智能在儿童喘恶化预测和管理中的应用:系统性审查
Fatima Mahmoud Osman Mohmed1, Wafa Elrasheed Osman Homaida2, Yousra Bala Babkir Abd Alla2
1General Medicine, Sharourah General Hospital, Sharourah, SAU.
Cureus
|October 20, 2025
概括
人工智能 (AI) 能够有效地预测儿童喘恶化,优于传统方法. 多式联络数据显示最有前途,但偏见和验证等挑战仍然存在于临床整合方面.
科学领域:
- 医疗信息学 医疗信息学
- 儿科肺病学 儿科肺病学
- 医疗保健中的人工智能
背景情况:
- 儿童喘恶化对全球健康构成重大挑战.
- 人工智能 (AI) 提供了改善预测和管理的潜力.
- 目前关于儿童喘人工智能的证据是零碎的.
研究的目的:
- 系统地审查和综合关于人工智能应用在儿童喘恶化预测和管理方面的文献.
- 评估人工智能模型的性能,临床效用和方法质量.
- 确定关键的挑战和未来的研究方向.
主要方法:
- 按照PRISMA 2020指南进行系统审查.
- 搜索了主要的数据库 (PubMed,Scopus,Embase等) 对于从2020年到2025年的研究.
- 通过使用ROBINS-I和Cochrane RoB 2工具评估偏差风险.
主要成果:
- 八项研究表明,人工智能在预测儿科喘恶化方面的有效性超过了传统方法.
- 多模式数据集成产生了优越的模型性能.
- 大多数研究显示偏差风险低,但局限性包括数据偏差和小样本大小.
结论:
- 人工智能显示出预测儿科喘恶化的巨大潜力,特别是使用多式联络数据.
- 解决算法偏差,前性验证和标准化指标对于临床整合至关重要.
- 未来的研究应该专注于公平的模型开发和现实世界的临床影响评估.
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