目前的技术进步在食障碍查:系统的范围审查.
Duo Wai-Chi Wong1, Jiao Wang1,2, Sophia Ming-Yan Cheung3
1Department of Biomedical Engineering, Faculty of Engineering, Hong Kong Polytechnic University, Hong Kong, China (Hong Kong).
Journal of medical Internet research
|May 5, 2025
概括
人工智能 (AI) 和传感器技术在老年人查失症方面表现有前途. 然而,目前的研究有显著的方法限制,影响现实世界的适用性.
科学领域:
- 生物医学工程 生物医学工程
- 老年学是一门学科.
- 人工智能的人工智能
背景情况:
- 缺食症影响超过50%的老年痴呆症患者,增加死亡风险.
- 可访问,客观和可靠的查工具对于早期检测和管理至关重要.
研究的目的:
- 审查人工智能和基于传感器的技术用于食障碍查的现状.
- 评估这些基于人工智能的工具的性能.
- 评估相关研究的方法质量和严格性.
主要方法:
- 按照PRISMA-ScR指南进行系统范围审查.
- 搜索了CINAHL,Embase,PubMed,科学网. 这是一个很大的问题.
- 包括使用基于传感器的仪器和人工智能用于检测缺食的研究;排除了儿科/婴儿病例.
主要成果:
- 24项研究包括2979名参与者;大多数专注于个人分类.
- 声波和振动信号是主要的模式;多式联络系统显示出更好的性能.
- 广泛的性能变化;在患者选择,索引测试和AI建模中存在重大偏差风险;没有外部验证.
结论:
- 人工智能和基于传感器的技术为远程吞评估提供了潜力.
- 方法上的局限性,包括缺乏外部验证,阻碍了实际应用.
- 未来的研究应该专注于针对复杂的消化障碍病例的模式特定向和多模式系统增强.
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