在阿尔茨海默病中,可穿戴设备和人工智能的整合:一个范围审查协议
Wenhao Qi1,2, Yankai Shi1, Shiying Shen1,2
1School of Nursing, Hangzhou Normal University, Hangzhou, China.
PloS one
|September 12, 2025
概括
人工智能 (AI) 和可穿戴设备显示出预测阿尔茨海默病 (AD) 的前景. 本综述系统地评估了使用可穿戴设备进行AD检测的AI模型,重点关注结果和开发过程.
科学领域:
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
- 生物医学工程 生物医学工程
背景情况:
- 全球范围内,阿尔茨海默氏病 (AD) 的发病率正在增加.
- 目前的诊断方法通常依赖于传统的生物标志物.
- 人工智能 (AI) 和可穿戴技术的快速发展提供了新的预测能力.
研究的目的:
- 系统评估基于人工智能的预测模型,利用可穿戴设备进行阿尔茨海默病检测和诊断.
- 专注于这些AI可穿戴系统中的测量结果和模型开发流程.
- 通过解决AI和可穿戴技术在AD研究中不断发展的景观来补充现有的文献.
主要方法:
- 遵守阿克西和奥马利框架和PRISMA-ScR指导方针进行范围审查.
- 在多个数据库 (Web of Science,Cochrane Library,PubMed) 和灰色文献中进行全面的文献搜索.
- 使用预测模型偏差风险评估工具 (PROBAST) 和TRIPOD检查清单进行严格的质量评估.
- 数据提取和叙事合成由两个独立的审稿人.
主要成果:
- 使用可穿戴设备对阿尔茨海默病基于人工智能的预测模型进行系统评估.
- 对测量结果和模型开发流程的分析.
- 确定对数据收集和外部验证策略的关键见解.
结论:
- 该审查提供了支持使用人工智能驱动的预测模型与阿尔茨海默病可穿戴设备的系统证据.
- 结果提供了对这些先进诊断工具的构建和验证的见解.
- 这项研究强调了整合人工智能和可穿戴设备的潜力,以改善AD检测和诊断.
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