ReCOGnAIze应用程序可以检测血管认知障碍和轻度认知障碍
Adnan Azam Mohammed1,2, Ashwati Vipin1,2, Yi Jin Leow1,2
1Dementia Research Centre (Singapore), Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Alzheimer's & dementia : the journal of the Alzheimer's Association
|February 13, 2026
概括
一个游戏化的应用程序ReCOGnAIze使用AI准确检测血管认知障碍 (VCI) 和轻度认知障碍 (MCI). 它的性能优于传统的认知测试,为早期检测提供了可扩展的解决方案.
科学领域:
- 人工智能在医学中的应用
- 神经科学是一个神经科学.
- 数字健康数字健康
背景情况:
- 血管认知障碍 (VCI) 是认知能力下降的主要原因,由于各种症状,经常被诊断不足.
- 在轻度认知障碍 (MCI) 阶段早期发现VCI对于及时干预至关重要.
- 目前的诊断方法可能无法完全捕捉VCI的频谱,需要新的方法.
研究的目的:
- 开发和验证ReCOGnAIze,一种基于平板电脑的,游戏化的,可解释的应用程序,用于检测VCI和MCI.
- 与健康对照组相比,评估ReCOGnAIze在识别患有VCI和MCI的个体方面的表现.
- 通过游戏化任务识别与VCI相关的数字生物标志物.
主要方法:
- 这是一项涉及亚洲社区群体的多阶段,横截面研究.
- 开发阶段 (n=200) 和验证阶段 (n=235) 具有全面的神经成像和神经心理学数据.
- 利用基于平板电脑的游戏化任务来收集与认知功能相关的数字特征.
主要成果:
- 在区分VCI (AUC=0.85) 和MCI与认知健康个体 (AUC=0.90) 中,ReCOGnAIze表现出强的表现.
- 发现的关键数字特征包括处理速度和响应时间的变化,与已知的VCI相关的执行功能缺陷一致.
- 在区分MCI与认知健康个体方面,ReCOGnAIze复合评分优于蒙特利尔认知评估 (MoCA) (AUC=0.90对AUC=0.70).
结论:
- ReCOGnAIze是一个可扩展,可解释的AI工具,能够准确检测VCI和MCI.
- 游戏化,基于平板电脑的任务为认知功能提供了可解释的见解.
- ReCOGnAIze为VCI和MCI的早期和准确诊断提供了一个有前途的数字解决方案.
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