在神经退行性疾病中对认知的数字评估:一种基于数据的方法,利用人工智能
David J Libon1,2, Rod Swenson3, Catherine C Price4
1Department of Geriatrics and Gerontology, New Jersey Institute for Successful Aging, Rowan-Virtua School of Osteopathic Medicine, Glassboro, NJ, United States.
Frontiers in psychology
|July 22, 2024
概括
这种人工智能辅助的数字工具快速评估神经认知功能,用于早期检测神经退行性疾病. 它精确地分类患者,反映传统方法,仅在10分钟内.
科学领域:
- 神经科学是一个神经科学.
- 人工智能在医学中的应用
- 数字健康数字健康
背景情况:
- 新出现的神经退行性疾病需要快速可靠的神经心理评估.
- 传统方法耗时,可能无法有效地捕捉微妙的认知变化.
- 需要可访问的远程评估工具来进行早期检测.
研究的目的:
- 开发和验证一个人工智能辅助的,数字管理的神经心理学协议.
- 评估与新出现的神经退行性疾病相关的神经认知结构.
- 在大约10分钟内实现远程管理.
主要方法:
- 开发了一个数字协议,包括口头学习测试,数字跨度向后测试和口头流利测试.
- 在门诊护理/记忆诊所给77名患者使用该协议.
- 利用核心指标的集群分析和分析的错误/流程变量进行分类.
主要成果:
- 集群分析成功地将参与者分为认知能力不受损害的,无记忆性MCI,无执行性MCI和痴呆症组.
- 错误和过程变量在操作上定义了记忆丧失和执行功能障碍的关键特征.
- 数字协议与传统的综合评估达成90%以上的一致性,并与纸质/笔测量显示出强大的相关性.
结论:
- 人工智能辅助的数字协议准确地识别了类似于标准测试的认知障碍模式.
- 它可以有效和全面地检测早期神经退行性疾病的微妙迹象.
- 该工具为神经心理评估提供了一个快速,可靠和远程解决方案.
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