公共卫生 公共卫生
Huijing Zheng1,2,3,4,5, Jeanine Cheng1, Ho Ko1,2,3,4,5
1Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, Hong Kong.
一个新的数字查工具,数字化综合目标-主体 (DCOS) 认知查工具,显示出对轻度神经认知障碍 (NCD) 的早期检测有希望. 这种由人工智能驱动的工具分析口语,以敏感和准确地识别认知障碍.
科学领域:
- 神经学 神经学
- 人工智能的人工智能
- 数字健康数字健康
背景情况:
- 早期发现轻度神经认知障碍 (NCD) 对于及时干预至关重要.
- 通过早期诊断,可以预防严重神经认知障碍的进展.
- 这项研究的重点是开发用于轻度NCD检测的数字查工具.
研究的目的:
- 开发一种敏感而简单的数字化查工具,用于轻度的NCD.
- 利用人工智能来捕捉和解释口语.
- 为了能够在进展之前早期检测轻度的NCD.
主要方法:
- 开发了基于DSM-5标准的数字化综合目标-主体 (DCOS) 认知查工具.
- 在两个独立的队列 (n=977和n=127) 上验证了该工具.
- 从现有的认知评估中使用ROC分析选择的DCOS项目,重点是口语领域.
主要成果:
- 该DCOS工具包括六个项目 (三个主观,三个客观),具有高诊断准确性 (验证时AUC=0.87).
- 与确定的痴呆症8 (AD8) 相比,DCOS表现优越,准确度与HK MoCA-5min.com相比相当.
- 该工具实现了88%的灵敏度和69%的特异性,显示了数字化的可行性.
结论:
- DCOS是一种新的查工具,用于评估轻度NCD的主观和客观认知领域.
- 它的简短的施用时间 (<5分钟) 使其适合于初级医疗保健机构.
- 未来在数字平台上与人工智能的整合将提高大规模的实用性.
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