远程人工智能查帕金森病:一种多模式,跨设置验证研究
Md Saiful Islam1,2, Tariq Adnan1,2, Abdelrahman Abdelkader1
1Department of Computer Science, University of Rochester, Rochester, New York, United States.
Research square
|July 18, 2025
概括
一个人工智能工具PARK使用网络摄像头数据远程检测帕金森病 (PD). 它在识别PD方面表现出很高的准确性,为服务不足的人群提供了可访问的查.
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:
- 帕金森病 (PD) 诊断通常依赖于专门的临床评估,这些评估可能无法获得.
- 需要远程查工具来改善早期检测和可访问性.
研究的目的:
- 评估PARK的性能和可用性,这是一个基于Web的AI工具,用于远程查帕金森病.
- 评估PARK在不同人群和环境中的准确性和通用性.
主要方法:
- 利用了1865名参与者的语音,面部表情和运动任务的视频和音频录音.
- 在独立测试集 (n=389) 上训练并验证了AI模型,并与运动障碍专家进行了性能比较.
- 进行可用性研究以评估参与者的满意度和偏好.
主要成果:
- 在对患有PD和没有PD的个体进行分类时,PARK获得了高准确度 (80.2%-80.6%) 和AUROC (0.85-0.87).
- 与临床专家表现出强烈的共识,并且在人口学子组中得到很好的概括.
- 可用性研究报告了参与者的高满意度和偏好远程查.
结论:
- 帕克显示出作为一种可访问,可扩展和临床一致的工具,用于远程识别帕金森病的潜力.
- 该工具可以支持早期检测,特别是在传统医疗保健服务有限的地方.
- 人工智能驱动的远程查提供了一个有希望的方法来克服神经疾病的医疗保健准入障碍.
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