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Classification of Illness01:17

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The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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使用SSWTRT基于机器学习的认知衰退检测:分类性能和决策分析分析.

Yuji Nozaki1, Chihiro Kamohara2,3, Ryota Abe1

  • 1Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Chofu, Japan.

Frontiers in artificial intelligence
|November 14, 2025
PubMed
概括

这项研究表明,机器学习可以使用声音象征文字纹理识别测试 (SSWTRT) 来检测认知能力下降. SSWTRT提供了一种快速,易于使用的方法来识别需要进一步认知评估的个人.

关键词:
这就是 SHAP SHAP 的意思.痴呆症 痴呆症是一种痴呆症.机器学习是机器学习.神经心理测试 神经心理测试声音是象征性的词语,象征性的词语.纹理识别功能 纹理识别功能

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科学领域:

  • 神经学 神经学
  • 认知科学 认知科学
  • 机器学习 机器学习

背景情况:

  • 早期发现认知能力下降对于管理痴呆症进展至关重要.
  • 传统的查工具,如迷你精神状态检查 (MMSE) 是耗时的,需要训练有素的人员.
  • 痴呆症与触觉和视觉感知方面的缺陷有关.

研究的目的:

  • 评估用于识别认知衰退的声音象征文字纹理识别测试 (SSWTRT).
  • 将机器学习应用于SSWTRT响应,用于自动认知状态分类.
  • 评估一种快速,自我管理的认知查工具的可行性.

主要方法:

  • 233名患有异常性正常压力头症 (iNPH) 的参与者完成了SSWTRT.
  • SSWTRT涉及使用日本声音符号词 (SSWs) 来描述从图像中感知到的纹理.
  • 机器学习分类器 (SVM,随机森林,KNN) 被训练来预测MMSE分数,使用SSWTRT反应,年龄和教育.

主要成果:

  • 一个平衡的支持矢量机 (SVM) 模型实现了中等的分类性能 (准确性,精度,回忆,F1,AUC = 0.72).
  • 沙普利添加式解释 (SHAP) 确定了特定的图像纹理 (柔软,粗) 作为关键预测因素.
  • 一些反应表明可能与年龄相关的感官衰退干扰,而不仅仅是认知障碍.

结论:

  • 对SSWTRT反应的机器学习分析可以适度地识别潜在认知衰退的个体.
  • SSWTRT提供了一种非侵入性的,资源高效的选方法.
  • 该框架为开发可扩展的,特定于语言的认知查工具提供了基础,尽管需要进一步验证.