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Updated: Jan 24, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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可解释的人工智能方法通过结合特征选择方法和机器学习分类器来预测抑郁症

Min Gyeong Kim1, Kun Chang Lee2, Kwanho Lee2

  • 1SKKU Business School, Sungkyunkwan University, Seoul, Republic of Korea.

Digital health
|January 23, 2026
PubMed
概括

这项研究将特征选择与可解释AI (XAI) 结合起来,以改进抑郁症预测模型. 关键的非诊断因素,如社会困扰和不愿寻求帮助被确定为重要的预测因素.

关键词:
抑郁症 抑郁症 抑郁症韩国国家心理健康调查.沙普利的添加式扩展 (SHAP)可解释的人工智能 (XAI)功能选择 功能选择机器学习是机器学习.心理健康 心理健康预测模型的预测模型.

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