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Updated: Jan 7, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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多重回归分析的预测准确性分为四组,基于决策树分析的入学引擎FIM

Makoto Tokunaga1, Katsuhiko Sannomiya2

  • 1Department of Rehabilitation Medicine, Kumamoto Kinoh Hospital, Kumamoto, Japan.

Japanese journal of comprehensive rehabilitation science
|December 29, 2025
PubMed
概括

使用决策树分析对患者进行分层,显著提高了中风康复中功能独立度量 (FIM) 评分的预测准确性. 这种方法增强了回归模型,以便更好地预测患者的结果.

关键词:
功能独立性措施 功能独立性措施决策树的分析多重回归分析多重回归分析预测的准确性 预测的准确性分层分层是分层的分层.

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