Constructing a risk screen for attention difficulty in U.S. adults using six machine learning methods

Logistic regression exhibited the highest clinical value in predicting concentration difficulty. These findings provide valuable insights for the recognition, management, and effective interference strategies for concentration difficulty.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2026-01-12
DOI
https://doi.org/10.3389/frai.2025.1704576
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Constructing a risk screen for attention difficulty in U.S. adults using six machine learning methods

Ying Song, Zedan Guo, Li Yi, Yansun Sun
Frontiers in Artificial Intelligence
Dementia and Cognitive Impairment Research
article

Constructing a risk screen for attention difficulty in U.S. adults using six machine learning methods

Ying Song, Zedan Guo, Li Yi, Yansun Sun
article en

Abstract

Logistic regression exhibited the highest clinical value in predicting concentration difficulty. These findings provide valuable insights for the recognition, management, and effective interference strategies for concentration difficulty.

Frontiers in Artificial IntelligenceVol. 8
Peking University Shenzhen Hospital (CN)
National Natural Science Foundation of China, Peking University, Shenzhen Science and Technology Innovation Program
Zero hunger
Openalex Percentile: Top 91%
Dementia and Cognitive Impairment Research
DOIOpen Access PDFOpenAlex
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