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Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol
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通过使用线性方程,内核方程,项目响应理论和机器学习方法协调CBCL和SDQADHD分数

Miljan Jović1, Maryam Amir Haeri1, Andrew Whitehouse2

  • 1Department of Learning, Data Analytics and Technology, University of Twente, Enschede, Netherlands.

Frontiers in psychology
|July 25, 2024
PubMed
概括

从儿童行为检查清单 (CBCL) 和优点和困难问卷 (SDQ) 中协调ADHD分数对于研究至关重要. 使用项目级数据的回归方法在规模协调方面被证明最有效.

关键词:
更多关于 ADHD ADHD 的文章在此之前,IRT是IRT.数据统一和数据协调.核心等同化等同化线性等价法是指线性等价法.机器学习是机器学习.测试等同化测试等同化测试

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相关概念视频

Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings.