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Updated: Jul 12, 2025

Using Brain Activation nir-HEG/Q-EEG and Execution Measures CPTs in a ADHD Assessment Protocol
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根据使用机器学习的前额功能近红外光谱学对患有多动症的儿童进行分类.

Chan-Mo Yang1,2, Jaeyoung Shin3, Johanna Inhyang Kim4

  • 1Department of Psychiatry, Wonkwang University School of Medicine, Iksan, Korea.

Clinical psychopharmacology and neuroscience : the official scientific journal of the Korean College of Neuropsychopharmacology
|October 20, 2023
PubMed
概括

功能近红外光谱学 (fNIRS) 通过机器学习有效地识别了注意力缺陷多动症 (ADHD) 的儿童. 这种神经成像技术在儿童群体中显示出作为ADHD诊断生物标志物的前景.

关键词:
注意力缺陷障碍与多动症.孩子孩子孩子孩子孩子孩子机器学习 机器学习接近红外光谱学,NIRS

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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....
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