A Prospective Study of an Early Prediction Model of Attention Deficit Hyperactivity Disorder Based on Artificial Intelligence

被引：0

作者：

Wang, Gang ^{[1
]}

Li, Wanyue ^{[1
]}

Huang, Shixiong ^{[2
]}

Chen, Zhuoming ^{[1
,3
]}

机构：

[1] Jinan Univ, Affiliated Hosp 1, Guangzhou, Guangdong, Peoples R China

[2] South China Univ Technol, Guangzhou, Guangdong, Peoples R China

[3] Jinan Univ, Affiliated Hosp 1, 613 W Huangpu Ave, Guangzhou 510630, Guangdong, Peoples R China

来源：

JOURNAL OF ATTENTION DISORDERS | 2024年 / 28卷 / 03期

基金：

国家重点研发计划;

关键词：

attention deficit hyperactivity disorder; parent symptom questionnaire; artificial intelligence; rapid screening; prediction model; ADHD;

D O I：

10.1177/10870547231211360

中图分类号：

B844 [发展心理学（人类心理学）];

学科分类号：

040202 ;

摘要：

Objective: To explore the relationship between the Parent Symptom Questionnaire (PSQ) and attention deficit hyperactivity disorder (ADHD) in China, and the application value of PSQ questionnaire. Method: Two hundred two children aged 3 to 14 years were enrolled in this study. Statistical methods were used to screen characteristic factors and explore the relationship between PSQ items and ADHD. Machine learning algorithms were used to evaluate the clinical application value of PSQ in screening ADHD. Results: By Mean-Whitney U test, LASSO regression and decision tree, 44, 24 and 12 items were screened out from PSQ with high correlation with ADHD. Then the above items were classified, and the accuracy reached more than 90%. Moreover, the items of ADHD hyperactivity index of PSQ under artificial intelligence algorithm are different from those of PSQ. Conclusion: There are some differences in the items of hyperactivity index between the PSQ and ADHD in China. The artificial intelligence algorithm model of ADHD children based on PSQ scale has a high accuracy.

引用

页码：302 / 309

页数：8

共 21 条

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