ADHD classification by dual subspace learning using resting-state functional connectivity.
As one of the most common neurobehavioral diseases in school-age children, Attention Deficit Hyperactivity Disorder (ADHD) has been increasingly studied in recent years. But it is still a challenge problem to accurately identify ADHD patients from healthy persons. To address this issue, we propose a...
| Publicado en: | Artificial Intelligence in Medicine Vol. 103 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Mar2020
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| Acceso en línea: | Ver este registro en EBSCOhost |