Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms

M Cao, E Martin, X Li - Translational Psychiatry, 2023 - nature.com
Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous
neurodevelopmental disorder in children and has a high chance of persisting in adulthood …

Exploring characteristic features of attention-deficit/hyperactivity disorder: findings from multi-modal MRI and candidate genetic data

JH Yoo, JI Kim, BN Kim, B Jeong - Brain Imaging and Behavior, 2020 - Springer
The current study examined whether machine learning features best distinguishing attention-
deficit/hyperactivity disorder (ADHD) from typically developing children (TDC) can explain …

Evaluation of pattern recognition and feature extraction methods in ADHD prediction

JR Sato, MQ Hoexter, A Fujita… - Frontiers in systems …, 2012 - frontiersin.org
Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, being
one of the most prevalent psychiatric disorders in childhood. The neural substrates …

Toward precision medicine in ADHD

J Buitelaar, S Bölte, D Brandeis, A Caye… - Frontiers in behavioral …, 2022 - frontiersin.org
Attention-Deficit Hyperactivity Disorder (ADHD) is a complex and heterogeneous
neurodevelopmental condition for which curative treatments are lacking. Whilst …

Computational psychiatry of ADHD: neural gain impairments across Marrian levels of analysis

TU Hauser, VG Fiore, M Moutoussis, RJ Dolan - Trends in neurosciences, 2016 - cell.com
Attention-deficit hyperactivity disorder (ADHD), one of the most common psychiatric
disorders, is characterised by unstable response patterns across multiple cognitive domains …

Predicting the course of ADHD symptoms through the integration of childhood genomic, neural, and cognitive features

G Sudre, W Sharp, P Kundzicz, M Bouyssi-Kobar… - Molecular …, 2021 - nature.com
Childhood attention deficit hyperactivity disorder (ADHD) shows a highly variable course
with age: some individuals show improving, others stable or worsening symptoms. The …

Toward a revised nosology for attention-deficit/hyperactivity disorder heterogeneity

JT Nigg, SL Karalunas, E Feczko, DA Fair - Biological Psychiatry: Cognitive …, 2020 - Elsevier
Attention-deficit/hyperactivity disorder (ADHD) is among the many syndromes in the
psychiatric nosology for which etiological signal and clinical prediction are weak. Reducing …

Classification accuracy of neuroimaging biomarkers in attention-deficit/hyperactivity disorder: effects of sample size and circular analysis

AA Pulini, WT Kerr, SK Loo, A Lenartowicz - … : Cognitive Neuroscience and …, 2019 - Elsevier
Background Motivated by an inconsistency between reports of high diagnosis-classification
accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this …

Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study

MM Owens, N Allgaier, S Hahn, DK Yuan… - Translational …, 2021 - nature.com
Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits,
including poor working memory and difficulty inhibiting undesirable behaviors that cause …

Insights into multimodal imaging classification of ADHD

JB Colby, JD Rudie, JA Brown, PK Douglas… - Frontiers in systems …, 2012 - frontiersin.org
Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by
clinicians via subjective ADHD-specific behavioral instruments and by reports from the …