ArticleEClinicalMedicine2024
Functional imaging derived ADHD biotypes based on deep clustering: a study on personalized medication therapy guidance.
Article in EClinicalMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Physical exercise as a non-pharmacological strategy for ADHD considering neurobiological mechanisms, cognitive benefits, and practical recommendations: a narrative review.European archives of psychiatry and clinical neuroscience · 2026Review
- What we have learned about adolescent mental health and where we are going after a decade with the Adolescent Brain Cognitive Development Study.Developmental cognitive neuroscience · 2026Review
- Abnormal MRI Features in Children with ADHD: A Narrative Review of Large-Scale Studies.Brain sciences · 2026Review
- Applying artificial intelligence in neurodevelopmental disorders management and research.European journal of medical research · 2026Review
- A graph transformer-based foundation model for brain functional connectivity network.Pattern recognition · 2026Article
- Diagnostic utility of biomarkers in progressive supranuclear palsy: toward a biotyping framework.Journal of neurology · 2025Review
- Subtyping Autism Spectrum Disorder With a Population Graph-Based Dual Autoencoder: Revealing Two Distinct Biotypes.CNS neuroscience & therapeutics · 2025Article
- Distinct neuroimaging subtypes of ADHD among adolescents based on semi-supervised learning.Translational psychiatry · 2025Article
- Deep Learning of Brain-Behavior Dimensions Identifies Transdiagnostic Biotypes in Youth with ADHD and Anxiety Disorders.bioRxiv : the preprint server for biology · 2025Article
- Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework.NeuroImage · 2024Article
- Neurodevelopmental Subtypes of Functional Brain Organization in the ABCD Study Using a Rigorous Analytic Framework.bioRxiv : the preprint server for biology · 2024Article
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Authors and funding
12 authors.
Funding
Abstract
Background: Attention deficit hyperactivity disorder (ADHD) is one prevalent neurodevelopmental disorder with childhood onset, however, there is no clear correspondence established between clinical ADHD subtypes and primary medications. Identifying objective and reliable neuroimaging markers for categorizing ADHD biotypes may lead to more individualized, biotype-guided treatment. Methods: Here we proposed a graph convolution network for biological subtype detection (GCN-BSD) using both functional network connectivity (FNC) and non-imaging phenotypic data for ADHD biotype. We applied GCN-BSD to ADHD patients from the ABCD study as the discovery dataset and a validation ADHD dataset with longitudinal medication treatment from Peking University Sixth Hospital. Findings: We identified two biotypes based on 1069 ADHD patients selected from Adolescent Brain and Cognitive Development (ABCD) study, which were validated on independent ADHD adolescents undergoing longitudinal medication treatment (n = 130). Interestingly, in addition to differences in cognitive performance and hyperactivity/impulsivity symptoms, biotype 1 demonstrated a significantly better recovery rate in psychosomatic problems score (p < 0.05, baseline symptom score adjusted) when treated with methylphenidate than with atomoxetine. Interpretation: Our results suggested that such an imaging-driven, biotype-guided approaches hold promise for facilitating personalized treatment of ADHD and exploring possible boundaries through innovative deep learning algorithms to improve medication treatment effectiveness. Funding: Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, the Startup Funds for Talents at Beijing Normal University, China Postdoctoral Science Foundation, and the National Institutes of Health.
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