ArticleHuman brain mapping2019
Enhancing the representation of functional connectivity networks by fusing multi-view information for autism spectrum disorder diagnosis.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 4 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The diagnosis of ASD with MRI: a systematic review and meta-analysis.Translational psychiatry · 2024Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- rs-fMRI and machine learning for ASD diagnosis: a systematic review and meta-analysis.Scientific reports · 2022Pooled it
- Somatosensory Deficits After Stroke: Insights From MRI Studies.Frontiers in neurology · 2022Pooled it
- Identification of Major Depressive Disorder Using Multiple Functional Connection Patterns.CNS neuroscience & therapeutics · 2026Article
- Temporal and spatial variability of large-scale dynamic brain networks in ASD.European child & adolescent psychiatry · 2025Article
- A signature combining brain functional connectivity with executive and motor function for general cognitive decline in Parkinson's disease.Frontiers in neurology · 2025Article
- Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.BMC medicine · 2023Article
- Role of Artificial Intelligence for Autism Diagnosis Using DTI and fMRI: A Survey.Biomedicines · 2023Article
- Fusing Multiview Functional Brain Networks by Joint Embedding for Brain Disease Identification.Journal of personalized medicine · 2023Article
- A Similarity Measure-Based Approach Using RS-fMRI Data for Autism Spectrum Disorder Diagnosis.Diagnostics (Basel, Switzerland) · 2023Article
- Multi-classifier fusion based on belief-value for the diagnosis of autism spectrum disorder.Frontiers in human neuroscience · 2023Article
- Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning.Scientific reports · 2022Article
- A Multiview Deep Learning Method for Brain Functional Connectivity Classification.Computational intelligence and neuroscience · 2022Article
- Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review.Frontiers in molecular neuroscience · 2022Review
- Identification of Pathogenetic Brain RegionsFrontiers in neuroscience · 2022Article
- Brain imaging-based machine learning in autism spectrum disorder: methods and applications.Journal of neuroscience methods · 2021Review
- Mitochondrial dysfunction: A hidden trigger of autism?Genes & diseases · 2021Review
- Brain functional connectivity analysis based on multi-graph fusion.Medical image analysis · 2021Article
- A Novel Unit-Based Personalized Fingerprint Feature Selection Strategy for Dynamic Functional Connectivity Networks.Frontiers in neuroscience · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Functional connectivity network provides novel insights on how distributed brain regions are functionally integrated, and its deviations from healthy brain have recently been employed to identify biomarkers for neuropsychiatric disorders. However, most of brain network analysis methods utilized features extracted only from one functional connectivity network for brain disease detection and cannot provide a comprehensive representation on the subtle disruptions of brain functional organization induced by neuropsychiatric disorders. Inspired by the principles of multi-view learning which utilizes information from multiple views to enhance object representation, we propose a novel multiple network based framework to enhance the representation of functional connectivity networks by fusing the common and complementary information conveyed in multiple networks. Specifically, four functional connectivity networks corresponding to the four adjacent values of regularization parameter are generated via a sparse regression model with group constraint ( l
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.