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Diagnosis of Autism Spectrum Disorder Using Central-Moment Features From Low- and High-Order Dynamic Resting-State Functional Connectivity Networks
The sliding-window-based dynamic functional connectivity networks (D-FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) are effective methods for diagnosing various neurological diseases, including autism spectrum disorder (ASD). However, traditional D-FCNs are low-orde...
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| Pubblicato in: | Front Neurosci |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7198826/ https://ncbi.nlm.nih.gov/pubmed/32410930 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2020.00258 |
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