The Dynamical Biomarkers in Functional Connectivity of Autism Spectrum Disorder Based on Dynamic Graph Embedding-Reference-Cited by-同舟云学术

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The Dynamical Biomarkers in Functional Connectivity of Autism Spectrum Disorder Based on Dynamic Graph Embedding

Published:2023-12-07 Issue: Volume: Page:
ISSN:1913-2751
Container-title:Interdisciplinary Sciences: Computational Life Sciences
language:en
Short-container-title:Interdiscip Sci Comput Life Sci

Author:

Liu Yanting,Wang Hao,Ding Yanrui^ORCID

Funder

National Natural Science Foundation of China

the Postgraduate Research & Practice Innovation Program of Jiangsu Province

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Computer Science Applications,General Biochemistry, Genetics and Molecular Biology

Link

https://link.springer.com/content/pdf/10.1007/s12539-023-00592-w.pdf

Reference53 articles.

1. Bahathiq RA, Banjar H, Bamaga AK et al (2022) Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: promising but challenging. Front Neuroinform 16:949926. https://doi.org/10.3389/fninf.2022.949926

2. Kaur P, Kaur A (2023) Review of progress in diagnostic studies of autism spectrum disorder using neuroimaging. Interdiscip Sci 15(1):111–130. https://doi.org/10.1007/s12539-022-00548-6

3. Maenner MJ, Warren Z, Williams AR et al (2023) Prevalence and characteristics of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2020. MMWR Surveill Summ 72(2):1–14

4. Feng W, Liu G, Zeng K et al (2022) A review of methods for classification and recognition of ASD using fMRI data. J Neurosci Methods 368:109456. https://doi.org/10.1016/j.jneumeth.2021.109456

5. Reiter MA, Jahedi A, Jac Fredo AR et al (2021) Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity. Neural Comput Appl 33(8):3299–3310. https://doi.org/10.1007/s00521-020-05193-y

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