Identification of autism subtypes based on wavelet coherence of BOLD FMRI signals using convolutional neural network
The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary cla...
| Main Authors: | Al-Hiyali, M.I., Yahya, N., Faye, I., Hussein, A.F. |
|---|---|
| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.23778 / |
| Published: |
MDPI AG
2021
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111742900&doi=10.3390%2fs21165256&partnerID=40&md5=67977c8dabb4447ccffc68d3415a7878 http://eprints.utp.edu.my/23778/ |
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