Dynamic coarsened spatio-temporal graph convolutional networks for fMRI classification of addiction-induced sleep disorders.
- DOI
- 10.1088/2057-1976/aea7a0
- Published
- 2026 Sep 15
- Container
- Biomedical physics & engineering express
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1088/2057-1976/aea7a0,
title = {Dynamic coarsened spatio-temporal graph convolutional networks for fMRI classification of addiction-induced sleep disorders.},
author = {Shen J and Meng J and Zeng J and Ye B},
year = {2026},
journal = {Biomedical physics \& engineering express},
doi = {10.1088/2057-1976/aea7a0},
url = {https://doi.org/10.1088/2057-1976/aea7a0}
}RIS
TY - JOUR TI - Dynamic coarsened spatio-temporal graph convolutional networks for fMRI classification of addiction-induced sleep disorders. AU - Shen J AU - Meng J AU - Zeng J AU - Ye B PY - 2026 JO - Biomedical physics & engineering express DO - 10.1088/2057-1976/aea7a0 UR - https://doi.org/10.1088/2057-1976/aea7a0 ER -
APA
J, S., J, M., J, Z., & B, Y. (2026). Dynamic coarsened spatio-temporal graph convolutional networks for fMRI classification of addiction-induced sleep disorders.. Biomedical physics & engineering express. https://doi.org/10.1088/2057-1976/aea7a0
Source records
- pubmed · retrieved 2026-09-26T01:23:01.715Z