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Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H. Staib, Pamela E. Ventola, James S. Duncan
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Li, X., Zhou, Y., Dvornek, N. C., Zhang, M., Gao, S., Zhuang, J., Scheinost, D., Staib, L. H., Ventola, P. E., & Duncan, J. S. (2021). BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Medical Image Analysis, 74, 102233. https://doi.org/10.1016/j.media.2021.102233
Li, Xiaoxiao, et al. "BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis." Medical Image Analysis, vol. 74, 2021, pp. 102233, https://doi.org/10.1016/j.media.2021.102233.
Li, Xiaoxiao, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Siyuan Gao, Juntang Zhuang, Dustin Scheinost, Lawrence H. Staib, Pamela E. Ventola, and James S. Duncan. "BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis." Medical Image Analysis 74 (2021): 102233. https://doi.org/10.1016/j.media.2021.102233.
Li X., Zhou Y., Dvornek N. C. [и др.] BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis // Medical Image Analysis. — 2021. — Vol. 74. — P. 102233. — URL: https://doi.org/10.1016/j.media.2021.102233
@article{li2021braingnn,
title = {{BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis}},
author = {Xiaoxiao Li and Yuan Zhou and Nicha C. Dvornek and Muhan Zhang and Siyuan Gao and Juntang Zhuang and Dustin Scheinost and Lawrence H. Staib and Pamela E. Ventola and James S. Duncan},
journal = {Medical Image Analysis},
year = {2021},
volume = {74},
pages = {102233},
doi = {10.1016/j.media.2021.102233},
url = {https://doi.org/10.1016/j.media.2021.102233}
}TY - JOUR AU - Li, Xiaoxiao AU - Zhou, Yuan AU - Dvornek, Nicha C. AU - Zhang, Muhan AU - Gao, Siyuan AU - Zhuang, Juntang AU - Scheinost, Dustin AU - Staib, Lawrence H. AU - Ventola, Pamela E. AU - Duncan, James S. TI - BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis JO - Medical Image Analysis VL - 74 SP - 102233 PY - 2021 DA - 2021/09/12 DO - 10.1016/j.media.2021.102233 UR - https://doi.org/10.1016/j.media.2021.102233 ER -
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