An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data - Citegraph

Paper Info

Title
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data

Abstract
•HDLFCA leveraged complementary information between FNC and TCs by combining DNN and C-RNN.•HDLFCA integrates discriminative regions identification and disorder diagnosis into a unified framework.•HDLFCA outperformed 12 alternative models based on single sFNC, TCs or dFNC.•Attention module identified discriminative ICs and improved classification performances.•The most group discriminative ICs provide meaningful biological interpretability.

Year	DOI	Venue
2022	10.1016/j.media.2022.102413	Medical Image Analysis
Keywords	DocType	Volume
Attention mechanism,Deep learning,Brain connectivity and activity,fMRI	Journal	78
ISSN	Citations	PageRank
1361-8415	0	0.34
References	Authors
0	10

Authors (10 rows)

Cited by (0 rows)

References (0 rows)

Name	Order	Citations	PageRank
Min Zhao	1	0	0.34
Weizheng Yan	2	0	0.34
Na Luo	3	0	0.68
Dongmei Zhi	4	0	0.34
Zening Fu	5	0	0.68
Yuhui Du	6	0	0.34
Shan Yu	7	13	5.70
T. Jiang	8	1419	128.59
Vince D Calhoun	9	2769	268.91
Jing Sui	10	0	0.34

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