Dual cross-attention fusion of sMRI and rs-fMRI data achieves 84.71% accuracy in MDD detection on the REST-meta-MDD dataset, outperforming concatenation on functional atlases.
Classification of major depressive disorder using an attention-guided unified deep convolutional neural network and individual structural covariance network
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection
Dual cross-attention fusion of sMRI and rs-fMRI data achieves 84.71% accuracy in MDD detection on the REST-meta-MDD dataset, outperforming concatenation on functional atlases.