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Integration of SNPs-FMRI-methylation data with sparse multi-CCA for schizophrenia study.

, , , and . EMBC, page 3310-3313. IEEE, (2016)

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Brain Functional Connectivity Analysis via Graphical Deep Learning., , , , , , , and . IEEE Trans. Biomed. Eng., 69 (5): 1696-1706 (2022)Joint Bayesian-Incorporating Estimation of Multiple Gaussian Graphical Models to Study Brain Connectivity Development in Adolescence., , , , , , , , and . IEEE Trans. Med. Imaging, 39 (2): 357-365 (2020)Multiscale retrieval of winter wheat water content., , , and . IGARSS, page 4999-5002. IEEE, (2017)Multi-modal Brain Connectivity Study Using Deep Collaborative Learning., , , and . GRAIL/Beyond-MIC@MICCAI, volume 11044 of Lecture Notes in Computer Science, page 66-73. Springer, (2018)Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity., , , , , , and . Medical Image Anal., (December 2023)Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition., , , , , , , , , and 1 other author(s). IEEE Trans. Medical Imaging, 40 (5): 1474-1483 (2021)Integration of SNPs-FMRI-methylation data with sparse multi-CCA for schizophrenia study., , , and . EMBC, page 3310-3313. IEEE, (2016)Vegetation Water Content Estimation for Corn by Means of Inverse Modeling from Simulations of the First-Order Scattering Model., , and . IGARSS, page 7597-7600. IEEE, (2018)A graph deep learning model for the classification of groups with different IQ using resting state fMRI., , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 11317 of SPIE Proceedings, page 113170A. SPIE, (2020)