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Task integration for connectome-based prediction via canonical correlation analysis., , , и . ISBI, стр. 87-91. IEEE, (2018)Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models., , , и . MICCAI (3), том 11072 из Lecture Notes in Computer Science, стр. 349-356. Springer, (2018)Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity., , , , , , и . NeuroImage, (2022)Associations among Household and Neighborhood Socioeconomic Disadvantages, Resting-state Frontoamygdala Connectivity, and Internalizing Symptoms in Youth., , , , , , , , , и 2 other автор(ы). J. Cogn. Neurosci., 34 (10): 1810-1841 (2022)There is no single functional atlas even for a single individual: Functional parcel definitions change with task., , , , , и . NeuroImage, (2020)Ten simple rules for predictive modeling of individual differences in neuroimaging., , , , , , , , , и 3 other автор(ы). NeuroImage, (2019)Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals., , , , , , , , и . J. Cogn. Neurosci., 32 (2): 241-255 (2020)Connectome-based machine learning models are vulnerable to subtle data manipulations., , , , , , , , и . Patterns, 4 (7): 100756 (июля 2023)Combining multiple connectomes improves predictive modeling of phenotypic measures., , , и . NeuroImage, (2019)