1) ICA can extract sparse and independent features from medical imaging data to build predictive models of conditions like brain trauma. 2) MCCA identifies joint patterns across multiple datasets, like functional MRI scans from a simulated driving experiment. 3) Dimension reduction with PCA improves ICA by addressing issues with high dimensionality, enhancing reproducibility of extracted patterns.