Sparse multiway canonical correlation analysis for multimodal stroke recovery data

This study aims to uncover important biomarkers and stroke recovery patterns based on physiological changes by developing two sparse CCA methods for multiple datasets. In analyzing the pig stroke data, we apply the proposed sparse CCA methods along with dimension reduction techniques, interpret the recovery patterns, and identify influential variables in recovery. Please click on the following link to read more: https://pubmed.ncbi.nlm.nih.gov/38368275/.