Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies

Xiao, Li; Cai, Biao; Qu, Gang; Zhang, Gemeng; Stephen, Julia M.; Wilson, Tony W.; Calhoun, Vince D.; Wang, Yuping

doi:10.1109/tbme.2022.3160447

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

hi@scite.ai

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Distance Correlation-Based Brain Functional Connectivity Estimation and Non-Convex Multi-Task Learning for Developmental fMRI Studies

Cited by 5 publications

References 59 publications

Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI

Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI

Age-related changes in human brain functional connectivity using graph theory and machine learning techniques in resting-state fMRI data

BrainNet with Connectivity Attention for Individualized Predictions Based on Multi-Facet Connections Extracted from Resting-State fMRI Data

Contact Info

Product

Resources

About