Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer’s Disease Using Multimodal Imaging Genetics

Zhou, Rong; Zhou, Houliang; Chen, Brian Y.; Shen, Li; Zhang, Yu; He, Lifang

doi:10.1007/978-3-031-43895-0_64

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

customersupport@researchsolutions.com

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

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

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.

Attentive Deep Canonical Correlation Analysis for Diagnosing Alzheimer’s Disease Using Multimodal Imaging Genetics

Cited by 5 publications

References 24 publications

DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data

DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data

Unified Multi-modal Learning for Any Modality Combinations in Alzheimer’s Disease Diagnosis

Interpretable Graph Convolutional Network for Alzheimer’s Disease Diagnosis using Multi-Modal Imaging Genetics

Contact Info

Product

Resources

About