Work

Hyperbolic Space Sparse Coding with Its Application on Prediction of Alzheimer’s Disease in Mild Cognitive Impairment

Year: 2016

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-319-46720-7_38

Authors: Jie Zhang, Jie Shi, Cynthia Stonnington, Qingyang Li, Boris A. Gutman, Kewei Chen, Eric M. Reiman, Richard Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang

Institutions: Arizona State University, Mayo Clinic in Arizona, University of Southern California, Banner - University Medical Center Phoenix, Banner Alzheimer’s Institute, University of Michigan

Language: English

Topic: Dementia and Cognitive Impairment Research

Subfield: Psychiatry and Mental health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering

Awards: MRI Biomarker Discovery for Preclinical Alzheimers Disease with Geometry Methods, Michigan Alzheimer's Disease Core Center, Empowering Diffusion MRI Measures by Integrating White and Grey Matter Morphology, Brain Imaging, APOE & the Preclinical Course of Alzheimer's Disease, ENIGMA Center for Worldwide Medicine, Imaging & Genomics, Arizona Alzheimer's Disease Core Center, Growth factors, neuroinflammation, exercise, and brain integrity, Multi-Source Sparse Learning to Identify MCI and Predict Decline

OpenAlex ID: W2526850289

FWCI: 11.52

Cites: 14

Cited by: 21

Related to: 10