Work

Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data

Year: 2012

Type: article

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2012.03.059

Authors: Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, Jieping Ye

Institutions: Arizona State University, University of California, Los Angeles

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, University of Pennsylvania, National Institutes of Health, National Institute on Aging, National Institute of Mental Health, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine, National Center for Research Resources

Awards: G104586243, G130320643, UC Davis Alzheimer's Disease Core Center, G1757829149, G179877238, G1909487776, G2627450486, Algorithms to Map Disease &Genetic Effects on the Brain, Novel PDEs for Cortical Mapping and Analysis in Disease, G3642348494, UCLA Alzheimer's Disease Research Center, "MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies", Computational Methods for Expression Image Analysis, A Multidimensional Alzheimer's Disease Brain Atlas, Alzheimer's disease risk analyzed using population imaging genomics, Empowering Personalized Medicine: Integrating Imaging, Genetics, and Biomarkers, Alzheimer's Disease Neuroimaging Initiative, G6644087359, CAREER: Dimensionality Reduction for Multi-Label Classification, Arizona Alzheimer's Disease Core Center, Boston University Alzheimer's Disease Center, Alzheimer's Disease Cooperative Study, III-COR-Small: Beyond Feature Selection and Extraction - An Integrated Framework for High-Dimensional Data of Small Labeled Samples

OpenAlex ID: W2095377654

FWCI: 9.088

Cites: 65

Cited by: 194

Related to: 10