Work

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer’s Disease

Year: 2018

Type: conference-paper

Source: Lecture notes in computer science

DOI: 10.1007/978-3-030-00928-1_63

Authors: Lodewijk Brand, Hua Wang, Heng Huang, Shannon Risacher, Andrew Saykin, Li Shen, for the ADNI

Institutions: Colorado School of Mines, University of Pittsburgh, Indiana University Indianapolis, University of Pennsylvania

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 Institutes of Health, National Institute on Aging, National Institute of Biomedical Imaging and Bioengineering, U.S. National Library of Medicine

Awards: G1221608705, Indiana Alzheimer Disease Center, Bioinformatics Strategies for Multidimensional Brain Imaging Genetics, G1576357080, G2957681590, G7378543102, Alzheimer's Disease Neuroimaging Initiative (ADNI4), G959842831

OpenAlex ID: W2890184610

FWCI: 12.39

Cites: 16

Cited by: 18

Related to: 10