| Literature DB >> 31179446 |
Lodewijk Brand1, Hua Wang1, Heng Huang2, Shannon Risacher3, Andrew Saykin3, Li Shen3,4.
Abstract
Alzheimer's disease (AD) is a degenerative brain disease that affects millions of people around the world. As populations in the United States and worldwide age, the prevalence of Alzheimer's disease will only increase. In turn, the social and financial costs of AD will create a difficult environment for many families and caregivers across the globe. By combining genetic information, brain scans, and clinical data, gathered over time through the Alzheimer's Disease Neuroimaging Initiative (ADNI), we propose a new Joint High-Order Multi-Modal Multi-Task Feature Learning method to predict the cognitive performance and diagnosis of patients with and without AD.Entities:
Keywords: Alzheimer’s disease; Longitudinal; Multi-modal; Tensor
Mesh:
Year: 2018 PMID: 31179446 PMCID: PMC6553480 DOI: 10.1007/978-3-030-00928-1_63
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv