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

Joint High-Order Multi-Task Feature Learning to Predict the Progression of Alzheimer's Disease. Med Image Comput Comput Assist Interv. 2018 Sep;11070:555-562 Authors: Brand L, Wang H, Huang H, Risacher S, Saykin A, Shen L, ADNI 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. PMID: 31179446 [PubMed - in process]
Source: MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention - Category: Radiology Tags: Med Image Comput Comput Assist Interv Source Type: research