Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction.

ABSTRACT: Alzheimer's disease (AD) is a serious neurodegenerative condition that affects millions of individuals across the world. As the average age of individuals in the United States and the world increases, the prevalence of AD will continue to grow. To address this public health problem, the research community has developed computational approaches to sift through various aspects of clinical data and uncover their insights, among which one of the most challenging problem is to determine the biological mechanisms that cause AD to develop. To study this problem, in this paper we present a novel Joint Multi-Modal Longitudinal Regression and Classification method and show how it can be used to identify the cognitive status of the participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI

SUBMITTER: Brand L 

PROVIDER: S-EPMC7380699 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature