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Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data.

Abstract：

:Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the early stage using longitudinal data, with each task corresponding to a particular time point. However, the underlying association among different time points in disease progression is still under-explored in previous studies. To this end, we propose a multi-task exclusive relationship learning model to automatically capture the intrinsic relationship among tasks at different time points for estimating clinical measures based on longitudinal imaging data. The proposed method can select the most discriminative features for different tasks and also model the intrinsic relatedness among different time points, by utilizing an exclusive lasso regularization and a relationship induced regularization. Specifically, the exclusive lasso regularization enables partial group structure feature selection among the longitudinal data, while the relationship induced regularization efficiently introduces the relationship information from data to guide knowledge transfer. We further develop an efficient optimization algorithm to solve the proposed objective function. Extensive experiments on both synthetic and real datasets demonstrate the effectiveness of our proposed method. In comparison with several state-of-the-art methods, our proposed method can achieve promising performance for cognitive status prediction and also can help discover disease-related biomarkers.

journal_name

Med Image Anal

journal_title

Medical image analysis

authors

Wang M,Zhang D,Shen D,Liu M

doi

10.1016/j.media.2019.01.007

subject

Has Abstract

pub_date

2019-04-01 00:00:00

pages

111-122

eissn

1361-8415

issn

1361-8423

pii

S1361-8415(19)30012-X

journal_volume

53

pub_type

杂志文章

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