Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model
Year: 2017
Type: conference-paper
Abstract: Alzheimer's disease (AD) is a neurodegenerative disorder with slow onset, which could result in the deterioration of the duration of persistent neurological dysfunction. How to identify the informative longitudinal phenotypic neuroimaging markers and predict cognitive measures are crucial to recognize AD at early stage. Many existing models related imaging measures to cognitive status using regression models, but they did not take full consideration of the interaction between cognitive scores. In this paper, we propose a robust low-rank structured sparse regression method (RLSR) to address this issue. The proposed model simultaneously selects effective features and learns the underlying structure between cognitive scores by utilizing novel mixed structured sparsity inducing norms and low-rank approximation. In addition, an efficient algorithm is derived to solve the proposed non-smooth objective function with proved convergence. Empirical studies on cognitive data of the ADNI cohort demonstrate the superior performance of the proposed method.
Authors: Jie Xu, Cheng Deng, Xinbo Gao, Dinggang Shen, Heng Huang
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
Awards: ABI Innovation: A New Automated Data Integration, Annotations, and Interaction Network Inference System for Analyzing Drosophila Gene Expression, III: Medium: Collaborative Research: Robust Large-Scale Electronic Medical Record Data Mining Framework to Conduct Risk Stratification for Personalized Intervention, Quantifying Brain Abnormality by Multimodality Neuroimage Analysis, G5520316217, BIGDATA: Collaborative Research: IA: Big Imaging-Omics Data Mining Framework for Precision Medicine, G6777872865, G7378543102, III: Small: Robust Large-Scale Data Mining for Knowledge Discovery in Depression Thought Records, SCH: EXP: Collaborative Research: Privacy-Preserving Framework for Publishing Electronic Healthcare Records, G9000211028, G9000243647
OpenAlex ID: W2740958986