Integrating Visualised Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction-Reference-Cited by-同舟云学术

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Integrating Visualised Automatic Temporal Relation Graph into Multi-Task Learning for Alzheimer's Disease Progression Prediction

Published:2024-10 Issue:10 Volume:36 Page:5206-5220
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Zhou Menghui¹^ORCID,Wang Xulong²^ORCID,Liu Tong²^ORCID,Yang Yun³^ORCID,Yang Po²^ORCID

Affiliation:

1. Department of Software, Yunnan University, Kunming, China

2. Department of Computer Science, University of Sheffield, Sheffield, U.K.

3. Yunnan Key Laboratory of Software Engineering and the Department of Software, Yunnan University, Kunming, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/69/10679113/10495318.pdf?arnumber=10495318

Reference52 articles.

1. Alzheimers disease facts and figures;Wiley;Alzheimers Dement,2021

2. Identifying the Neuroanatomical Basis of Cognitive Impairment in Alzheimer's Disease by Correlation- and Nonlinearity-Aware Sparse Bayesian Learning

3. Sparse shared structure based multi-task learning for MRI based cognitive performance prediction of Alzheimer’s disease

4. Structured sparsity regularized multiple kernel learning for Alzheimer’s disease diagnosis

5. Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

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