Multimodal multitask deep learning model for Alzheimer’s disease progression detection based on time series data

Early prediction of Alzheimer’s disease (AD) is crucial for delaying its progression. As a chronic disease, ignoring the temporal dimension of AD data affects the performance of a progression detection and medically unacceptable. Besides, AD patients are represented by heterogeneous, yet complementa...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 412; S. 197 - 215
Hauptverfasser:	El-Sappagh, Shaker, Abuhmed, Tamer, Riazul Islam, S.M., Kwak, Kyung Sup
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 28.10.2020
Schlagworte:	Alzheimer’s disease Deep learning Machine learning Multimodal multitask learning Progression detection Time series data analysis Deep learning Progression detection Alzheimer’s disease Multimodal multitask learning Time series data analysis Machine learning
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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