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

• Published in: Neurocomputing (Amsterdam) Vol. 412; pp. 197 - 215
• Main Authors: El-Sappagh, Shaker, Abuhmed, Tamer, Riazul Islam, S.M., Kwak, Kyung Sup
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 28.10.2020
• Subjects: 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

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...