Two-stage deep learning model for Alzheimer’s disease detection and prediction of the mild cognitive impairment time

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by thinking, behavioral and memory impairments. Early prediction of conversion from mild cognitive impairment (MCI) to AD is still a challenging task. No study has been able to predict the exact conversion time of MC...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 34; no. 17; pp. 14487 - 14509
Main Authors:	El-Sappagh, Shaker, Saleh, Hager, Ali, Farman, Amer, Eslam, Abuhmed, Tamer
Format:	Journal Article
Language:	English
Published:	London Springer London 01.09.2022 Springer Nature B.V
Subjects:	Alzheimer's disease Artificial Intelligence Biomarkers Cerebrospinal fluid Classification Cognitive ability Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Conversion Data integration Data Mining and Knowledge Discovery Decision trees Deep learning Image Processing and Computer Vision Impact prediction Impairment Machine learning Medical imaging Model accuracy Multivariate analysis Neuroimaging Original Article Probability and Statistics in Computer Science Regression Support vector machines Deep learning Alzheimer’s disease Time-series data analysis Alzheimer’s progression detection
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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