Early Detection of Alzheimer’s Disease Using Magnetic Resonance Imaging: A Novel Approach Combining Convolutional Neural Networks and Ensemble Learning

• Published in: Frontiers in neuroscience Vol. 14; p. 259
• Main Authors: Pan, Dan, Zeng, An, Jia, Longfei, Huang, Yin, Frizzell, Tory, Song, Xiaowei
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 13.05.2020; Frontiers Media S.A
• Subjects: Alzheimer's disease; Brain; Brain slice preparation; Classification; Cognitive ability; convolutional neural networks; Datasets; Deep learning; ensemble learning; Limbic system; Machine learning; Magnetic resonance imaging; mild cognitive impairment; MRI biomarkers; Neural networks; Neurodegenerative diseases; Neuroimaging; Neuroscience; Support vector machines; Temporal lobe; ensemble learning; magnetic resonance imaging; Alzheimer’s disease; mild cognitive impairment; convolutional neural networks; MCI-to-AD conversion; MRI biomarkers; Alzheimer’s Disease Neuroimaging Initiative

Early detection is critical for effective management of Alzheimer's disease (AD) and screening for mild cognitive impairment (MCI) is common practice. Among several deep-learning techniques that have been applied to assessing structural brain changes on magnetic resonance imaging (MRI), convolu...