Classification of Alzheimer’s Disease Based on Abnormal Hippocampal Functional Connectivity and Machine Learning

• Published in: Frontiers in aging neuroscience Vol. 14; p. 754334
• Main Authors: Zhu, Qixiao, Wang, Yonghui, Zhuo, Chuanjun, Xu, Qunxing, Yao, Yuan, Liu, Zhuyun, Li, Yi, Sun, Zhao, Wang, Jian, Lv, Ming, Wu, Qiang, Wang, Dawei
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 22.02.2022; Frontiers Media S.A
• Subjects: Aging; Aging Neuroscience; Algorithms; Alzheimer's disease; Cerebellum; Classification; Cognitive ability; Cortex (cingulate); Cortex (parietal); Differential diagnosis; functional connectivity; Hippocampus; Learning algorithms; Machine learning; Magnetic resonance imaging; Medical ethics; Memory; Neural networks; Neurodegenerative diseases; Older people; Seeds; Statistical analysis; SVM; Thalamus; Volumetric analysis; functional connectivity; SVM; Alzheimer’s disease; hippocampus; classification

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive deterioration of memory and cognition. Mild cognitive impairment (MCI) has been implicated as a prodromal phase of AD. Although abnormal functional connectivity (FC) has been demonstrated in AD and MCI, the cli...