Identifying and characterizing different stages toward Alzheimer's disease using ordered core features and machine learning

Identifying and characterizing different stages toward Alzheimer's disease using ordered core features and machine learning

Based on the joint HCPMMP parcellation method we developed before, which divides the cortical brain into 360 regions, the concept of ordered core features (OCF) is first proposed to reveal the functional brain connectivity relationship among different cohorts of Alzheimer's disease (AD), late m...

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Bibliographic Details
Main Authors: Jinhua Sheng, Bocheng Wang, Qiao Zhang, Rougang Zhou, Luyun Wang, Yu Xin
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Heliyon
Subjects:
Alzheimer's disease (AD)
Mild cognitive impairment (MCI)
Machine learning
The area under ROC curve (AUC)
Human connectome project (HCP)
Connectivity network analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844021013906

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http://www.sciencedirect.com/science/article/pii/S2405844021013906

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