Dynamic and Static Structure–Function Coupling With Machine Learning for the Early Detection of Alzheimer's Disease

ABSTRACT The progression of Alzheimer's disease (AD) involves complex changes in brain structure and function that are driven by their interaction, making structure–function coupling (SFC) a valuable indicator for early detection of AD. Static SFC refers to the overall structure–function intera...

Full description

Saved in:

Bibliographic Details
Published in:	Human brain mapping Vol. 46; no. 5; pp. e70202 - n/a
Main Authors:	Wu, Han, Lu, Yinping, Wang, Luyao, Wu, Jinglong, Liu, Ying, Zhang, Zhilin
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01.04.2025
Subjects:	Aged Aged, 80 and over Alzheimer Disease - diagnosis Alzheimer Disease - diagnostic imaging Alzheimer Disease - physiopathology Alzheimer's disease Biomarkers Brain Cognitive ability Cognitive Dysfunction - diagnosis Cognitive Dysfunction - diagnostic imaging Cognitive Dysfunction - physiopathology Coupling Disease Disease Progression dynamic structure–function coupling Early Diagnosis Education Feature selection Female Functional anatomy Hospitals Humans Learning algorithms Machine Learning Magnetic Resonance Imaging Male Medical imaging Mental disorders Middle Aged Neurodegenerative diseases Neuroimaging Physiology Scanners static structure–function coupling Structure-function relationships Canada Montreal Quebec Canada static structure–function coupling magnetic resonance imaging dynamic structure–function coupling machine learning Alzheimer's disease
ISSN:	1065-9471, 1097-0193, 1097-0193
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!