Brain age prediction using the graph neural network based on resting-state functional MRI in Alzheimer's disease
J Gao, J Liu, Y Xu, D Peng, Z Wang - Frontiers in Neuroscience, 2023 - frontiersin.org
Introduction Alzheimer's disease (AD) is a neurodegenerative disease that significantly
impacts the quality of life of patients and their families. Neuroimaging-driven brain age …
impacts the quality of life of patients and their families. Neuroimaging-driven brain age …
Individual brain parcellation: Review of methods, validations and applications
Individual brains vary greatly in morphology, connectivity and organization. The applicability
of group-level parcellations is limited by the rapid development of precision medicine today …
of group-level parcellations is limited by the rapid development of precision medicine today …
Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size
Structural neuroimaging data have been used to compute an estimate of the biological age
of the brain (brain‐age) which has been associated with other biologically and behaviorally …
of the brain (brain‐age) which has been associated with other biologically and behaviorally …
[HTML][HTML] Beyond network connectivity: A classification approach to brain age prediction with resting-state fMRI
SK Sorooshyari - NeuroImage, 2024 - Elsevier
The brain is a complex, dynamic organ that shows differences in the same subject at various
periods. Understanding how brain activity changes across age as a function of the brain …
periods. Understanding how brain activity changes across age as a function of the brain …
Brain age monotonicity and functional connectivity differences of healthy subjects
SK Sorooshyari - Plos one, 2024 - journals.plos.org
Alterations in the brain's connectivity or the interactions among brain regions have been
studied with the aid of resting state (rs) fMRI data attained from large numbers of healthy …
studied with the aid of resting state (rs) fMRI data attained from large numbers of healthy …
NeuroSynth: MRI-Derived Neuroanatomical Generative Models and Associated Dataset of 18,000 Samples
SS Chintapalli, R Wang, Z Yang, V Tassopoulou… - arXiv preprint arXiv …, 2024 - arxiv.org
Availability of large and diverse medical datasets is often challenged by privacy and data
sharing restrictions. For successful application of machine learning techniques for disease …
sharing restrictions. For successful application of machine learning techniques for disease …
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience
Machine learning (ML) has shown great promise for revolutionizing a number of areas,
including healthcare. However, it is also facing a reproducibility crisis, especially in …
including healthcare. However, it is also facing a reproducibility crisis, especially in …
[HTML][HTML] pNet: A toolbox for personalized functional networks modeling
Personalized functional networks (FNs) derived from functional magnetic resonance
imaging (fMRI) data are useful for characterizing individual variations in the brain functional …
imaging (fMRI) data are useful for characterizing individual variations in the brain functional …
Resting state network connectivity alterations in HIV: Parallels with aging
BJ Lew, MC McCusker, J O'Neill, SH Bares… - Human Brain …, 2023 - Wiley Online Library
The increasing incidence of age‐related comorbidities in people with HIV (PWH) has led to
accelerated aging theories. Functional neuroimaging research, including functional …
accelerated aging theories. Functional neuroimaging research, including functional …