no code implementations • 12 Feb 2024 • Ziquan Wei, Tingting Dan, Guorong Wu
Graph learning is crucial in the fields of bioinformatics, social networks, and chemicals.
no code implementations • 22 Jan 2024 • Jaeyoon Sim, Sooyeon Jeon, InJun Choi, Guorong Wu, Won Hwa Kim
As setting different number of hidden layers per node is infeasible, recent works leverage a diffusion kernel to redefine the graph structure and incorporate information from farther nodes.
1 code implementation • 5 Jun 2023 • Md Asadullah Turja, Martin Styner, Guorong Wu
In this work, we apply GraphDMD -- an extension of the DMD for network data -- to extract the dynamic network modes and their temporal characteristics from the fMRI time series in an interpretable manner.
no code implementations • 12 Oct 2022 • Enze Xu, Jingwen Zhang, Jiadi Li, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen
Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by beta-amyloid, pathologic tau, and neurodegeneration.
no code implementations • 22 Jan 2022 • Jingwen Zhang, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen
Background: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-\b{eta} (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.
no code implementations • 7 Mar 2021 • Qing Liu, Defu Yang, Jingwen Zhang, Ziming Wei, Guorong Wu, Minghan Chen
Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimer's disease.
no code implementations • 10 Sep 2020 • Jingwen Zhang, Defu Yang, wei he, Guorong Wu, Minghan Chen
Currently, many studies of Alzheimer's disease (AD) are investigating the neurobiological factors behind the acquisition of beta-amyloid (A), pathologic tau (T), and neurodegeneration ([N]) biomarkers from neuroimages.
no code implementations • 1 Jul 2020 • Jiazhou Chen, Guoqiang Han, Hongmin Cai, Defu Yang, Paul J. Laurienti, Martin Styner, Guorong Wu, Alzheimer's Disease Neuroimaging Initiative ADNI
To that end, we propose a novel connectome harmonic analysis framework to provide enhanced mathematical insights by detecting frequency-based alterations relevant to brain disorders.
no code implementations • 3 Dec 2019 • Xin Ma, Guorong Wu, Won Hwa Kim
As there is significant interest in understanding the altered interactions between different brain regions that lead to neuro-disorders, it is important to develop data-driven methods that work with a population of graph data for traditional prediction tasks.
no code implementations • CVPR 2014 • Gerard Sanroma, Guorong Wu, Yaozong Gao, Dinggang Shen
In this way, we can select the best atlases according to their expected labeling accuracy.
no code implementations • CVPR 2013 • Shihui Ying, Guorong Wu, Qian Wang, Dinggang Shen
Specifically, we first use a graph to model the distribution of all image data sitting on the image manifold, with each node representing an image and each edge representing the geodesic pathway between two nodes (or images).