Results 91 to 100 of about 8,038,825 (297)

Metro Traffic Flow Prediction via Knowledge Graph and Spatiotemporal Graph Neural Network

Journal of Advanced Transportation, 2022
Existing traffic flow prediction methods generally only consider the spatiotemporal characteristics of traffic flow. However, in addition to the spatiotemporal characteristics, the interference of various external factors needs to be considered in ...
Shun Wang, Yimei Lv, Yuan Peng, Xinglin Piao, Yong Zhang   +4 more
doaj   +1 more source

Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad, Pouya Metanat, Michael Thomas, Luke W. Bonham, Tyson Lam, Mehmet Kurt, Hong Nguyen, Tara Ellingson, Mauro Zucchelli, Stefano Casagranda, Quin Lu, Andreas M. Rauschecker, Leo Sugrue, Luis E. Savastano, Christopher P. Hess, Kamalini Ranasinghe, S. Andrew Josephson, Bruce L. Miller, Jennifer S. Yokoyama, Gil D. Rabinovici, Peter A. Ljubenkov, Lawren VandeVrede, Kambiz Nael   +22 more
wiley   +1 more source

Deep graph representation learning: methods, applications, and challenges

大数据
Graph representation learning has emerged as a crucial research area in recent years, aiming to generate vector representations that accurately capture the structure and features of graphs. These vectors play a vital role in downstream tasks such as node
ZHANG Xulong, QU Xiaoyang, XIAO Chunguang, WANG Jianzong   +3 more
doaj   +2 more sources

Nonlinear Subspace Clustering via Adaptive Graph Regularized Autoencoder

IEEE Access, 2019
Most existing subspace clustering methods focus on learning a meaningful (e.g., sparse or low-rank) representation of the data. However, they have the following two problems which greatly limit the performance: 1) They neglect the intrinsic local ...
Qiang Ji, Yanfeng Sun, Junbin Gao, Yongli Hu, Baocai Yin   +4 more
doaj   +1 more source

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source

Reserves, Injury Severity, and Outcomes in Traumatic Brain Injury: A CENTER‐TBI Observational Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Reserve refers to the brain's ability to maintain function after an injury and strongly relates to traumatic brain injury (TBI) outcomes. This study examined (1) whether associations between pre‐injury reserve proxies and outcomes differed across injury severity categories, and (2) whether the impact of injury severity varied across ...
Natascha Ekdahl, Marika C. Möller, Lindsay Wilson, Anne Vik, Toril Skandsen, Jonas Stenberg, CENTER‐TBI participants and investigators   +6 more
wiley   +1 more source

Graph Representation Learning for Wireless Communications

, 2022
Wireless networks are inherently graph-structured, which can be utilized in graph representation learning to solve complex wireless network optimization problems.
Rajatheva, Nandana, Ranasinghe, Vismika, Mohsenivatani, Maryam, Latva-Aho, Matti, Ali, Samad   +4 more
core  

Exploring the power of text-rich graph representation learning [PDF]

, 2023
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo termsThe student, Qi Zhu, accepted the attached license on 2023-11-20 at 23:27.The student, Qi Zhu, submitted this
Zhu, Qi
core  

On the Interpretability and Evaluation of Graph Representation Learning

CoRR, 2019
With the rising interest in graph representation learning, a variety of approaches have been proposed to effectively capture a graph's properties. While these approaches have improved performance in graph machine learning tasks compared to traditional graph techniques, they are still perceived as techniques with limited insight into the information ...
Antonia Gogoglou, C. Bayan Bruss, Keegan E. Hines   +2 more
openaire   +3 more sources

A Return to Normality: A Descriptive Qualitative Interview Study Exploring the Patient Experience of Gout Flare Resolution

Arthritis Care &Research, EarlyView.
Objective Although the definition of a gout flare is well established, the state of gout flare resolution has not yet been defined. This study aimed to explore patients’ experiences and perceptions of gout flare resolution. Methods Semistructured interviews were conducted with 24 people with gout, guided by open‐ended questions exploring their ...
Sarah Stewart, Anne Horne, Angelo Gaffo, Lisa K. Stamp, N. Lawrence Edwards, Nicola Dalbeth   +5 more
wiley   +1 more source