Cargando…

Predicting COVID-19 positivity and hospitalization with multi-scale graph neural networks

The pandemic of COVID-19 is undoubtedly one of the biggest challenges for modern healthcare. In order to analyze the spatio-temporal aspects of the spread of COVID-19, technology has helped us to track, identify and store information regarding positivity and hospitalization, across different levels...

Descripción completa

Detalles Bibliográficos
Autores principales:	Skianis, Konstantinos, Nikolentzos, Giannis, Gallix, Benoit, Thiebaut, Rodolphe, Exarchakis, Georgios
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10066232/ https://www.ncbi.nlm.nih.gov/pubmed/37002271 http://dx.doi.org/10.1038/s41598-023-31222-6

Ejemplares similares

Synthetic electronic health records generated with variational graph autoencoders
por: Nikolentzos, Giannis, et al.
Publicado: (2023)

DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction
por: You, Ronghui, et al.
Publicado: (2021)

Polymer Informatics at Scale with Multitask Graph Neural Networks
por: Gurnani, Rishi, et al.
Publicado: (2023)

Graph neural network and multi-data heterogeneous networks for microbe-disease prediction
por: Gong, Houwu, et al.
Publicado: (2022)

Multi-Scale Aggregation Graph Neural Networks Based on Feature Similarity for Semi-Supervised Learning
por: Zhang, Xun, et al.
Publicado: (2021)

Multi-Particle Reconstruction with Dynamic Graph Neural Networks
por: Qasim, Shah Rukh
Publicado: (2023)

MSGNN-DTA: Multi-Scale Topological Feature Fusion Based on Graph Neural Networks for Drug–Target Binding Affinity Prediction
por: Wang, Shudong, et al.
Publicado: (2023)

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches
por: Crichton, Gamal, et al.
Publicado: (2018)

Graph Neural Networks for Parkinson’s Disease Monitoring and Alerting
por: Zafeiropoulos, Nikolaos, et al.
Publicado: (2023)

Highly accurate and large-scale collision cross sections prediction with graph neural networks
por: Guo, Renfeng, et al.
Publicado: (2023)

MDGNN: Microbial Drug Prediction Based on Heterogeneous Multi-Attention Graph Neural Network
por: Pi, Jiangsheng, et al.
Publicado: (2022)

Multi-instance learning of graph neural networks for aqueous pK(a) prediction
por: Xiong, Jiacheng, et al.
Publicado: (2021)

Accurate Prediction of Epigenetic Multi-Targets with Graph Neural Network-Based Feature Extraction
por: Wang, Yishu, et al.
Publicado: (2022)

Multi-Task Time Series Forecasting Based on Graph Neural Networks
por: Han, Xiao, et al.
Publicado: (2023)

Predicting chemical shifts with graph neural networks
por: Yang, Ziyue, et al.
Publicado: (2021)

Equivariant Graph Neural Networks for Toxicity Prediction
por: Cremer, Julian, et al.
Publicado: (2023)

Introduction to graph neural networks
por: Liu, Zhiyuan, et al.
Publicado: (2020)

A class of Fourier integrals based on the electric potential of an elongated dipole
por: Skianis, Georgios Aim
Publicado: (2014)

Multi-type feature fusion based on graph neural network for drug-drug interaction prediction
por: He, Changxiang, et al.
Publicado: (2022)

Dual graph convolutional neural network for predicting chemical networks
por: Harada, Shonosuke, et al.
Publicado: (2020)

Evaluating graph neural networks under graph sampling scenarios
por: Wei, Qiang, et al.
Publicado: (2022)

Evaluating explainability for graph neural networks
por: Agarwal, Chirag, et al.
Publicado: (2023)

Long-distance dependency combined multi-hop graph neural networks for protein–protein interactions prediction
por: Zhong, Wen, et al.
Publicado: (2022)

A deep graph convolutional neural network architecture for graph classification
por: Zhou, Yuchen, et al.
Publicado: (2023)

Inferring Users’ Social Roles with a Multi-Level Graph Neural Network Model
por: Zhang, Chunrui, et al.
Publicado: (2021)

An Integrative Heterogeneous Graph Neural Network–Based Method for Multi-Labeled Drug Repurposing
por: Sadeghi, Shaghayegh, et al.
Publicado: (2022)

Multi-channel EEG emotion recognition through residual graph attention neural network
por: Chao, Hao, et al.
Publicado: (2023)

MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction
por: Huang, Xiaohui, et al.
Publicado: (2023)

Predicting lncRNA-protein interactions with bipartite graph embedding and deep graph neural networks
por: Ma, Yuzhou, et al.
Publicado: (2023)

Supervised biological network alignment with graph neural networks
por: Ding, Kerr, et al.
Publicado: (2023)

Accelerating network layouts using graph neural networks
por: Both, Csaba, et al.
Publicado: (2023)

Graph neural network based coarse-grained mapping prediction
por: Li, Zhiheng, et al.
Publicado: (2020)

Prediction of protein–protein interaction using graph neural networks
por: Jha, Kanchan, et al.
Publicado: (2022)

A graph neural network approach for molecule carcinogenicity prediction
por: Fradkin, Philip, et al.
Publicado: (2022)

Attention-Based Graph Neural Network for Molecular Solubility Prediction
por: Ahmad, Waqar, et al.
Publicado: (2023)

Explainable Multilayer Graph Neural Network for cancer gene prediction
por: Chatzianastasis, Michail, et al.
Publicado: (2023)

Auto-GNN: Neural architecture search of graph neural networks
por: Zhou, Kaixiong, et al.
Publicado: (2022)

Early stage NSCLS patients’ prognostic prediction with multi-information using transformer and graph neural network model
por: Lian, Jie, et al.
Publicado: (2022)

GATNNCDA: A Method Based on Graph Attention Network and Multi-Layer Neural Network for Predicting circRNA-Disease Associations
por: Ji, Cunmei, et al.
Publicado: (2021)

Graph Neural Network(GNN) Inference of FPGA
por: Fuad, Kazi Ahmed Asif
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_89qqpgko706ut1cic7v2insrh6