Results 1 to 10 of about 1,147 (107)

Node Classification Method Based on Hierarchical Hypergraph Neural Network [PDF]

Sensors
Hypergraph neural networks have gained widespread attention due to their effectiveness in handling graph-structured data with complex relationships and multi-dimensional interactions.
Feng Xu, Wanyue Xiong, Zizhu Fan, Licheng Sun   +3 more
doaj   +2 more sources

A hypergraph neural network for prioritizing Alzheimer’s disease risk genes [PDF]

Frontiers in Genetics
Identifying the complex genetic architecture of Alzheimer’s disease (AD) is critical for understanding its pathophysiology. While network-based computational methods assist in this task, they primarily model simple pairwise gene interactions and fail to ...
Meng Ma, Chao Deng, Yan Liu, Qingqing Cao, Fang Liu, Yan Zhang, Yan Zhang   +6 more
doaj   +2 more sources

Coupling Fault Diagnosis of Bearings Based on Hypergraph Neural Network [PDF]

Sensors
Coupling faults that simultaneously occur during the operation of mechanical equipment are widespread. These faults encompass a diverse range of high-order coupling relationships, involving multiple base fault types.
Shenglong Wang, Xiaoxuan Jiao, Bo Jing, Jinxin Pan, Xiangzhen Meng, Yifeng Huang, Shaoting Pei   +6 more
doaj   +2 more sources

A lightweight single-view contrastive learning hypergraph neural network for food–microbe–disease association prediction [PDF]

BMC Bioinformatics
Background Identifying potential associations among food, gut microbiota and disease is fundamental for elucidating interaction mechanisms and advancing personalized healthy dietary strategies. While computational methods have been extensively applied to
Jianqiang Hu, Mingyi Hu, Yangxiang Wu, Songyao Mu, Dahao Huang, Baolong Wang, Yuchen Gao, Shixin Gu, Jinlin Zhu   +8 more
doaj   +2 more sources

A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images [PDF]

Scientific Reports
Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability.
Pooja Govindaraj, Sasikaladevi Natarajan, Pradeepa Sampath, Akilesh Thimma Suresh, Rengarajan Amirtharajan   +4 more
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Multi-Modal Temporal Hypergraph Neural Network for Flotation Condition Recognition [PDF]

Entropy
Efficient flotation beneficiation heavily relies on accurate flotation condition recognition based on monitored froth video. However, the recognition accuracy is hindered by limitations of extracting temporal features from froth videos and establishing ...
Zunguan Fan, Yifan Feng, Kang Wang, Xiaoli Li   +3 more
doaj   +2 more sources

Molecular Merged Hypergraph Neural Network for Explainable Solvation Gibbs Free Energy Prediction [PDF]

Research
Solvation free energies play a fundamental role in various fields of chemistry and biology. Accurately determining the solvation Gibbs free energy ([Formula: see text]) of a molecule in a given solvent requires a deep understanding of the intrinsic ...
Wenjie Du, Shuai Zhang, Zhaohui Cai, Xuqiang Li, Zhiyuan Liu, Junfeng Fang, Jianmin Wang, Xiang Wang, Yang Wang   +8 more
doaj   +2 more sources

Hierarchical Network Organization and Dynamic Perturbation Propagation in Autism Spectrum Disorder: An Integrative Machine Learning and Hypergraph Analysis Reveals Super-Hub Genes and Therapeutic Targets [PDF]

Biomedicines
Background/Objectives: Autism spectrum disorder (ASD) exhibits remarkable genetic heterogeneity involving hundreds of risk genes; however, the mechanism by which these genes organize within biological networks to contribute to disease pathogenesis ...
Larissa Margareta Batrancea, Ömer Akgüller, Mehmet Ali Balcı, Lucian Gaban   +3 more
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Traffic Flow Prediction Based on Hypergraph Spatiotemporal Interaction Network [PDF]

Entropy
To improve the accuracy and stability of short-term traffic flow prediction in complex road networks and address the limitations of existing models in modeling spatiotemporal dependencies, this paper proposes a traffic flow prediction model based on a ...
Wei Cao, Haipeng Jiang, Xinye Wu
doaj   +2 more sources

A model of multi-view contrastive hypergraph learning for predicting circRNA-disease associations [PDF]

Scientific Reports
In recent years, circRNAs have been found to be closely related to a variety of human diseases. In-depth exploration of their potential associations with diseases is of great value for understanding disease mechanisms and auxiliary diagnosis.
Jiaqi Liu, Changqing Yu, Xiujuan Ma, Cheng-Wei Ruan, Lei Wang   +4 more
doaj   +2 more sources