MoAGL-SA: a multi-omics adaptive integration method with graph learning and self attention for cancer subtype classification by Lei Cheng, Qian Huang, Zhengqun Zhu, Yanan Li, Shuguang Ge, Longzhen Zhang, Ping Gong

“…First, patient relationship graphs are generated from each omics dataset using graph learning. …”
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PIDQA—Question Answering on Piping and Instrumentation Diagrams by Mohit Gupta, Chialing Wei, Thomas Czerniawski, Ricardo Eiris

“…First, we recognize entities in a P&ID image and organize their relationships to form a base entity graph. Second, this entity graph is converted into a Labeled Property Graph (LPG), enriched with semantic attributes for nodes and edges. …”
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Intermittent Sampled Data Control for Time-Varying Formation-Containment of the Multiagent System with/without Time Delay by Ming Chi, Xu-Long Wang, Yangming Dou, Zhi-Wei Liu

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A New Technique for Quantitative Determination of Dexamethasone in Pharmaceutical and Biological Samples Using Kinetic Spectrophotometric Method by Ali Mohammad Akhoundi-Khalafi, Masoud Reza Shishehbore

“…Under optimized experimental conditions, calibration graph was linear over the range 0.2–54.0 mg L−1. …”
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A food safety targeted sampling decision-making method based on association rule mining and GNNs by Jiabin Yu, Xinyue Ma, Xin Zhang, Xiaoyu Cui, Shuaixiang Chen, Zhiyao Zhao

“…Second, a decision-making support module for targeted sampling to support food safety was constructed. A graph neural network was used to perform decision-making on the sampling frequency. …”
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Graphene for separation and preconcentration of trace amounts of cobalt in water samples prior to flame atomic absorption spectrometry by Yukun Wang, Xiaojing Ke, Xin Zhou, Jingci Li, Jingjun Ma

“…Under optimum conditions, the calibration graph was linear in the concentration range of 5.0–240.0 μg L−1 with a detection limit of 0.36 μg L−1. …”
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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…These features are used to construct a feature vector matrix, and a dynamic clustering graph is formed using fuzzy clustering to realize the fiber state diagnosis. …”
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A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample by Chaoyi Wu, Chenyu Yuan, Yinqing Fan, Ang Hong, Zhiling Wu, Zhen Wang

“…Methods Data on comprehensive psychopathology and RDoC negative valence constructs were collected from the sample. Factor analysis and exploratory graph analysis were used to extract symptom dimensions. …”
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Design of an improved graph-based model for real-time anomaly detection in healthcare using hybrid CNN-LSTM and federated learning by G Muni Nagamani, Chanumolu Kiran Kumar

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Methodological development study: Dynamic mask attention graph neural network for mechanical ventilation in elderly intensive care unit patients by Yi Xie, Ni Xie, Jiao Guo

“…We propose a dynamic mask attention graph neural network (DymaGNN) to capture the time-varying relationship of key physiological variables by constructing a dynamic heterogeneous graph structure and an adaptive edge-weighting mechanism. …”
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Edges are all you need: Potential of medical time series analysis on complete blood count data with graph neural networks. by Daniel Walke, Daniel Steinbach, Sebastian Gibb, Thorsten Kaiser, Gunter Saake, Paul C Ahrens, David Broneske, Robert Heyer

“…Additionally, we connected complete blood count samples of the same patient based on their measured time (patient-centric graphs) to incorporate time series information in the GNNs. …”
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Estimating area under the curve from graph-derived summary data: a systematic comparison of standard and Monte Carlo approaches by Sean Titensor, Joshua Ebbert, Karen Della Corte, Dennis Della Corte

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Directions for Improving Labor Force Surveys in Uzbekistan Based on Foreign Experience by A. T. Tairova

“…At the same time, approaches to forming a sample of households to be included in the survey are carried out differently in different countries. …”
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Fault diagnosis of power transformers based on dissolved gas analysis and multi-kernel graph convolution network integrated with dual-channel classifiers by Xuebin Lv, Fuzheng Liu, Mingshun Jiang, Faye Zhang, Lei Jia

“…Secondly, extract and model sample features deeply adopting graph generation network and multi-kernel graph convolution network to further explore the relationship between representation features and fault samples. …”
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Leveraging molecular-QTL co-association to predict novel disease-associated genetic loci using a graph convolutional neural network. by Julian Ng-Kee-Kwong, Andrew D Bretherick

“…We encode their co-association across the genome using PinSage, a graph convolutional neural network-based recommender system previously deployed at Pinterest. …”
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A New Approach to Studying Net Present Value and the Internal Rate of Return of Engineering Projects under Uncertainty with Three-Dimensional Graphs by Alexander Maravas, John-Paris Pantouvakis

“…Three-dimensional fNPV and fIRR graphs are introduced as a means of visualizing uncertainty. …”
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A Novel Fault Diagnosis Method Using FCEEMD-Based Multi-Complexity Low-Dimensional Features and Directed Acyclic Graph LSTSVM by Rongrong Lu, Miao Xu, Chengjiang Zhou, Zhaodong Zhang, Kairong Tan, Yuhuan Sun, Yuran Wang, Min Mao

“…Finally, a multi-classifier based on DAG LSTSVM is constructed using the directed acyclic graph (DAG) strategy, improving fault diagnosis precision. …”
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Effectiveness of dogmatic criminal law reasoning in the permanent structure of the general theory of crime and punishment through plithogenic n-SuperHyperGraphs by Luis A. Crespo-Berti, Josía Jeseff Isea Argüelles, Marco Patricio Villa Zura

“…The research involves an interdisciplinary approach of legal dogmatic theory of crime and punishment in conjunction with fuzzy logic and combinatorial mathematics to investigate a sample of case law for where n-SuperHyperGraphs fill in the gaps of traditional criminal dogmatics. …”
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ResGAT-F: a novel graph neural network-based approach for evaluating landing suitability in the lunar southern polar region by Shibo Wen, Yongzhi Wang, Xingyu Chen, Qizhou Gong, Jianzhong Liu, Xiaoxi Kang, Hengxi Liu, Kai Zhu, Sheng Zhang

“…This study proposes a Residual Connection Graph Attention Forest (ResGAT-F) model, which systematically integrates multi-source spatial data to extract regional features and environmental relationships, enabling a quantitative assessment of landing suitability that addressing safety and multi-disciplinary scientific exploration scenarios. …”
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A Dual-Perspective Self-Supervised IoT Intrusion Detection Method Based on Topology Reconstruction and Feature Perturbation by Ruisheng Li, Huimin Shen, Qilong Zhang

“…Additionally, the custom adaptive cosine loss function dynamically adjusts the loss weights of different samples and utilizes cosine similarity to align the embeddings of real and predicted graphs, thereby maximizing mutual information between local embeddings of real graphs and global summaries. …”
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