14 papers · ranked by Valyu relevance
Li Liang, Shi-Ming Cai, Shi-Cai Gong, Alexandre G. Evsukoff + 1 more
Hypergraphs are powerful tools for modeling complex systems because they naturally encode higher-order interactions. However, most existing hypergraph representation-learning methods still struggle to capture such high-order structures, particularly in heterogeneous hypergraphs, which results in suboptimal performance…
Bo Xiao, Wei Yin, Stanisław Drożdż
Bitcoin transaction anomaly detection is essential for maintaining financial market stability. A significant challenge is capturing the dynamically evolving transaction patterns within transaction networks. Dynamic graph models are effective for characterizing the temporal evolution of transaction systems. However…
Jiangnan Zhou, Sheng Zhang, Bing Wu, Qiuming Wang + 5 more
Existing methods for hypergraph node classification usually rely on local message passing and use a unified strategy for topological modeling across hyperedges of different sizes. However, they have two limitations in semi-supervised settings. First, representation learning mainly depends on local neighborhoods, making…
Arooj Nissar, A. H. Mir
Background Computed tomography imaging, a non-invasive tool, is used around the globe by medical professionals to identify and diagnose lung cancer; a lethal disease with high rates of occurrence and mortality globally. Radiomics extracted from medical images, including computed tomography, in tandem with machine…
Meilin Liu, Wenping Zheng, Shuxia Yuan, Jeng-Shyang Pan + 3 more
Hypergraph neural networks have shown strong potential for node classification due to their ability to capture high-order relationships and multi-granularity structural patterns. However, real-world hypergraphs are often sparse, which limits interaction modeling through node-hyperedge incidence and, in turn, weakens…
Amin Khodaei, Zahra Pourabbas, Fatemeh Hashem-zadehdizajyekan, Erfan Esmaeili
Title: Highlights 1. • Modeling the structure of various viruses in the form of directed weighted graphs. 2. • Presenting a feature extraction algorithm based on complex networks metrics. 3. • The impact of the eigen-vector, input centrality and output centrality measures of specific nucleotide triplets within genes…
Yang Qi, Yiqi Chen, Yingfu Wu, Yang Guo + 4 more
Transposable elements (TEs) are DNA sequences that can move within a genome. They constitute a substantial portion of the eukaryotic genome and play essential roles in gene regulation and genome evolution. Accurate classification of these repetitive elements is crucial for investigating their potential impact on the…
Muhammed Ali Pala, Muhammet Burhan Navdar, Jae-Ho Han
Background/Objectives: Traditional medical image analysis methods often suffer from locality bias, limiting their ability to model long-range contextual relationships between spatially distributed anatomical structures. To overcome this challenge, this study proposes SPX-GNN (Superpixel Explainable Graph Neural…
Daniela M. Godinho, João M. Felício, Carlos A. Fernandes, Raquel C. Conceição + 1 more
Axillary Lymph Nodes (ALNs) can be affected by breast cancer, and the number of affected ALNs is a determinant factor in breast cancer staging. Microwave imaging (MWI) has emerged as a promising technique for ALN assessment, addressing limitations in conventional imaging modalities. This study investigates, for the…
Hui Wang, Bailing Dai, Na Feng, Hongxia Zhang + 5 more
Objectives To assess the inter-reader agreement and diagnostic performance of Node-reporting and data system (Node-RADS) in the evaluation of colon cancer among radiologists with varied experience levels. Materials and methods A total of 247 patients with colon cancer were included in this retrospective study. Lymph…
Hassan Ishfaq, Jamal Hussain Shah, Rabia Saleem, Maira Afzal + 1 more
Classification and detection of zero-day attacks remain a significant challenge within the domain of cybersecurity. Due to the vast types of malware families and the presence of an imbalanced dataset, real-time detection and classification become increasingly complex and inaccurate. Thus, there’s an urgent need to…
Jiarong Lu, Bin Liao, Yi Liu, Lei Zhong
Against the complex characteristics of the Ethereum transaction network and the limitations of existing graph embedding methods based on random walks, which fail to effectively capture transaction temporal dynamics and the flow of funds, we propose a fraud detection algorithm for Ethereum, ETX2Vec (Ethereum…
Borui Zuo, Keqi Shang, Jie Zhang, Manyu Peng + 2 more
Due to the differences in node types and the diversity of network relationships, Fuzzy Social Network Analysis (FSNA) needs to specifically address the issues of network heterogeneity and relationship ambiguity. To address this challenge, we propose a new analytical framework called Extended Directed Fuzzy Social…
Sabino Francesco Roselli, Eibe Frank
Model trees provide an appealing way to perform interpretable machine learning for both classification and regression problems. In contrast to “classic” decision trees with constant values in their leaves, model trees can use linear combinations of predictor variables in their leaf nodes to form predictions, which can…