Early breast cancer detection in CT scans using convolutional neural bidirectional feature pyramid network by Tahani Jaser Alahmadi, Adeel Ahmed, Amjad Rehman, Abeer Rashad Mirdad, Bayan Al Ghofaily, Shehryar Ali

“…Despite the potential of CT scans in visualizing breast tissue in 3D with high resolution, extracting meaningful patterns from these scans is difficult due to the complex and nonlinear nature of the tissue features. …”
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Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning by Naafey Aamer, Muhammad Nabeel Asim, Aamer Iqbal Bhatti, Andreas Dengel

“…Methods We developed BIND (Biological Interaction Network Discovery), a comprehensive framework utilizing 11 Knowledge Graph Embedding Methods evaluated on 8 million interactions across 30 biological relationships and 129,000 nodes. …”
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CeRNA network reveals potential diagnostic biomarkers or immunotherapy targets for Hypopharyngeal squamous cell carcinoma by Xi Yang, Chun Feng, Donghui Jiang, Xin Xu, Yingying Zhang, Jin Wang, Xiaoguang He

“…In addition, the diagnostic value of the biomarkers and their relevance to the tumor microenvironment and immunotherapy were evaluated. A ceRNA network based on mRNAs, circRNAs, and miRNAs was established. …”
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A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing by Hsuan-Ming Lin, JrJung Lyu

“…Traditional oversampling methods often struggle with complex clinical data. This study evaluates an enhanced conditional Wasserstein Generative Adversarial Network with Gradient Penalty (CWGAN-GP) framework to improve IDH prediction by generating high-utility synthetic data for balancing. …”
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Changes of functional brain network topology associated with nutritional indicator of patients with recurrent major depressive disorder by Guanghui Liu, Yanli Jiang, Chunpeng Zhou, Xiangxiang Wang, Min Dai, Jinping Zhang, Jing Yu, Gangzhong Zhang

“…The level of BDNF were positively related to nodal strength of right amygdala and nodal global efficiency of right amygdala of rMDD patients.ConclusionOur findings revealed distinct patterns of brain network topology between fMDD and rMDD patients, with rMDD patients showing more widespread disruptions, which might be associated with greater number of relapses and worse level of neurological nutrition. …”
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Clinico-dermoscopic study and comparative evaluation with Wood’s Lamp as a diagnostic tool in patients with melasma by Anupa Khadka, Sabina Bhattarai, Sagar GC

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Carotid plaque segmentation and classification using MRI-based plaque texture analysis and convolutional neural network by Zakarya Hasan Ahmed Abu Alregal, Gehad Abdullah Amran, Ali A. Al-Bakhrani, Saleh Abdul Amir Mohammad, Amerah Alabrah, Lubna Alkhalil, Abdalla Ibrahim, Maryam Ghaffar, Maryam Ghaffar

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LLMs Have Rhythm: Fingerprinting Large Language Models Using Inter-Token Times and Network Traffic Analysis by Saeif Alhazbi, Ahmed Hussain, Gabriele Oligeri, Panos Papadimitratos

“…We develop a Deep Learning (DL) pipeline to capture these timing patterns using network traffic analysis and evaluate it on 16 Small Language Models (SLMs) and 10 proprietary LLMs across different deployment scenarios, including local host machine (GPU/CPU), Local Area Network (LAN), Remote Network, and when using Virtual Private Network (VPN). …”
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Multidimensional evaluation of nutritional security policies in the Republic of Moldova: gaps, progress, and alignment with international standards by Rodica Siminiuc, Dinu Țurcanu, Sergiu Siminiuc

“…In the Republic of Moldova, rapid changes in food availability and consumption patterns have intensified the need for robust public policies to promote healthy dietary habits.MethodsThis study evaluates Moldova’s public policies on nutritional security using a multidimensional model adapted from the Policy Evaluation Network framework. …”
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Identification and evaluation of metabolic mRNAs and key miRNAs in colorectal cancer liver metastasis by Guanxuan Chen, Shiwen Wang, Meng Zhang, Wenna Shi, Ruoyu Wang, Wanqi Zhu

“…Subsequently, we employed Weighted Gene Co-expression Network Analysis (WGCNA) to construct an integrated co-expression network of mRNAs and miRNAs, facilitating the identification of pivotal mRNAs and miRNAs. …”
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Integrated evaluation and optimization of acid fracturing effectiveness in carbonate reservoirs: Experimental insights and field validation. by Peng Lu, Songlei Li, Jinsong Liu, Nan Yuan, Heng Liu

“…The study's key innovation lies in identifying conductivity-governing factors through an integrated experimental-modeling approach, establishing criteria for optimal etching pattern development. The framework is further enriched by introducing dynamic conductivity metrics and heterogeneity indices, which deepen theoretical understanding. …”
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Evaluating the Accuracy of Land-Use Change Models for Predicting Vegetation Loss Across Brazilian Biomes by Macleidi Varnier, Eliseu José Weber

“…While machine-learning-based models use computational methods and spatial variables to identify patterns that explain the occurrence of changes. Considering these two groups of models, machine-learning-based models are much more widely used, even though their formulation is considerably more complex. …”
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Evaluating the Quality of High-Frequency Pedestrian Commuting Streets: A Data-Driven Approach in Shenzhen by Xin Guo, Yuqing Hu, Yixuan Zhang, Shengao Yi, Wei Tu

“…By integrating multi-source urban big data, we identify HFPCSs using LBS data and develop a multi-dimensional evaluation system that incorporates 1.07 million Points of Interest (POIs) for assessing convenience, utilizes DeepLabv3+ for the semantic segmentation of street view imagery to evaluate comfort, and leverages 15,374 km of road network data for accessibility analysis. …”
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Comparison of Fuzzy-AHP and ANP Decision Making Methods to Assess the Ecological Capability of Ecotourism Application (Case study: Dehloran National Natural Monuments) by Mohsen Tavakoli

“…Tourism with the ecotourism approach is considered as a pattern of tourism in nature. This spatial pattern involves the approach of tourists to the natural environment, with different motivations that the tourist is considered in traveling to the natural environment or nature. …”
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Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions by Mohamad Alkhalidi, Abdullah Al-Dabbous, Shoug Al-Dabbous, Dalal Alzaid

“…This analysis reveals that ERA5 effectively captures general wind speed patterns, with offshore stations demonstrating stronger correlations (up to 0.85) and higher Perkins Skill Score (PSS) values (up to 0.94). …”
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Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis by Yun Zhu, Dan Han, Hongjue Duan, Qi Rao, Yike Qian, Qiaoyun Chen, Xiao Du, Huanyu Ni, Siliang Wang

“…Thereafter, we conducted single-sample gene set enrichment analysis (ssGSEA) for evaluating pyroptosis-associated expression patterns among cases and for exploring the associations with clinicopathological factors and prognostic outcome. …”
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Entrepreneurial Skill Augmented Neural Network (ESANN): A Deep Learning Approach for Enhancing Entrepreneurial Competencies in Teachers by Jian Li

“…The model leverages Convolutional Neural Networks (CNNs), Bidirectional Long Short-Term Memory (Bi-LSTM) networks, and a Transformer-based recommendation engine to deliver adaptive, real-time feedback and optimize training pathways based on individual learning patterns. …”
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StationNet: An Algorithm for the Extraction and Visualization of Top-n Correlated Bike Stations in Bike Sharing Systems Big Datasets by Ahmet Şakir Dokuz

“…Many application areas are present which use BSS big datasets, such as behavioral analyses, urban pattern discovery, and network analysis of bike stations. …”
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Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

“…Meanwhile, deep learning models excel in pattern recognition and automated feature extraction, offering a complementary approach to traditional gene selection techniques. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

“…Deep recurrent neural networks (RNNs) are utilized to capture temporal dependencies in charging station data, allowing for more accurate predictions and adaptive control strategies. …”
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