Identification and validation of biomarkers, construction of diagnostic models, and investigation of immunological infiltration characteristics for idiopathic frozen shoulder by Han-tao Jiang, Li-ping Shen, Meng-Qi Pang, Min-jiao Wu, Jiang Li, Wei-jie Gong, Gang Jin, Rang-teng Zhu

“…At the outset, we conducted differential expression analysis, weighted gene co-expression network analysis (WGCNA), and utilized the cytoHubba plugin, complemented by two machine learning algorithms, receiver operating characteristic (ROC) analysis, and expression level evaluation to identify biomarkers for FS. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Immune response characteristics and functional enrichment patterns were further evaluated in these cohorts.ResultsOur study delved into disulfidptosis in LUAD through a series of analyses: scRNA-seq data processing, WGCNA analysis, construction of a prognostic model, evaluation of clinical features and risk, enrichment analysis, mutation landscape assessment, and examination of the tumor microenvironment. …”
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The role of senescence-related hub genes correlating with immune infiltration in type A aortic dissection: Novel insights based on bioinformatic analysis. by Wei He, Panli Tang

“…Additionally, a miRNA-gene network involving hub DESRGs was constructed. Finally, CIBERSORT was employed to analyze the compositional patterns of the 22 types of immune cell fractions in AAD.…”
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Extraction of <i>Suaeda salsa</i> from UAV Imagery Assisted by Adaptive Capture of Contextual Information by Ning Gao, Xinyuan Du, Min Yang, Xingtao Zhao, Erding Gao, Yixin Yang

“…The model accurately delineates fine-grained spatial distribution patterns of <i>Suaeda salsa</i>, outperforming existing approaches in capturing ecologically critical structural details.…”
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Respiratory symptoms among e-cigarette users without an established smoking history in the VERITAS cohort by Jefrrey Zamora Goicoechea, Allison Boughner, Juan José Cirion Lee, Aman Mahajan, Kurt Yeo, Maris Sproga, Christopher Russell, Michael Coughlan, Arielle Selya, Grazia Caci, Pasquale Caponnetto, Venera Tomaselli, Riccardo Polosa

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Predicting danceability and song ratings using deep learning and auditory features by Wei Wu

“…Our model integrates a Bidirectional Long Short-Term Memory (BiLSTM) network to capture sequential and contextual patterns from categorical inputs, alongside a Residual Network (ResNet) that extracts hierarchical representations from numerical auditory features. …”
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Using of Deep Learning in Beamforming Antenna Array by Ali Naji, Thamer M. Jamel M. Jamel, Hassan F. khazaal

“…To substantiate the efficacy of the technique, several illustrative examples are employed to steer the beam pattern in the desired direction. …”
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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

“…Large-scale analysis of functional connectivity within intrinsic brain networks using functional magnetic resonance imaging (fMRI) data has been widely used for identifying biomarkers in various psychiatric disorders. …”
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Industrial Image Anomaly Detection via Synthetic-Anomaly Contrastive Distillation by Junxian Li, Mingxing Li, Shucheng Huang, Gang Wang, Xinjing Zhao

“…<i>FeaCali</i> modules are trained to strip out a student’s anomalous patterns in anomaly branches, enhancing the student network’s exclusive modeling of normal patterns. …”
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Machine learning-optimized dual-band wearable antenna for real-time remote patient monitoring in biomedical IoT systems by Umar Musa, Amor Smida, Muhammad S. Yahya, Mohamed I. Waly, Jun Jiat Tiang, Nazih Khaddaj Mallat, Surajo Muhammad, Abubakar Salisu

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Forecasting Insurance Company Commitments with Long Short-Term Memory Models by Negar Tehraniyazdi, Reza Vaezi, Saeed Setayeshi, Iman Raeesi Vanani

“…It can identify hidden patterns and non-linear, complex relationships within claims data. …”
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Transformer-Guided Serial Knowledge Distillation for High-Precision Anomaly Detection by Danyang Wang, Bingyan Wang

“…This three-stage architecture consists of a fixed pretrained teacher network serving as the upstream feature extractor, a dedicated multi-feature aggregation and filtering module integrated with Vision Transformer components as the intermediate processor, and a trainable student network functioning as the downstream reconstruction module. …”
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Ranking nodes in bipartite systems with a non-linear iterative map by Andrea Mazzolini, Michele Caselle, Matteo Osella

“…This paper introduces a method based on a non-linear iterative map to evaluate node relevance in bipartite networks. By tuning a single parameter γ, the method captures different concepts of node importance, including established measures like degree centrality, eigenvector centrality and the fitness-complexity ranking. …”
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Dynamical System Modeling for Disruption in Supply Chain and Its Detection Using a Data-Driven Deep Learning-Based Architecture by Víctor Hugo de la Cruz Madrigal, Liliana Avelar Sosa, Jose-Manuel Mejía-Muñoz, Jorge Luis García Alcaraz, Emilio Jiménez Macías

“…The network architecture integrates convolutional layers for feature extraction and dense layers for classification, thereby enhancing its ability to identify disruption-related patterns. …”
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Spectrogram-Based Arrhythmia Classification Using Three-Channel Deep Learning Model with Feature Fusion by Alaa Eleyan, Fatih Bayram, Gülden Eleyan

“…This spectrogram is further processed to generate a histogram of oriented gradients (HOG) and local binary pattern (LBP) features. Three separate 2D convolutional neural networks (CNNs) then analyze these three image representations in parallel. …”
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Altered internetwork functional connectivity and graph analysis of occipital regions in patients with chronic rhinosinusitis accompanied by olfactory dysfunction by Hongmei Kuang, Shunda Hong, Yeyuan Chen, Hao Peng, Zihan Li, Yangyang Xie, Wanqing Zhou, Suhong Qin, Jing Ru, Jian Jiang

“…These results imply that distinct brain network patterns, particularly in the occipital cortex, could be a valid neuroimaging marker for related diagnosis and prognosis of CRSsOD and CRSwOD patients, and contribute to our better understanding of the central neural mechanisms of CRSwOD, providing new ideas for the clinical management of CRSwOD.…”
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Strengthening the public health system of Sierra Leone through scientific research and community engagement by Gebrekrstos Negash Gebru, Adel Hussein Elduma, James Sylvester Squire, Mohamed Alex Vandi, Soter Ameh, Hawawu Hussein, Kassim Kamara, Eric Ikoona, Ikechukwu Ogbuanu

“…The topics covered include investigations and responses to outbreaks and pandemics of both national and international significance, evaluations of electronic surveillance systems, assessments of the impact of COVID-19 on routine immunization, factors associated with COVID-19 fatalities, predictors of mental health disorders, and analyses of trends and patterns related to various priority diseases. …”
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Transcriptome analysis of ovarian cancer uncovers association between tumor-related inflammation/immunity and patient outcome by Jingfang Wang, Wenrui Zhu, Xia Li, Yuanyuan Wu, Wenhui Ma, Yangzhou Wang, Weihong Zhao, Fang Wei, Wenhao Wang

“…The immune infiltration microenvironment, clinicopathological features, and survival rates differed significantly between two inflammatory gene expression patterns identified using cluster and immune microenvironment analyses. …”
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Resilient Operation of Electric Vehicles considering Grid Resiliency and Uncertainties by Seyed Mostafa Armaghan, Fatemeh Asgharzadeh, Babak Yousefi-Khanghah, Hamid Reza Ashrafi

“…This paper proposes a novel short-time optimization method based on a resiliency enhancement strategy for a smart distribution network during adverse weather conditions. The key idea is to integrate various electric vehicles (EVs) with different behaviour patterns and other distributed energy resources into emergency tools of distribution network operation such as topology reconfiguration and grid-supported services. …”
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Adaptive meta-modeling of evapotranspiration in arid agricultural regions of Saudi Arabia using climatic factors, drought indices and MODIS data by Osama Elsherbiny, Salah Elsayed, Obaid Aldosari, Muhammad Sohail Memon, Ahmed Elbeltagi

“…Machine learning models, including the backpropagation neural network (BPNN) and XGBoost Regressor (XGB), enhanced with an adaptive meta-model (AMM) strategy, were evaluated for predicting monthly AET. …”
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