Prognostic value of tertiary lymphoid structures in triple-negative breast cancer: integrated analysis with the tumor microenvironment and clinicopathological features by Florence Boissière-Michot, Marie-Christine Chateau, Simon Thézenas, Virginie Lafont, Evelyne Crapez, Evelyne Crapez, Priyanka Sharma, Angélique Bobrie, Angélique Bobrie, Pascal Roger, Séverine Guiu, Séverine Guiu, William Jacot, William Jacot, William Jacot, William Jacot

“…In multivariate analysis, pathological stage, adjuvant chemotherapy and PT-TLS remained correlated with relapse-free survival.ConclusionOur results suggest that TLS are a frequent feature in early TNBC and that their presence, particularly at the tumor periphery, recapitulates the tumor immune microenvironment. …”
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Uncovering abnormal gray and white matter connectivity patterns in Alzheimer’s disease spectrum: a dynamic graph theory analysis for early detection by Juanjuan Jiang, Tao Kang, Ronghua Ling, Yingqian Liu, Jiuai Sun, Yiming Li, Xiaoou Li, Hui Yang, Bingcang Huang, the Alzheimer’s Disease Neuroimaging Initiative

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Gut microbiota modulation: a key determinant of atopic dermatitis susceptibility in children by Huimiao Tang, Huimiao Tang, Wenxin Li, Yidan Xu, Yidan Xu, Yanjun Zhou, Yanjun Zhou, Michael R. Hamblin, Xiang Wen, Xiang Wen

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Uncovering How Information Quality Shapes Diverse User Engagement on Content Community Platforms: Harnessing Deep Learning for Feature Extraction by Yanzi Wang, Min Wang, Zhen Zhu, Haoxiang Ye

“…Our objective is to uncover distinct patterns of impact that information quality features have on these different forms of user engagement. …”
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PIONet: A Positional Encoding Integrated Onehot Feature-Based RNA-Binding Protein Classification Using Deep Neural Network by Mahmood A. Rashid, Mayank Chaturvedi, Kuldip K. Paliwal

“…The CNN model processes these combined features to extract local patterns and motifs critical for RNA-protein interactions. …”
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An Efficient One-Dimensional Texture Representation Approach for Lung Disease Diagnosis by Abrar Alabdulwahab, Hyun-Cheol Park, Heon Jeong, Sang-Woong Lee

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Robust EEG Characteristics for Predicting Neurological Recovery from Coma After Cardiac Arrest by Meitong Zhu, Meng Xu, Meng Gao, Rui Yu, Guangyu Bin

“…Our evaluation revealed that functional connectivity features contribute the most to classification at 70%. …”
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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…These algorithms simultaneously combined the continuous and binary representations of PSO and SMO to effectively manage trade-offs between accuracy, feature selection, and hyperparameter tuning. We evaluated several CAD models and investigated the impact of handcrafted methods such as Local Binary Patterns (LBP), Histogram of Oriented Gradients (HOG), Gabor Filters, and Edge Detection. …”
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Model morphing supported large scale crop type mapping: A case stuy of cotton mapping in Xinjiang, China by Longcai Zhao, Taifeng Dong, Xin Du, Bing Dong, Qiangzi Li

“…To address these challenges, this paper constructs a time-continuous sequence model that captures the unique feature pattern between the target-crop and non-target crops (referred to as the knowledge model). …”
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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Results indicated that: 1) The reconstruction of cloud-free time series images with the Cloud Score+ method and the integrated NSPI and MNSPI approach was stable and effective, with correlation coefficients (<italic>r</italic>) exceeding 0.87 and low values for indicators such as root mean square error (RMSE), Robert&#x0027;s edge (Edges), and local binary patterns (LBP), meeting the requirements for paddy rice classification. 2) The classification accuracy of combining Sentinel-1 polarization features with Sentinel-2 spectral features could improve by up to 10.52% compared to before the combination. …”
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Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme by Kyrylo Yemets, Ivan Izonin, Ivanna Dronyuk

“…These approaches have already shown considerable advantages over traditional methods, especially due to their capacity to efficiently process large datasets and detect complex patterns. A crucial step in the forecasting process is the preprocessing of time-series data, which can greatly improve the training quality of neural networks and the precision of their predictions. …”
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Integrating Interpretability in Machine Learning and Deep Neural Networks: A Novel Approach to Feature Importance and Outlier Detection in COVID-19 Symptomatology and Vaccine Effic... by Shadi Jacob Khoury, Yazeed Zoabi, Mickey Scheinowitz, Noam Shomron

“…In this study, we introduce a novel approach that integrates interpretability techniques from both traditional machine learning (ML) and deep neural networks (DNN) to quantify feature importance using global and local interpretation methods. …”
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10-year stability of magnetite nanopowder prepared by the exploding wire method: is it a useful feature for environment safety and biomedical applications? by I. A. Khlusov, A. S. Omelyanchik, V. V. Rodionova, V. V. Shupletsova, O. G. Khaziakhmatova, K. A. Yurova, L. S. Litvinova, I. K. Norkin

“…No dramatic changes in the structural, magnetic, and cytotoxic features of MNPs were noted after 10 years of storage. …”
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A Three-Dimensional Feature Space Model for Soil Salinity Inversion in Arid Oases: Polarimetric SAR and Multispectral Data Synergy by Ilyas Nurmemet, Yilizhati Aili, Yang Xiang, Aihepa Aihaiti, Yu Qin, Bilali Aizezi

“…Based on the interactions of these three optimal features within the 3D feature space, we constructed the Optical-Radar Salinity Inversion Model (ORSIM). …”
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D4Care: A Deep Dynamic Memory-Driven Cross-Modal Feature Representation Network for Clinical Outcome Prediction by Binyue Chen, Guohua Liu

“…Besides, we use gating mechanisms and dynamic memory components to enable the model to learn feature information of different historical-current patterns, further improving the model’s performance. …”
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Comparative Analysis of AlexNet, ResNet-50, and VGG-19 Performance for Automated Feature Recognition in Pedestrian Crash Diagrams by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…By employing cutting-edge technological methods, the research aims to uncover and extract hidden features from pedestrian crash data in Michigan, thereby enhancing the understanding and prevention of such incidents. …”
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An explainable hybrid feature aggregation network with residual inception positional encoding attention and EfficientNet for cassava leaf disease classification by M. Sundara Srivathsan, S. Alden Jenish, K. Arvindhan, R. Karthik

“…The RIPEA track extracts significant features by leveraging residual connections for preserving gradients and uses multi-scale feature fusion for combining fine-grained details with broader patterns. …”
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MDFT-GAN: A Multi-Domain Feature Transformer GAN for Bearing Fault Diagnosis Under Limited and Imbalanced Data Conditions by Chenxi Guo, Vyacheslav V. Potekhin, Peng Li, Elena A. Kovalchuk, Jing Lian

“…Beyond performance metrics, this work also incorporates a Grad-CAM-based interpretability scheme to visualize hierarchical feature activation patterns within the discriminator, providing transparent insight into the model’s decision-making rationale across different fault types. …”
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Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns by Aleksandra Badura, Maria Bienkowska, Andrzej Mysliwiec, Ewa Pietka

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Identification of anoikis-related molecular patterns and the novel risk model to predict prognosis, tumor microenvironment infiltration and immunotherapy response in bladder cancer by Luochen Zhu, Feng Xiao, Yi Hou, Shenjun Huang, Yanyan Xu, Xiaohong Guo, Xinwei Dong, Chunlu Xu, Xiaolei Zhang, Haijuan Gu

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