DualAD: Dual adversarial network for image anomaly detection⋆ by Yonghao Wan, Aimin Feng

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XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…This study is situated at the intersection of clinical oncology and computational intelligence, exploring the potential of gradient-boosting algorithms to overcome the limitations of conventional screening methodologies. …”
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Not seeing the trees for the forest. The impact of neighbours on graph-based configurations in histopathology by Olga Fourkioti, Matt De Vries, Reed Naidoo, Chris Bakal

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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…Automated storage and retrieval systems (AS/RS) play a crucial role in modern logistics, yet effectively monitoring cargo stacking patterns remains challenging. While computer vision and deep learning offer promising solutions, existing methods struggle to balance detection accuracy, computational efficiency, and environmental adaptability. …”
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Definition of Critical Metrics for Performance Evaluation and Multiphase Flow Modeling in an Alkaline Electrolyzer Using CFD by Marco Dreoni, Francesco Balduzzi, Syed Sahil Hossain, Matthias Neben, Francesco Maria Ferro, Giovanni Ferrara, Alessandro Bianchini

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Exploring the Structure of AI-Induced Language Change in Scientific English by Riley Galpin, Bryce Anderson, Tom S Juzek

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Credit Scoring Prediction Using Deep Learning Models in the Financial Sector by Xi Shi, Dingfen Tang, Yike Yu

“…Existing approaches often struggle with integrating structured numerical records and unstructured user behavior signals, limiting their ability to capture meaningful temporal and non-linear patterns. In the swiftly transforming domain of computational science, the incorporation of sophisticated machine learning algorithms has emerged as a critical driver in addressing these challenges. …”
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The application of vibration tactile stimulation in hand motor imagery paradigm: a pilot study by Wenbin Zhang, Aiguo Song, Hexuan Hu, Minmin Miao, Baoguo Xu

“…Background The motor imagery (MI) paradigm is widely used in active brain-computer interfaces (BCIs), but its effectiveness is hindered by accuracy limitations and individual variability. …”
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Enhancing Disaster Situation Awareness Through Multimodal Social Media Data: Evidence from Typhoon Haikui by Songfeng Gao, Tengfei Yang, Yuning Xu, Naixia Mou, Xiaodong Wang, Hao Huang

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BCINetV1: Integrating Temporal and Spectral Focus Through a Novel Convolutional Attention Architecture for MI EEG Decoding by Muhammad Zulkifal Aziz, Xiaojun Yu, Xinran Guo, Xinming He, Binwen Huang, Zeming Fan

“…This research demonstrates that BCINetV1 is computationally efficient, extracts clinically vital markers, effectively handles the non-stationarity of EEG data, and shows a clear advantage over existing methods, marking a significant step forward for practical BCI applications.…”
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Comparison of instrumental methods for color change assessment of Giomer resins by Luiza de Almeida Queiroz Ferreira, Rogéli Tibúrcio Ribeiro da Cunha Peixoto, Cláudia Silami de Magalhães, Tassiana Melo Sá, Monica Yamauti, Francisca Daniele Moreira Jardilino

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Markerless Video-Based Gait Analysis in People With Multiple Sclerosis by Matteo Moro, Giorgia Marchesi, Maria Cellerino, Giacomo Boffa, Francesca Odone, Matilde Inglese, Maura Casadio

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Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments by Donghui Han, Tong Qin, Tianyu Yang, Hua Liao, Qiaosong Hei, Fangwen Yu, Bailu Si, Weihua Dong

“…Current models often rely on knowledge of the discharge patterns of navigation cells in living organisms (e.g. place/grid cells) to encode spatial information, which works well in ideal environments. …”
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GDText-VM: an arbitrary-shaped scene text detector based on globally deformable VMamba by Yingnan Zhao, Zheng Hu, Fangqi Ding, Jielin Jiang, Xiaolong Xu

“…This approach enhances the capability to capture long-range dependencies, achieving a global receptive field and rapid convergence while maintaining linear computational complexity. Unlike the original VMamba, GDText-VM integrates deformable convolutions to enhance focus on local regions and reduces reliance on cross-shaped activation patterns. …”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…By harnessing these technologies, we can analyze data to gain insights into symptoms and patterns, ultimately facilitating remote patient care. …”
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Granularity at Scale: Estimating Neighborhood Socioeconomic Indicators From High-Resolution Orthographic Imagery and Hybrid Learning by Ethan Brewer, Giovani Valdrighi, Parikshit Solunke, Joao Rulff, Yurii Piadyk, Zhonghui Lv, Jorge Poco, Claudio Silva

“…Concurrent with improved sensor resolutions, recent advancements in machine learning and computer vision have made it possible to quickly extract features from and detect patterns in image data, in the process correlating these features with other information. …”
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A Comprehensive Study of Part-Solid Lung Adenocarcinoma with Lymph Node Metastasis: Clinical, Pathological, and Radiological Perspectives by Zhao Z, Gan H, Fu BJ, Li W, Lv F, Chu Z

“…Radiologically, solid components located at the tumor margins or distributed in a scattered manner (odds ratio [OR] = 4.048, P = 0.038) and consolidation-to-tumor ratio (CTR) > 57.2% (area) (OR = 45.649, P = 0.041) were independent predictors of LNM, with an area under the curve of this model being 0.881, sensitivity of 97%, and specificity of 77.1% (P < 0.001).Conclusion: LNM in part-solid LUADs is more prevalent in IACs with high-grade patterns, particularly the micropapillary pattern, with these lesions presenting as part-solid lesions that often have a larger CTR or distinct distribution of solid components.Keywords: lymphatic metastasis, lung neoplasms, adenocarcinoma of lung, tomography, X-ray computed…”
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IKZF1 as a potential therapeutic target for dendritic cell-mediated immunotherapy in IgA nephropathy by Fei Peng, Chunjia Sheng, Jiayi He, Yena Zhou, Yilun Qu, Shuwei Duan, Yinghua Zhao, Jikai Xia, Jie Wu, Guangyan Cai, Lingling Wu, Chuyue Zhang, Xiangmei Chen

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Moving Target Tracking and Imaging Through Scattering Media via Speckle-Difference-Combined Bispectrum Analysis by Yingbo Wang, Jie Cao, Chengqiang Xu, Yang Cheng, Xuemin Cheng, Qun Hao

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A memory model of rodent spatial navigation in which place cells are memories arranged in a grid and grid cells are non-spatial by David E Huber

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