Discovery of novel diagnostic biomarkers of hepatocellular carcinoma associated with immune infiltration by Qiang Liu, Hua Zhang, Heng Xiao, Ao Ren, Ying Cai, Rui Liao, Huarong Yu, Zhongjun Wu, Zuotian Huang

“…Objective Diagnosis of hepatocellular carcinoma (HCC) remains challenging for clinicians. Machine learning approaches and big data analyses are viable strategies for identifying HCC diagnostic markers.Materials and methods In this study, we downloaded mRNA expression profiles of HCC from the GEO database and used random forest and machine learning algorithms, such as least absolute shrinkage and selection operator, to screen for reliable diagnostic genes. …”
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Refining early detection of Marburg Virus Disease (MVD) in Rwanda: Leveraging predictive symptom clusters to enhance case definitions by Olivier Nsekuye, Frederick Ntabana, Hugues Valois Mucunguzi, Ziad El-Khatib, Eric Remera, Lyndah Makayotto, Menelas Nkeshimana, David Turatsinze, Frederic Ntirenganya, Semakula Muhammed, Athanase Rukundo, Brian Chirombo, Richard Muvunyi, Claude Mambo Muvunyi, Pacifique Nizeyimana, Yvan Butera, Sabin Nsanzimana, Edson Rwagasore

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Decoding Digital Discourse Through Multimodal Text and Image Machine Learning Models to Classify Sentiment and Detect Hate Speech in Race- and Lesbian, Gay, Bisexual, Transgender,... by Thu T Nguyen, Xiaohe Yue, Heran Mane, Kyle Seelman, Penchala Sai Priya Mullaputi, Elizabeth Dennard, Amrutha S Alibilli, Junaid S Merchant, Shaniece Criss, Yulin Hswen, Quynh C Nguyen

“… BackgroundA major challenge in sentiment analysis on social media is the increasing prevalence of image-based content, which integrates text and visuals to convey nuanced messages. …”
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The present educational process as a state of the future social system by I. V. Petrova

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Declarative and procedural tactical knowledge in youth soccer players: an exploratory study in Chile by Ricardo Souza de Carvalho, Eugenio Merellano Navarro, Manuel González-Farías, Jorge Mendez-Cornejo, Alejandro Almonacid-Fierro

“…It indicates why emergent-based methodologies that support the interweaving of tactical thought and action to enable adjusted and effective learning in grassroots football are urgently needed.…”
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Group psychological counseling-based growth mindset intervention to promote active aging behaviors in older people: protocol for a randomized controlled trial by Xiaohua Xiao, Yunying Zhu, Dongdong Jiang, Anna Vinnikova, Jin Zhang, Ruotong Zhang, Wenxiao Chen, Sisi Li, Jingwen Wang, Mingyuan Sheng, Joseph T. F. Lau, Qian Yang

“…Indicators of active aging and positive psychology orientation, including growth mindset, active learning behaviors, active health behavior, active social participation behaviors, and active self-security behaviors will be evaluated to verify intervention effects at four timepoints (baseline, after the intervention, one month and three months after the intervention). …”
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The Role of Performance Metrics in Estimating Market Values of Footballers in Europe's Top Five Leagues by Murat Işık, Mehmet Ali Yalçınkaya

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Future directions: what LIES ahead for smart biochemical wearables in health monitoring? by S. Kharb

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Comparative analysis of convolutional neural networks and transformer architectures for breast cancer histopathological image classification by Bo Yuan, Yudie Hu, Yan Liang, Yutong Zhu, Lingyu Zhang, Shimin Cai, Rui Peng, Xianbin Wang, Zheng Yang, Jinhui Hu

“…Recent advances in deep learning demonstrate promising potential to improve diagnostic accuracy, reduce false positives/negatives, and alleviate radiologists’ workload, thereby enhancing clinical decision-making in breast cancer management.MethodsThis study trains and evaluates 14 deep learning models, including AlexNet, VGG16, InceptionV3, ResNet50, Densenet121, MobileNetV2, ResNeXt, RegNet, EfficientNet_B0, ConvNeXT, ViT, DINOV2, UNI, and GigaPath on the BreakHis v1 dataset. …”
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Efficient Progressive Mamba Model for Hyperspectral Sequence Unmixing by Yang Liu, Shujun Liu, Huajun Wang

“…In recent years, deep learning-based hyperspectral unmixing has increasingly incorporated spatial information to improve performance. …”
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Exploring single-head and multi-head CNN and LSTM-based models for road surface classification using on-board vehicle multi-IMU data by Luis A. Arce-Saenz, Javier Izquierdo-Reyes, Rogelio Bustamante-Bello

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Developing and presenting a mathematical model for the purpose of organizational culture architecture based on creating alignment between the strategic reference points of organiza... by Elyas hasanzadeh Shweili, Mir Mehrdad peidaie, Ali reza Rezghi Rostami

“…Strategic reference points of organizational elements Strategic reference points are points for coordination that, if all elements and systems of the organization coordinate with it, an all-round coordination will occur (Kiyajori & Brimani, 2017). The method of strategic reference points, which is also called alignment, has a key position in organizational studies and strategic management; because a suitable method for acquiring and creating value in the market and increasing the performance of the organization is the interaction and coordination between the elements and components of the organization and the environment (Walian et al, 2017). …”
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A TRIZ-based algorithm for business model innovation in manufacturing SMEs: a systematic framework for strategic innovation integrated with the business model canvas by Juan G. Mejia-Duque, Andres Guerrero-Alvarado

“…The algorithm systematically transforms business models by applying TRIZ to all BMC components, addressing SMEs’ key challenges and positioning TRIZ as a strategic BMI tool rather than just a problem-solving method. …”
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Multimodal radiomics model with triple -timepoint contrast-enhanced ultrasound for precise diagnosis of C-TIRADS 4 thyroid nodules by Linlin Shao, Lili Zhang, Lifang Liu, Fangfang Sun, Hongyu Li, Tongfeng Liu, Feng Hu, Lirong Zhao

“…ROIs were manually delineated (3D-Slicer), with radiomics features extracted (PyRadiomics) and selected via mRMR and LASSO. Six CEUS radiomics-based machine learning models (KNN, SVM, RF, XGBoost, LightGBM, SGD) were developed and evaluated using AUC, accuracy, sensitivity, specificity, and F1-score. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…However, traditional intrusion detection methods exhibit several limitations, including insufficient feature extraction from network data, high model complexity, and data imbalance, which result in issues like low detection efficiency, as well as frequent false positives and missed alarms. …”
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PLFF-SLAM: A Point and Line Feature Fused Visual SLAM Algorithm for Dynamic Illumination Environments by Shucheng Huang, Wenhan Ren, Mingxing Li

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Prediction of Traction Energy Consumption for Urban Rail Transit Trains in Relative Speed Mode by GUO Tuansheng

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A Multi-Encoder BHTP Autoencoder for Robust Lithium Battery SOH Prediction Under Small-Sample Scenarios by Chang Liu, Shunli Wang, Zhiqiang Ma, Siyuan Guo, Yixiong Qin

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A population-based observational study using statistical modeling to assess the association between depressive symptom severity and sleep disorders in postmenopausal women by Ying Cui, Huimin Du

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Individual Segmentation of Intertwined Apple Trees in a Row via Prompt Engineering by Herearii Metuarea, François Laurens, Walter Guerra, Lidia Lozano, Andrea Patocchi, Shauny Van Hoye, Helin Dutagaci, Jeremy Labrosse, Pejman Rasti, David Rousseau

“…Segmenting individual apple trees in dense orchard rows is challenging because of the complexity of outdoor illumination and intertwined branches. Traditional methods rely on supervised learning, which requires a large amount of annotated data. …”
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