Multi-modality radiomics diagnosis of breast cancer based on MRI, ultrasound and mammography by Jiao Wu, YongXin Li, Wanqing Gong, Qian Li, Xue Han, Tingting Zhang

“…Methods This study retrospectively collected data from 204 patients across three hospitals, including MRI, US, and MMG imaging data along with confirmed pathological diagnoses. …”
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Evaluation of Modified Reflection Symmetry Decomposition Polarization Features for Sea Ice Classification by Tianlang Lan, Chengfei Jiang, Xiaofan Luo, Wentao An

“…In this research, backscattering coefficients were combined with FD, H/A/α, and MRSD polarization features to create eight feature combinations for comparative analysis. Three machine learning algorithms, Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machines (SVM), were also used for the comparative analysis. …”
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The Mediating Role of Self-Efficacy and Outcome Expectations in the Relationship Between Peer Context and Academic Engagement: A Social Cognitive Theory Perspective by Getachew Tassew Woreta, Girum Tareke Zewude, Krisztián Józsa

“…The results of the path analysis demonstrated a good model-data fit. Peers’ academic norms, educational aspirations, and effort socialization positively predicted academic engagement. …”
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CHANGES IN THE TRENDS IN THE USE OF INFORMATION AND COMMUNICATION TOOLS FOR FUTURE PROFESSIONAL AND TECHNOLOGICAL EDUCATION SPECIALISTS by Юрій Туранов, Володимир Рак, Ірина Луцик, Юрій Франко

“…The study used theoretical analysis, surveys (questionnaires, interviews), observations, systematization, analysis of data, comparisons, and generalizations. …”
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The synergy amongst factors influencing pre-service science teachers’ perceptions of inclusive education by Eric Appiah-Twumasi, Peter Atakorah Ofori, Benedict Osei-Owusu, Eric Twum Ampofo

“…Qualitative data from the interviews were, however, analysed using thematic analysis. …”
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Using AI for Optimizing Packing Design and Reducing Cost in E-Commerce by Hayder Zghair, Rushi Ganesh Konathala

“…In the first phase, a systematic analysis of current packaging inefficiencies was conducted through secondary data, benchmarking, and cost modeling. …”
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A Time Series Approach to Forecasting Financial Indicators in the Wholesale and Retail Trade by Sylvia Jenčová, Petra Vašaničová, Martina Košíková, Marta Miškufová

“…Forecasting using historical time series data has become increasingly important in today’s world. …”
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Progressive Women's Da'wah Movement in Southeast Sulawesi, Indonesia by Muhammad Alifuddin, Kholil Lur Rochman, Uswatun Hasanah, Wahyu Budiantoro

“…Based on the data and analysis carried out, the following conclusions were obtained: Aisyiyah's da'wah movement was carried out in two patterns, namely: (1). …”
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Gathering requirements for IoT-assisted wellbeing in elementary school—a multi-stakeholder perspective by Karin Brodén, Jonas Andersson, Agnieszka Kitkowska, Awais Ahmad, Peter Mozelius

“…We collected qualitative data through individual interviews and workshops with 25 staff members and a survey from 464 students. …”
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Harnessing artificial intelligence for brain disease: advances in diagnosis, drug discovery, and closed-loop therapeutics by Su-jun Fang, Su-jun Fang, Zhao-di Yin, Qi Cai, Li-fan Li, Peng-fei Zheng, Li-zhen Chen, Li-zhen Chen

“…Recent advancements in artificial intelligence (AI), especially deep learning models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Graph Neural Networks (GNNs), offer powerful new tools for analysis. …”
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Tourism Resource Evaluation Integrating FNN and AHP-FCE: A Case Study of Guilin by Xujiang Qin, Zhuo Peng, Xin Zhang, Xiang Yang

“…In contrast, FNN can effectively improve evaluation accuracy through the adaptive learning mechanism, and it especially shows significant advantages in dealing with tourists’ perception data. …”
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Large-scale activity-based demand generation modeling: A literature review and exploration of potential approaches by Ngoc An Nguyen, Joerg Schweizer, Federico Rupi

“…This paper presents a comprehensive review of existing demand generation models within activity-based frameworks, focusing on various methodologies including constraint-based, utility-based, rule-based, learning-based, and hybrid approaches. A comparative analysis is offered, highlighting their theoretical foundations, data requirements, key outputs, and particularly their applications in large-scale microsimulations. …”
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Benefits and risks of ChatGPT in future education by Baltezarević Radoslav, Baltezarević Ivana

“…ChatGPT analyses enormous volumes of data using machine learning (ML) to offer the necessary content and simply respond to queries in a conversational manner. …”
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Linking Stochastic Resonance With Long Short‐Term Memory Neural Network for Streamflow Simulation Enhancement by Xungui Li, Jian Sun, Qiyong Yang, Yi Tian, Xiaoli Yang

“…Results indicate that SR improves accuracy at approximately 70% of 1,244 stations, particularly in regions with high‐quality data. Comparative analysis shows that incorporating SR enhances the performance of deep learning models, highlighting its potential for improving both global and peak streamflow simulation accuracy. …”
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Management of Zakat Muqayyad to Students Reviewed from Jasser Auda's Theory of Maqasid Syariah by Rizky Fadhilah, Dhiauddin Tanjung, Hasan Matsum

“…Once accumulated, the data were analyzed using a qualitative descriptive analysis method. …”
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Directional migration of recirculating lymphocytes through lymph nodes via random walks. by Niclas Thomas, Lenka Matejovicova, Wichat Srikusalanukul, John Shawe-Taylor, Benny Chain

“…We examine how long different T cells may spend in an individual lymph node by examining data from long term cannulation of blood and efferent lymphatics of a single lymph node in the sheep. …”
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Assessment of Forest Fire Impact and Vegetation Recovery in the Ghalahmah Mountains, Saudi Arabia by Rahmah Al-Qthanin, Rahaf Aseeri

“…The study advances fire ecology research by combining multi-source remote sensing data and machine learning techniques to provide a comprehensive understanding of fire impacts and recovery processes in semi-arid mountainous regions. …”
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A review of SAR tomography by Xin Zhao, Jie Dong, Yanghai Yu, Mingsheng Liao, Lu Zhang, Jianya Gong

“…For the TomoSAR applications of forest, urban, and glacier scenarios, we present their scattering mechanisms using real data and explore their application potentials. Finally, how deep learning and multi-source data fusion enhance TomoSAR imaging and its applications is discussed. …”
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Research Progress on Coarse and Fine Sediment Exchange Near Riverbed by JIN Zhong-wu, LI Shan, LU Jin-you, GUO Xiao-hu

“…This study systematically reviews domestic and international research progress over the past three decades, focusing on the mechanisms of coarse and fine sediment exchange near the riverbed from four aspects: theoretical models, mathematical models, experimental methods, and field data analysis. The results demonstrate that existing theoretical models (e.g., upward flux formulas based on turbulent bursting, energy balance, and diffusion theories) largely depend on empirical assumptions, lack universally applicable mechanism descriptions, and face limitations due to insufficient field data validation. …”
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Emerging insights into thyroid cancer from immunotherapy perspective: A correspondence by Zheng Zhang, Zhao-Nan Zhang, Zhen-Xi Xu, Wen-Yu Luan, Yan-Dong Miao

“…Our study uniquely integrates bibliometric analysis with machine learning to map the evolution of thyroid cancer immunotherapy, emphasizing predictive modeling of emerging therapies and clinical translation. …”
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