Discovering opioid slang on social media: A Word2Vec approach with reddit data by E. Holbrook, B. Wiskur, Z. Nagykaldi

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Exploring the factors affecting the motivation for learning from the perspective of public health students: A qualitative study by Leila Allahqoli, Vinnaras Nithyanantham, Azam Rahmani, Azra Allahveisi, Reza Ghanei Gheshlagh, Arezoo Fallahi, Babak Nemat-Shahrbabaki

“…Despite the significant role of motivation in achieving success among public health students, students often do not demonstrate adequate motivation for learning and education. This study was performed to determine factors affecting the motivation for learning from the perspective of public health students via content analysis approach. …”
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An Encoder-Only Transformer Model for Depression Detection from Social Network Data: The DEENT Approach by Robinson Narvaez Burbano, Oscar Mauricio Caicedo Rendon, Carlos. A. Astudillo

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ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI by Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu

“…Moreover, current studies usually focus on analyzing fMRI using conventional machine learning models that rely on human-engineered fMRI features, without investigating deep learning models that can automatically learn data-driven fMRI representations. …”
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Integrative analysis of cell state changes in lung fibrosis with peripheral protein biomarkers by Christoph H Mayr, Lukas M Simon, Gabriela Leuschner, Meshal Ansari, Janine Schniering, Philipp E Geyer, Ilias Angelidis, Maximilian Strunz, Pawandeep Singh, Nikolaus Kneidinger, Frank Reichenberger, Edith Silbernagel, Stephan Böhm, Heiko Adler, Michael Lindner, Britta Maurer, Anne Hilgendorff, Antje Prasse, Jürgen Behr, Matthias Mann, Oliver Eickelberg, Fabian J Theis, Herbert B Schiller

“…We further discovered CRTAC1 as a biomarker of alveolar type‐2 epithelial cell health status in lavage fluid and plasma. Using cross‐modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.…”
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Multidimensional perspectives of geo-epidemiology: from interdisciplinary learning and research to cost–benefit oriented decision-making by S. D. Smith, E. M. Geraghty, A. L. Rivas, F. O. Fasina, F. O. Fasina, M. Kosoy, L. Malania, A. L. Hoogesteijn, J. M. Fair

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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

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Wind power prediction using stacking and transfer learning by Xu Cheng, Yu Cao, Zhiyuan Song, Chenguang Zhang

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Statewide Forest Canopy Cover Mapping of Florida Using Synergistic Integration of Spaceborne LiDAR, SAR, and Optical Imagery by Monique Bohora Schlickmann, Inacio Thomaz Bueno, Denis Valle, William M. Hammond, Susan J. Prichard, Andrew T. Hudak, Carine Klauberg, Mauro Alessandro Karasinski, Kody Melissa Brock, Kleydson Diego Rocha, Jinyi Xia, Rodrigo Vieira Leite, Pedro Higuchi, Ana Carolina da Silva, Gabriel Maximo da Silva, Gina R. Cova, Carlos Alberto Silva

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Case Studies of Survival Analysis for Predictive Maintenance in Manufacturing by Selver Softic, Bahrudin Hrnjica

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Evaluation Method of Innovative Education Model of E-Commerce Video Live Broadcast Based on Big Data Analysis Technology by Huili Liu, Ou Bai

“…This paper takes student evaluation data and student online learning data as research objects. …”
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Increasing Public Interest in Online Education during the COVID-19 Pandemic in the United States: An Analysis of Google Trends Data by Qinyi Tan, Ziqi Zhang, Luyan Teng

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Estimation of the compressive strength of ultrahigh performance concrete using machine learning models by Rakesh Kumar, Divesh Ranjan Kumar, Warit Wipulanusat, Chanachai Thongchom, Pijush Samui, Baboo Rai

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Automated Root Cause Analysis of Network Failures in IP/MPLS Network Using Machine Learning and Case-Based Reasoning by Tikumporn Wankvar, Apichon Witayangkurn

“…The system integrates Apache Kafka as a high-throughput message broker to enable real-time processing of SNMP Traps and Syslog data. Additionally, a case-based fault identification service automates fault analysis and provides actionable insights via an interactive dashboard and a notification system that delivers alerts through modern messaging platforms. …”
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The sociopolitical discourse on health data sharing in Switzerland: lessons learned from 1992 to 2023 for present public trust building – a multi-method study by Federica Zavattaro, Paola Daniore, Viktor von Wyl, Felix Gille

“…METHODS: We designed a multi-method study comprising (A.I) a thematic analysis of online interviews with key stakeholders and (A.II) a scoping review of expert opinion papers to capture expert perspectives; (B) a policy analysis of government policies to comprehend the political trajectory of the health data sharing discourse; and (C) an analysis of news articles across eight major Swiss newspapers to trace the evolution of the media narrative around data sharing. …”
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Policy brief: Improving national vaccination decision-making through data by Sandra Evans, Joe Schmitt, Dipak Kalra, Tomislav Sokol, Daphne Holt

“…Rapid strides in artificial intelligence, such as machine learning and natural language processing, can enhance data analysis, conceptual modelling, and real-time surveillance. …”
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Unlocking Retail Insights: Predictive Modeling and Customer Segmentation Through Data Analytics by Juan Tang

“…Exploratory data analysis (EDA) findings indicated dramatic changes in sales and revenue, activities, and customer interactions, and products. …”
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Modeling Groundwater Resources in Data-Scarce Regions for Sustainable Management: Methodologies and Limits by Iolanda Borzì

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A data augmentation procedure to improve detection of spike ripples in brain voltage recordings by Emily D. Schlafly, Daniel Carbonero, Catherine J. Chu, Mark A. Kramer

“…Despite advancements, dataset heterogeneity and scarcity severely limit machine learning performance. Our study explores long-short term memory (LSTM) neural network architectures for spike ripple detection, leveraging data augmentation to improve classifier performance. …”
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Machine learning algorithm to predict in-hospital mortality after aneurysmal subarachnoid hemorrhage by Juri V. Kivelev, Alexey L. Krivoshapkin, Albert A. Sufianov

“…Machine learning (ML) methodology surpasses the traditional tools of statistical analysis in processing big data clinical datasets .Aim. …”
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