Mapping the Evolution of Corporate Social Responsibility Research (2015–2024): A Bibliometric Analysis Based on Scopus by Cristyano Cristyano, Suryadi Suryadi, Riyanto Riyanto

“…The objective is to map the intellectual evolution of CSR scholarship by identifying key thematic shifts, dominant theoretical frameworks, and methodological patterns. Using VOSviewer as the primary visualization tool, the study explores research networks, keyword co-occurrences, and temporal transitions in CSR literature over the past decade. …”
Get full text

Automated violence monitoring system for real-time fistfight detection using deep learning-based temporal action localization by Baolong Qi, Baoyuan Wu, Bailing Sun

“…The proposed framework leverages both Context-Aware Encoded Transformer (CAET) for modeling interactions between individuals and their environment and Spatial–Temporal Graph Convolutional Networks (ST-GCN) for capturing intra-person and inter-person dynamics from skeletal data. …”
Get full text

Tourist Destination Recommendations Using Deep Learning by Amarita Ritthipakdee, Chartchai Leenawong

“…The model employs Neural Collaborative Filtering (NCF), utilizing deep neural networks to capture complex, non-linear patterns between users and destinations, surpassing the limitations of traditional matrix factorization methods. …”
Get full text

Optimizing Supply Chain Resilience Using Advanced Analytics and Computational Intelligence Techniques by Jie Xu, Lixing Bo

“…LSTM’s strength in capturing complex temporal patterns is utilized to predict demand with high precision, while PSO is employed to optimize various supply chain components, including inventory management, transportation, and production planning. …”
Get full text

Educational Reforms and Healthcare Competitiveness through Data-Driven Analysis by Artem Artyukhov, Olha Yeremenko, Nadiia Artiukhova, Artur Lapidus, Olena Churikanova, Kseniia Bliumska-Danko

Get full text

Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through cross-validation. A contextual clinical variable indicating recent SARS-CoV-2 infection was incorporated into 1 model configuration to assess its impact on classification performance. …”
Get full text

Human-Centric Cognitive State Recognition Using Physiological Signals: A Systematic Review of Machine Learning Strategies Across Application Domains by Kaizhe Jin, Adrian Rubio-Solis, Ravi Naik, Daniel Leff, James Kinross, George Mylonas

“…This systematic review analyses advancements in cognitive state recognition from 2010 to early 2024, evaluating 405 relevant articles from an initial pool of 2398 records identified through five databases: Scopus, Engineering Village, Web of Science, IEEE Xplore, and PubMed. …”
Get full text

Revolutionizing Utility of Big Data Analytics in Personalized Cardiovascular Healthcare by Praneel Sharma, Pratyusha Sharma, Kamal Sharma, Vansh Varma, Vansh Patel, Jeel Sarvaiya, Jonsi Tavethia, Shubh Mehta, Anshul Bhadania, Ishan Patel, Komal Shah

“…The term “big data analytics (BDA)” defines the computational techniques to study complex datasets that are too large for common data processing software, encompassing techniques such as data mining (DM), machine learning (ML), and predictive analytics (PA) to find patterns, correlations, and insights in massive datasets. …”
Get full text

Fiber Sensing in the 6G Era: Vision Transformers for <i>ϕ</i>-OTDR-Based Road-Traffic Monitoring by Robson A. Colares, Leticia Rittner, Evandro Conforti, Darli A. A. Mello

“…We apply vision transformers (ViTs) in a distributed fiber-optic sensing system to evaluate road traffic parameters in smart cities. Convolutional neural networks (CNNs) are also assessed for benchmarking. …”
Get full text

Deep Learning-Based Cascaded Light Source Detection for Link Alignment in Underwater Wireless Optical Communication by Bowen Jia, Wenmin Ge, Jingxuan Cheng, Zihao Du, Renming Wang, Guangbin Song, Yufan Zhang, Chengye Cai, Sitong Qin, Jing Xu

“…In this paper, deep neural networks (DNNs) with strong feature extraction capabilities are introduced to automatically learn the patterns of the light source from diverse images. …”
Get full text

Epigenetic regulation of histone modifications in glioblastoma: recent advances and therapeutic insights by Li Zhang, Yang Yang, Yanchu Li, Chenyu Wang, Chenbin Bian, Hongbin Wang, Feng Wang

“…These challenges are attributed to the complexity of histone modification networks and the adaptive responses of the tumor microenvironment. …”
Get full text

Emerging research themes in ferroptosis research for non-small cell lung cancer: a bibliometric and visualized analysis by Wenbo Zhang, Wenbo Zhang, Wenbo Zhang, Wenbo Zhang, Jianwei Gu, Jianwei Gu, Jianwei Gu, Jianwei Gu, Yong Chen, Guolu Jiang, Diego Gonzalez-Rivas, Diego Gonzalez-Rivas, Minjie Ma, Chang Chen, Chang Chen, Chang Chen

“…Bibliometric tools including VOSviewer, CiteSpace, and GraphPad Prism were used to analyze publication trends, citation patterns, collaborative networks, and research hotspots. …”
Get full text

Comparative Study of Cell Nuclei Segmentation Based on Computational and Handcrafted Features Using Machine Learning Algorithms by Rashadul Islam Sumon, Md Ariful Islam Mozumdar, Salma Akter, Shah Muhammad Imtiyaj Uddin, Mohammad Hassan Ali Al-Onaizan, Reem Ibrahim Alkanhel, Mohammed Saleh Ali Muthanna

“…Conversely, CNN-based features are automatically acquired representations that identify complex patterns in nuclei images. To assess how effectively these techniques segment cell nuclei, their performance is evaluated. …”
Get full text

Study protocol for a multi-session randomized sham-controlled trial of PCC- and amygdala-targeted neurofeedback for the treatment of PTSD by Jonathan M. Lieberman, Ruth A. Lanius, Jean Théberge, Benicio N. Frey, Paul A. Frewen, Frank Scharnowski, David Steyrl, Tomas Ros, Maria Densmore, Emma Tassinari, Vangel Matic, Niki Hosseini-Kamkar, Sandhya Narikuzhy, Fardous Hosseiny, Rakesh Jetly, Andrew A. Nicholson

“…Neural outcomes will also be examined, focusing on brain activation and connectivity patterns. Additionally, qualitative interviews and actigraphy will assess participants’ subjective experiences and track sleep and physical activity patterns. …”
Get full text

Multimodal Explainability Using Class Activation Maps and Canonical Correlation for MI-EEG Deep Learning Classification by Marcos Loaiza-Arias, Andrés Marino Álvarez-Meza, David Cárdenas-Peña, Álvaro Ángel Orozco-Gutierrez, German Castellanos-Dominguez

“…On the GIGAScience MI dataset, experiments show that shallow neural networks are good at classifying MI-EEG data, while the CAM-based method finds spatio-frequency patterns. …”
Get full text

Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review by Vishal Gaurav, Chander Grover, Mehul Tyagi, Suman Saurabh

“…AI algorithms, particularly deep convolutional neural networks (CNNs), have demonstrated high sensitivity and specificity in interpreting nail images, aiding differential diagnosis as well as enhancing the efficiency of diagnostic processes in a busy clinical setting. …”
Get full text

Causal knowledge graph construction for enterprise innovation events in the digital economy and its application to strategic decision-making by Pengfei Wu, Bingtao Xu, Xuhan Zhang

“…We introduce a new architecture that integrates pre-trained language encoders and graph neural networks to jointly model event contexts and global causal structure. …”
Get full text

Machine Learning Approaches to Predict No-Shows in Saudi Arabian Primary and General Healthcare Settings by Abdulrahman Alshehri, Abdullah Saeed, Abdullah AlShafea, Sabah Althubiany, Mohammed Alshehri, Amer Alzahrani, Khalid Hakami, Lamia Ibrahim, Abdulrahim Alshehri, Rana Alamri

“…Machine learning models, such as decision trees, random forests, Naive Bayes, logistic regression, and artificial neural networks (ANN), have been developed and evaluated based on accuracy, precision, recall, F1 score, and area under the curve (AUC). …”
Get full text

Patients’ preferences on atopic dermatitis skincare and social media use: a qualitative study by Roxana Mazilu, Stefanie Ziehfreund, Stephan Traidl, Alexander Zink

“…Conclusions Patients exhibit diverse patterns of SM use when selecting daily products and critically evaluate the online content, demonstrating a greater trust in healthcare professionals or familial connections. …”
Get full text

THE INVERSE GAUSSIAN PLUME METHOD FOR ESTIMATING THE LEVEL OF AIR POLLUTION by Volodymyr Hura, Liubomyr Monastyrskyi

“…Its demonstrated predictive capability makes it an asset for enhancing environmental monitoring programs, potentially supplementing fixed monitoring networks and identifying areas of concern. Furthermore, the model's utility extends significantly into the domain of regulatory compliance, facilitating environmental impact assessments for proposed industrial activities and evaluating the effectiveness of emission control measures.…”
Get full text