A novel ensemble Wasserstein GAN framework for effective anomaly detection in industrial internet of things environments by Rubina Riaz, Guangjie Han, Kamran Shaukat, Naimat Ullah Khan, Hongbo Zhu, Lei Wang

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PneuX-Net: An Enhanced Feature Extraction and Transformation Approach for Pneumonia Detection in X-Ray Images by Kashif Munir, Muhammad Usama Tanveer, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman

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Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction by Bahram Shahri, Ali Tajik, Mohsen Moohebati, Vahid Mahdavizadeh

“…While STOP-BANG was higher in event patients, risk group classification was non-significant (p = 0.3). Three models were trained: (1) all selected features, (2) GRACE alone, and (3) GRACE + STOP-BANG. …”
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Tumor ViT-GRU-XAI: Advanced Brain Tumor Diagnosis Framework: Vision Transformer and GRU Integration for Improved MRI Analysis: A Case Study of Egypt by Mohammed Aly, Abdullatif Ghallab, Islam S. Fathi

“…After processing the dataset and training our model, we achieved notable performance metrics: a precision of 98.8%, recall of 98.4%, and F1-score of 98.3%. …”
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Adopting Land Cover Standards for Sustainable Development in Ghana: Challenges and Opportunities by Elisha Njomaba, Fatima Mushtaq, Raymond Kwame Nagbija, Silas Yakalim, Ben Emunah Aikins, Peter Surovy

“…The classification achieved an overall accuracy of 90%, showing the robustness of the RF model for land cover mapping in a heterogeneous landscape such as Ghana. …”
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Accelerated and accurate cervical cancer diagnosis using a novel stacking ensemble method with explainable AI by Md Ismail Hossain Siddiqui, Shakil Khan, Zishad Hossain Limon, Hamdadur Rahman, Mahbub Alam Khan, Abdullah Al Sakib, S M Masfequier Rahman Swapno, Rezaul Haque, Ahmed Wasif Reza, Abhishek Appaji

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Integrated artificial intelligence approach for well-log fluid identification in dual-medium tight sandstone gas reservoirs by Wurong Wang, Wurong Wang, Linbo Qu, Linbo Qu, Dali Yue, Dali Yue, Wei Li, Wei Li, Junlong Liu, Wujun Jin, Jialin Fu, Jialin Fu, Jiarui Zhang, Jiarui Zhang, Dongxia Chen, Dongxia Chen, Qiaochu Wang, Qiaochu Wang, Sha Li, Sha Li

“…Reservoir classification based on geological genetic mechanism significantly reduces data noise and prediction ambiguity, thereby improving the efficiency of model training.DiscussionThe final model is constructed by an ensemble method that integrates multiple sub-models, including fuzzy C-means clustering (FCM), gradient boosting decision tree (GBDT), backpropagation neural network (BPNN), random forests (RF), and light gradient boosting machines (LightGBM). …”
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Sentiment Analysis of Public Comments on X Social Media Related to Israeli Product Boycotts Using The Long Short-Term Memory (LSTM) Method by Pitra Rahmadani Panggabean, Asrianda Asrianda, Hafizh Al-Kausar Aidilof

“…LSTM was chosen for this analysis due to its superior ability to process sequential data like text and effectively capture long-term dependencies in natural language, which is crucial for accurate sentiment classification. Data was processed through preprocessing steps, sentiment labeling, and Term Frequency-Inverse Document Frequency (TF-IDF) weighting before being fed into the LSTM model. …”
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Artificial Intelligence in Recordkeeping by Sigit Sumarsono, Muhamad Prabu Wibowo

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A Comparison of Approaches for Handling Concept Drifts in Data Processed With Machine Learning by Emanuel Valerio Pereira, Wendley Souza da Silva

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The Influence of Domestic Players on the Success in National and International Competitions in Football by Michal Varmus, Pavol Boško, Roman Adámik, Dominika Toman, Zakaria Elkhwesky

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Comparative Analysis of Random Forest and Logistic Regression Methods in Predicting Leukemia Blood Cancer Using Microscopic Blood Cell Images by Jepri Banjarnahor, Galuh Wira Relungwangi

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Private Collaborative Edge Inference via Over-the-Air Computation by Selim F. Yilmaz, Burak Hasircioglu, Li Qiao, Deniz Gunduz

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Identification of unknown operating system type of Internet of Things terminal device based on RIPPER by Shichang Xuan, Dapeng Man, Wu Yang, Wei Wang, Jiashuai Zhao, Miao Yu

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Decomposition of Fuzzy Soft Sets with Finite Value Spaces by Feng Feng, Hamido Fujita, Young Bae Jun, Madad Khan

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Combining a Risk Factor Score Designed From Electronic Health Records With a Digital Cytology Image Scoring System to Improve Bladder Cancer Detection: Proof-of-Concept Study by Sandie Cabon, Sarra Brihi, Riadh Fezzani, Morgane Pierre-Jean, Marc Cuggia, Guillaume Bouzillé

“…Second, we investigated 3 strategies (logistic regression, decision tree, and a custom strategy based on score interpretation) to combine the model’s score with the score from an image-based model to produce a robust bladder cancer scoring system. …”
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Towards trustworthy AI-driven leukemia diagnosis: A hybrid Hierarchical Federated Learning and explainable AI framework by Khadija Pervez, Syed Irfan Sohail, Faiza Parwez, Muhammad Abdullah Zia

“…The framework trains EfficientNetB3 for the classification of leukemia cells and incorporates explainability techniques to make decisions of the underlying model transparent and interpretable. …”
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A Systematic Literature Review of Digital Twin Research for Healthcare Systems: Research Trends, Gaps, and Realization Challenges by Md. Doulotuzzaman Xames, Taylan G. Topcu

“…Our findings are structured around three research questions aimed at identifying: (i) current research trends, (ii) gaps, and (iii) realization challenges. …”
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Surface water quality assessment for drinking and pollution source characterization: A water quality index, GIS approach, and performance evaluation utilizing machine learning anal... by Abhijeet Das

“…Evaluating the effectiveness and dependability of classification algorithms in identifying changes in water quality is crucial since accurate information is required to improve decision-making. …”
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Improving National Forest Mapping in Romania Using Machine Learning and Sentinel-2 Multispectral Imagery by Mohamed Islam Keskes, Aya Hamed Mohamed, Stelian Alexandru Borz, Mihai Daniel Niţă

“…This comprehensive approach to ground data collection, supplemented by an independent dataset from Brasov County collected using the same protocols, allowed for robust training and validation of the machine learning models. This study evaluates the performance of three machine learning algorithms—Random Forest (RF), Classification and Regression Trees (CART), and the Gradient Boosting Tree Algorithm (GBTA)—in predicting the forest attributes from Sentinel-2 satellite imagery. …”
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