Effective tweets classification for disaster crisis based on ensemble of classifiers by Christopher Ifeanyi Eke, Kholoud Maswadi, Musa Phiri, Mulenga, Mohammad Imran, Dekera Kwaghtyo, Akeremale Olusola Collins

“…The proposed approach demonstrates not only high predictive capacity but also scalability for real-time tweet filtering during emergencies. …”
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Imaging genomics of cancer: a bibliometric analysis and review by Xinyi Gou, Aobo Feng, Caizhen Feng, Jin Cheng, Nan Hong

“…It has been widely applied to explore heterogeneity and predict responsiveness and disease progression in cancer. …”
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Clinical Utility of Bladder Cancer Biomarkers by Laura Maria Krabbe, Georgios Gakis, Yair Lotan

“…The need for frequent follow-up, including invasive procedures like cystoscopy, repetitive procedures like transurethral resection of bladder tumors and intravesical instillation therapy in non-muscle invasive stages, as well as systemic treatment with or without radical local treatment in advanced stages, makes bladder cancer one of the most expensive cancers to treat. Prognostic and predictive biomarkers have the potential to fundamentally change bladder cancer treatment algorithms, which may result in improved patient comfort and oncological outcomes and may also decrease the socioeconomic burden of the disease. …”
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High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
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Advanced Soft Computing Ensemble for Modeling Contaminant Transport in River Systems: A Comparative Analysis and Ecological Impact Assessment by Jafar Chabokpour

“…The research employed various techniques, including Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Support Vector Regression (SVR), and Genetic Algorithms (GA), to predict pollutant concentrations and estimate transport parameters. …”
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The Fractality of Sentiment Arcs for Literary Quality Assessment: the Case of Nobel Laureates by Yuri Bizzoni, Pascale Moreira, Mads Rosendahl Thomsen, Kristoffer L. Nielbo

“…To test this hypothesis, we present the results from two studies: (i) a probability distribution test, where we compute the probability of seeing a title from a Nobel laureate at different levels of arc fractality; (ii) a classification test, where we use several machine learning algorithms to measure the predictive power of both sentiment arcs and their fractality measure. …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
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Resolving Covid-19 with Blockchain and AI by Suyogita Singh, Satya Bhushan Verma

“…In that review, many potential blockchain applications were discovered; however, the majority of them were still in their infancy, and it couldn’t yet be predicted how they could contribute to the fight against COVID-19 through the use of platforms, access kinds, and consensus algorithms. …”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Improving survival time and predicting prognosis for distinct molecular profiles is substantial. …”
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Aligned in Human Dignity? Parallel Anthropological Aspects of EU Tech Regulation and Pope Francis’ Teaching on AI by Bernát Török, Ádám Darabos

“…We will highlight four concrete challenges posed by artificial intelligence to the human person (profiling, predictive algorithms, human intervention and manipulation), to which the legislation of the European Union has responded partly on anthropological grounds. …”
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Identification of common genetic variation that modulates alternative splicing. by Jeremy Hull, Susana Campino, Kate Rowlands, Man-Suen Chan, Richard R Copley, Martin S Taylor, Kirk Rockett, Gareth Elvidge, Brendan Keating, Julian Knight, Dominic Kwiatkowski

“…The functional consequences of these SNPs could not be predicted using bioinformatic algorithms. Our findings suggest that phenotypic variation in splicing patterns is determined by the presence of SNPs within flanking introns or exons. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. …”
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Improving Sharpness-Aware Minimization Using Label Smoothing and Adaptive Adversarial Cross-Entropy Loss by Tanapat Ratchatorn, Masayuki Tanaka

“…Recent advances in learning algorithms have identified loss surface sharpness as an effective metric for reducing the generalization gap. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…However, existing SAR ship detection algorithms encounter two major challenges: limited detection accuracy and high computational cost, primarily due to the wide range of target scales, indistinct contour features, and complex background interference. …”
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Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
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AIoT-Driven Human Activity Recognition for Versatile Framework on Multipurpose Applications by Nanik Triwahyuni, Eni Wardihani, Aminuddin Rizal, Samuel Beta, Ricky Sambora, Rindang Oktaviani

“…The framework integrates sensor data from wearable IoT devices, which is then processed by AI algorithms to classify and predict human activities in real-time. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…Additionally, RE and parametric modeling could assist in creating durable, cost-effective alternatives, and predicting appropriate replacements.…”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

“…Four machine learning algorithms (Random Forest, Support Vector Classification, Gradient Boosting, and Extremely Randomized Tree Classifier) were applied to create eight classification models based on bacterial abundance at the genus level and KEGG pathways. …”
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COVID-19 REINFECTION: DOES IT MATTER? by E. Füsun Karaşahin, Ömer Karaşahin, Mehtap Hülya Aslan

“…Conclusion: This study demonstrated that the frequency of COVID-19 reinfection is higher than predicted. The complex algorithms recommended by international health institutions make it difficult to detect these cases. …”
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Hydrologic model calibration approaches for highly regulated river basin: A comprehensive assessment by Md Rasel Sheikh, Paulin Coulibaly

“…The study highlights the challenges of using reservoir outflow as an operational control, which leads to poor water level predictions, reinforcing the need for more region-specific operational constraints. …”
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