Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…This research represents the first comprehensive application of ML techniques to WDE incubation period prediction, establishing a methodological framework that integrates experimental data, statistical analysis, and advanced ML algorithms. Unlike previous approaches, our methodology (1) systematically evaluates multiple ML algorithms and transformation techniques for WDE prediction, (2) provides quantitative assessment of feature importance that aligns with physical understanding of erosion mechanisms, (3) demonstrates superior predictive accuracy compared to traditional empirical models, and (4) offers a generalizable approach applicable across different metallic materials and impact conditions. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

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Self-Organizing TDMA: A Distributed Contention-Resolution MAC Protocol by Mahsa Derakhshani, Yahya Khan, Duc Tuong Nguyen, Saeedeh Parsaeefard, Atoosa Dalili Shoaei, Tho Le-Ngoc

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COMPARATIVE CHARACTERISTICS OF BIOMATERIALS FOR THE REPLACEMENT OF JAW BONE DEFECTS AND THEIR ROLE IN THE PREVENTION OF INFLAMMATORY COMPLICATIONS by V.M. Havryliev, A.V. Kopchak, N.B. Kuzniak, D.V. Steblovski, O.A. Toropov, P.I. Yatsenko

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The impact of artificial intelligence on financial auditing: the case of Algeria by Amira Benachour, Ramzi Kaddai, Hanane Abdelmalek, Fella Bochelgoum, Lamine Tarhlissia

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Model of Interaction of Structural Elements of the Financial Market of Ukraine by Kochorba Valeriia Yu.

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Using baseline MRI radiomics to predict the tumor shrinkage patterns in HR-Positive, HER2-Negative Breast Cancer by Lijia Wang, Yongchen Wang, Li Yang, Jialiang Ren, Qian Xu, Yingmin Zhai, Tao Zhou

“…Radiomics features were extracted and analyzed using machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). …”
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MCOA: A Comprehensive Multimodal Dataset for Advancing Deep Learning in Corneal Opacity Assessment by Xinyu Ma, Jianxia Fang, Yaqi Wang, Zhichao Hu, Zhe Xu, Sha Zhu, Weijia Yan, Mengqi Chu, Jingwei Xu, Siting Sheng, Chujun Liu, Mingxuan Zhang, Ce Shi, Gangyong Jia, Wen Xu

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Machine learning for prediction of Helicobacter pylori infection based on basic health examination data in adults: a retrospective study by Qiaoli Wang, Tao Liang, Yuexi Li, Peng Zhou, Xiaoqin Liu

“…Six distinct machine learning algorithms were utilized to construct the predictive models, and their performance was comprehensively evaluated. …”
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Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

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Use machine learning to predict treatment outcome of early childhood caries by Yafei Wu, Maoni Jia, Ya Fang, Duangporn Duangthip, Chun Hung Chu, Sherry Shiqian Gao

“…Methods This study was a secondary analysis of a recently published clinical trial that recruited 1,070 children aged 3- to 4-year-old with ECC. Machine learning algorithms including Naive Bayes, logistic regression, decision tree, random forest, support vector machine, and extreme gradient boosting were adopted to predict the caries-arresting outcome of ECC at 30-month follow-up after receiving fluoride and silver therapy. …”
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Are Artificial Intelligence Models Listening Like Cardiologists? Bridging the Gap Between Artificial Intelligence and Clinical Reasoning in Heart-Sound Classification Using Explain... by Sami Alrabie, Ahmed Barnawi

“…First, we observed that automatic heart-sound segmentation algorithms—commonly used for data augmentation—produce varying outcomes, raising concerns about the accuracy of both the segmentation process and the resulting classification performance. …”
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Age- and Post-Based Complex Analyses of Heart Rate Variability in Young Male Handball Players for Potential Prevention of Overload-induced Injuries by Zita Petrovszki, Olivér Czimbalmos, Vera Gal, Gabor Korosi, Edit Nagy, Rita Mikulan, Gyongyi Horvath

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Digital Twin-Assisted Load-Balanced User Association and AoI-Aware Scheduling in IoT Networks by Ahmed Shaharyar Khwaja, Nhat Tri Vo, Williams-Paul Nwadiugwu, Isaac Woungang, Alagan Anpalagan

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The Application and Ethical Implication of Generative AI in Mental Health: Systematic Review by Xi Wang, Yujia Zhou, Guangyu Zhou

“…However, to ensure ethical and effective implementation, comprehensive safeguards—particularly around privacy, algorithmic bias, and responsible user engagement—must be established.…”
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Key gene screening and diagnostic model establishment for acute type a aortic dissection by Yue Pan, Zhiming Yu, Xiaoyu Qian, Xuesong Zhang, Qun Xue, Weizhang Xiao

“…The nomogram model exhibited high diagnostic precision (AUC=0.935, 95% CI: 0.908–0.963), supported by calibration and decision curve analyses.ConclusionThis study identifies key molecular markers and pathways in ATAAD pathogenesis, emphasizing the role of immune dysregulation and extracellular matrix remodeling. …”
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Prepartum Vaccination Against Neonatal Calf Diarrhea and Its Effect on Mammary Health and Milk Yield of Dairy Cows: A Retrospective Study Addressing Non-Specific Effects of Vaccina... by Caroline Kuhn, Holm Zerbe, Hans-Joachim Schuberth, Anke Römer, Debby Kraatz-van Egmond, Claudia Wesenauer, Martina Resch, Alexander Stoll, Yury Zablotski

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Artificial Intelligence in Revolutionizing Kidney Care and Beyond: Kid-AI Revolution by Kounaina Khan, Farhan Zameer, Pratheek Jain, Ravi KR, Vidya Niranjan, Manoj S, Ravish H, Subrahmanya Padyana

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Optimization and image quality in CT studies: application of DRLs based on clinical indication by Carmine Picone, Annamaria Porto, Roberta Fusco, Claudio Granata, Maria Chiara Brunese, Vincenza Granata, Alessandro Ottaiano, Marialuisa Barretta, Ferdinando Caranci, Biagio Pecori, Eugenio Sorgente, Sergio Salerno, Raffaella Mormile, Fabio Pinto, Antonio Pinto, Andrea Magistrelli, Antonella Petrillo

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Large Language Models in Transportation: A Comprehensive Bibliometric Analysis of Emerging Trends, Challenges, and Future Research by Mahbub Hassan, Md. Emtiaz Kabir, Muzammil Jusoh, Hong Ki An, Michael Negnevitsky, Chengjiang Li

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