Exploring the role of repetitive negative thinking in the transdiagnostic context of depression and anxiety in children by Kuiliang Li, Lei Ren, Xiao Li, Chang Liu, Xuejiao Tan, Ming Ji, Xi Luo

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Prediction of risk for acute kidney injury and its progression to mortality in obese patients admitted to ICU postoperatively by LI Qiang, LI Qiang, MU Guo, MU Guo, WANG Wenzhang

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Application of Quantitative Interpretability to Evaluate CNN-Based Models for Medical Image Classification by Nuan Cui, Yingjie Wu, Guojiang Xin, Jiaze Wu, Liqin Zhong, Hao Liang

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

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A Machine Learning Approach for Predicting Maternal Health Risks in Lower-Middle-Income Countries Using Sparse Data and Vital Signs by Avnish Malde, Vishnunarayan Girishan Prabhu, Dishant Banga, Michael Hsieh, Chaithanya Renduchintala, Ronald Pirrallo

“…The ensemble model using stratified sampling achieved the highest accuracy (87.2%), outperforming CatBoost (84.7%), XGBoost (84.2%), random forest (81.3%) and decision trees (80.3%) without stratified sampling. …”
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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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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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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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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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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…The dataset underwent 7:3 stratified partitioning for training and testing cohorts. …”
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Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members by Nataly Buslón, Davide Cirillo, Oriol Rios, Simón Perera del Rosario

“…ResultsAnalysis of the focus group discussions revealed several critical barriers impacting the integration of AI in personalized medicine for trans people, including concerns around data privacy, biases in algorithmic decision-making, and the lack of tailored health care data reflective of trans experiences. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

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Enhanced supervised classification of seasonal pastures on the Qinghai-Tibet Plateau (1990–2020) using Landsat optimal time window by Panfei Fang, Jia Wang, Haifeng Xu, Ruonan Li, Long Yu, Shaodong Huang, Yuying Liang, Pengfei Zheng

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Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications by Sita Rani, Raman Kumar, B. S. Panda, Rajender Kumar, Nafaa Farhan Muften, Mayada Ahmed Abass, Jasmina Lozanović

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Immune transcriptomic analysis on COVID-19 patients with varying clinical presentations identifies severity markers by Abdallah Musa Abdallah, Hifzur Rahman Ansari, Muhammad Shuaib, Asmma Doudin, Hadi M. Yassine, Syed Shahab Ud Din Shah, Fayaz Ahmad Mir, Mohamed M. Emara, Abdel-Naser Elzouki, Farhan S. Cyprian

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Lymph node metastasis in patients with hepatocellular carcinoma using machine learning: a population-based study by Li Yuqin, Li Yuqin, Li Hongyan, Li Hongyan, Li Hongyuan, Li Tingting, He Kun, Fang Jie, Han Yunhui

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Application of Artificial Intelligence Large Language Model in Power Equipment Operation and Maintenance by Xiaohong Chen, Wenrun Fu, Chaoming Liu, Zehong Liu, Junpeng Li, Zhiliang Hu, Dongbin Hu

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