A practical study of artificial intelligence-based real-time feedback in online physical education teaching by Jiewei Ma, Lianzhen Ma, Shilong Qi, Bo Zhang, Wenpian Ruan

“…Future research should focus on optimizing algorithms and integrating adaptive learning to create more effective OLPE strategies.…”
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Moving Vehicles Detection and Tracking on Highways and Transportation System for Smart Cities by Manoj Kumar, Susmita Ray, Dileep Kumar Yadav

“…The real-time video surveillance system has become an integral part of our life and Highways play a very crucial role in transportation. …”
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Early Perspectives on the Planned Brazilian Program to Address Ship-Sourced Pollution by Daniel Constantino Zacharias, Angelo Teixeira Lemos

“…The system incorporates a range of technologies, such as satellite data, AI algorithms, autonomous sensors, and high-resolution modeling, to detect and respond to oil spills and maritime threats. …”
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Use of artificial intelligence to assess genetic predisposition to develop critical COVID-19 disease: a comparative study of machine learning models by Martín Pérez Salomón, Sanchez Jimenez Flora, Fuentes Cantero Sandra, Jímenez Barragan Marta, Sanchez Mora Catalina, Borreguero Leon Juan M., Teresa Arrobas Velilla, Valido Morales Agustín, Delgado Torralbo Juan A., León Justel Antonio

“…Clinical data, laboratory data and genetic polymorphisms were integrated into AI models to compare the performance of different machine learning algorithms.…”
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Safety of creatine supplementation: a scientometrics analysis on the impact of the ‘Creatine For Health’ initiative and introduction to CREAS by Diego A. Bonilla, Drew E. Gonzalez, Gustavo Humeres, Jisun Chun, Kelly Hines, Adriana Gil, Richard B. Kreider

“…These big data text mining and social network analyses are part of the Creatine Research and Information System (CREAS), a project that integrates bibliometrics, scientometrics, and other AI-assisted analyses.Results A total of 129,782 comments were collected from YouTube videos published between April 2011 and February 2025 that included “creatine” in their title or description. …”
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Evaluating the Predictive Power of Software Metrics for Fault Localization by Issar Arab, Kenneth Magel, Mohammed Akour

“…We fitted thousands of models and benchmarked different algorithms—including deep learning, Random Forest, XGBoost, and LightGBM—to choose the best-performing model. …”
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A comprehensive survey of cyberattacks on EVs: Research domains, attacks, defensive mechanisms, and verification methods by Tawfiq Aljohani, Abdulaziz Almutairi

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The evolving role of programming and LLMs in the development of self-driving laboratories by John R. Kitchin

“…To address this, we introduce Claude-Light, a lightweight, remotely accessible instrument designed for prototyping automation algorithms and machine learning workflows. Claude-Light integrates a REST API, a Raspberry Pi-based control system, and an RGB LED with a photometer that measures ten spectral outputs, providing a controlled but realistic experimental environment. …”
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Lung Cancer Prediction Using an Enhanced Neutrosophic Set Combined with a Machine Learning Approach by Vakeel A. Khan, Asheesh Kumar Yadav, Mohammad Arshad, Nadeem Akhtar

“…To address this issue, we propose an Enhanced Neutrosophic Set (ENS) framework integrated with machine learning algorithms to improve the prediction accuracy of lung cancer. …”
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BREAST-CAD: A Computer-Aided Diagnosis System for Breast Cancer Detection Using Machine Learning by Riyam M. Masoud, Ramadan Madi Ali Bakir, M. Sabry Saraya, Sarah M. Ayyad

“…In the final phase, the DT model was embedded within a user-friendly client application, empowering clinicians to input patient diagnostic data directly and receive immediate, AI-driven predictions of cancer probability, with results securely transmitted and managed by a dedicated server, facilitating remote access and centralized data storage and ensuring data integrity.…”
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Towards Economic Sustainability: A Comprehensive Review of Artificial Intelligence and Machine Learning Techniques in Improving the Accuracy of Stock Market Movements by Atoosa Rezaei, Iheb Abdellatif, Amjad Umar

“…This study examines the incorporation of artificial intelligence (AI) and machine learning (ML) technologies to address gaps in identifying predictive factors, integrating diverse data sources, and optimizing methodologies. …”
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Thermal damage detection of EAST internal component based on machine learning by Zhongfang Guan, Bin Zhang, Jian Liu, Jinping Qian, Xianzu Gong, Runze Chen, Zuhao Wang, Binfu Gao, Yutong Guo, Chuannan Xuan, Cong Cao, Tianqi Jia, Pan Li, Wenbin Liu, Wei Wang, Yunchan Hu, Yifan He, Kangjia Yang, Wenyi Lu, Chunyu He, the EAST team

“…This problem- oriented approach significantly improves the operational safety and stability of the EAST device by enabling early detection of thermal events. The AI-based detection method provides a new solution to safeguarding the fusion device, while also offering potential avenues for integrating artificial intelligence technologies into EAST feedback control and operating systems in the future.…”
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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

“…This study recommends future research to focus on integrating spatial-temporal data, implementing Explainable AI (XAI), and conducting cross-regional validation to enhance model reliability and policy relevance.…”
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A Comprehensive Survey on Deep Learning in Abdominal Imaging: Datasets, Techniques, and Performance Metrics by Mariem Bellal, Sanaa El Fkihi, Korhan Cengiz, Nikola Ivkovic

“…Ethical considerations, including algorithmic bias, transparency in model development, and equitable patient care, are thoroughly examined to underscore the importance of ethical practices in deploying Artificial Intelligence (AI) technologies in healthcare.…”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…This research not only advances the methodological landscape of fake news detection but also contributes to the broader discourse on safeguarding democratic values, media integrity, and responsible AI deployment in digital environments.…”
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A strategy for network multi-layer information fusion based on multimodel in user emotional polarity analysis by Ronghua Wang, Peng Zhuang

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Methodologies for estimating emissions from road transport and comparison with the inventory air emissions (INEMAR). The case of Pavia Province by Marilisa Moretti, Roberto De Lotto

“…The result should highlight in an “emission based” analysis of land use, the opportunities of integrated mobility new systems.…”
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WDM C-band four channel demultiplexer using cascaded multimode interference on SiN strip waveguide structure by Malka Dror

“…Our design was optimized using AI-enhanced RSoft-CAD simulations that combined the Beam Propagation Method (BPM) and Finite-Difference Time-Domain (FDTD) techniques, integrated with convolutional neural network (CNN) machine learning algorithms. …”
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Hybrid LSTM–Attention and CNN Model for Enhanced Speech Emotion Recognition by Fazliddin Makhmudov, Alpamis Kutlimuratov, Young-Im Cho

“…Emotion recognition is crucial for enhancing human–machine interactions by establishing a foundation for AI systems that integrate cognitive and emotional understanding, bridging the gap between machine functions and human emotions. …”
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