Bibliometric analysis and review of AI-based video generation: research dynamics and application trends (2020–2025) by Wei Xie, Anshu Hu, Qing Xie, Junjie Chen, Ruoyu Wan, Yuhan Liu

“…Our findings the rise of specific architectures, pinpoint high-activity application areas, reveal evolving thematic clusters, and also remarks persistent challenges, including technical hurdles and critical ethical issues such as deepfake detection, algorithmic transparency, and data privacy. By synthesizing these analyses, this study offers a structured overview of the recent landscape, and highlights areas that may warrant further exploration in AI video generation.…”
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Mined Block Withholding and Imposed Fork by Using Mining Pool Alliance Strategic—A Case Study in Bitcoin System by Yean-Fu Wen, Ming-Fang Chen

“…As the difficulty of mining increases, pools may develop competition strategies to reduce time and increase the rewards for mining blocks. …”
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GenAI-Based Jamming and Spoofing Attacks on UAVs by Burcu Sonmez Sarikaya, Serif Bahtiyar

“…Creating effective intrusion detection systems against such attacks has been a significant challenge since there is a lack of sufficient attack data that can be used to design an intrusion detection system with advanced computing algorithms. In this research, we propose a novel framework to create attacks data for UAVs by using generative artificial intelligence algorithms. …”
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Mathematics teachers’ perceptions of computational thinking and its integration into mathematics education by Muhammad Zuhair Zahid

“…The findings reveal that mathematics teachers have oversimplified perspective on some components such as algorithmic thinking and automation, contributing to their vague perception of computational thinking as problem-solving, which may hinder the original purpose of integrating computational thinking into mathematics education. …”
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Current application of artificial intelligence in laparoscopic cholecystectomy by S.M. Chooklin, S.S. Chuklin

“…Advances in AI have made it possible to train algorithms that identify anatomy and interpret the surgical field. …”
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Morph_CNeT: A new GIS tool to extract morphometric attributes characterising channel network topology of Indian catchments by Saroj Rana, Sagar Rohidas Chavan

“…There is a dearth of attempts to utilize these attributes in hydro-geomorphological applications, may be due to the complexity involved in their extraction owing to lack of any algorithmic procedure. …”
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Precision Agriculture: Utilizing Machine Learning for Accurate Plant Disease Diagnosis by Divya Banti, Tandan Gajendra

“…Mobile applications with ML algorithms also enable on the spot plant disease diagnosis from the smartphone camera, enabling site rather than later intervention. …”
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AI-powered Somatic Cancer Cell Analysis for Early Detection of Metastasis: The 62 principal Cancer Types by Sandile Buthelezi, Solly Matshonisa Seeletse, Taurai Hungwe, Vimbai Mbirimi-Hungwe

“…Objective: To emphasize the importance of early metastasis detection in improving cancer patient outcomes, and to highlight that recent advancements in AI-powered somatic cancer cell analysis may enhance early detection and personalize treatment strategies. …”
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Beyond the STI clinic: Use of administrative claims data and machine learning to develop and validate patient-level prediction models for gonorrhea by Lorenzo Argante, Germain Lonnet, Emmanuel Aris, Jane Whelan

“…ML classification models were constructed based on logistic regression and tree-based algorithms. Results Models constructed using tree-based algorithms such as XGBoost provided the best discriminatory results, but simpler ridge regressions models with splines also achieved reasonable discrimination, allowing for the identification of population subsets at increased risk of gonorrhea infection. …”
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Performance Comparison of Support Vector Machine (SVM) and k-Nearest Neighbors (kNN) in Verifying Material Orientation by Eldio Utama, Eko Rudiawan Jamzuri

“…For instance, in the beverage industry, incorrect orientation of materials, such as bottle caps, can lead to failures in the packaging process, resulting in improperly sealed bottles that may compromise product quality and safety. This study compares the performance of Support Vector Machine (SVM) and k-Nearest Neighbors algorithms for verifying material orientation verification through automated optical inspection. …”
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Teaching a neural network modeling socio-economic development of the region by S. V. Romanchukov, O. G. Berestneva, L. A. Petrova

“…At the same time, however, it should be noted that the resources of an individual research team may be (and most likely will be) insufficient to create their own software solution for the implementation of machine learning algorithms from scratch. …”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…Additionally, ML is being used for foreign object detection (FOD) to ensure safety by identifying metallic and living objects that may interfere with power transmission. The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
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Distinguish the Value of the Benign Nevus and Melanomas Using Machine Learning: A Meta-Analysis and Systematic Review by Suli Li, Yihang Chu, Ying Wang, Yantong Wang, Shipeng Hu, Xiangye Wu, Xinwei Qi

“…This suggests that state-of-the-art ML-based algorithms for distinguishing melanoma from benign nevi may be ready for clinical use. …”
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Prediction of ultimate load capacity of demountable shear stud connectors using machine learning techniques by Ahmed I. Saleh, Nabil S. Mahmoud, Fikry A. Salem, Mohamed Ghannam

“…Despite the robust performance of advanced algorithms, the study acknowledges challenges such as data imbalance and minimal influence of certain parameters, which may affect model generalizability.…”
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Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome. by Dragana M Pavlovic, Petra E Vértes, Edward T Bullmore, William R Schafer, Thomas E Nichols

“…The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. …”
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Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation by Todd A. Miano, PharmD, PhD, Athena F. Zuppa, MD, MSCE, Rui Feng, PhD, Stephen Griffiths, BS, Laurel Kalman, BA, Michelle Oyster, MS, Edward Cantu, MD, MSCE, Wei Yang, PhD, Joshua M. Diamond, MD, MSCE, Jason D. Christie, MD, MSCE, Marc H. Scheetz, PharmD, MSC, Michael G.S. Shashaty, MD, MSCE

“…Population PK models that include lung-transplant–specific covariates may enable precision dosing algorithms that account for this highly dynamic clearance. …”
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CORE-MD clinical risk score for regulatory evaluation of artificial intelligence-based medical device software by Frank E. Rademakers, Elisabetta Biasin, Nico Bruining, Enrico G. Caiani, Rhodri H. Davies, Stephen H. Gilbert, Eric Kamenjasevic, Gearóid McGauran, Gearóid O’Connor, Jean-Baptiste Rouffet, Baptiste Vasey, Alan G. Fraser

“…Abstract The European CORE–MD consortium (Coordinating Research and Evidence for Medical Devices) proposes a score for medical devices incorporating artificial intelligence or machine learning algorithms. Its domains are summarised as valid clinical association, technical performance, and clinical performance. …”
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A comprehensive review on safe reinforcement learning for autonomous vehicle control in dynamic environments by Rohan Inamdar, S. Kavin Sundarr, Deepen Khandelwal, Varun Dev Sahu, Nitish Katal

“…However, traditional RL algorithms are unsuitable for safety-critical applications, as they may explore unsafe actions, potentially resulting in accidents. …”
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Forecasting Surface Velocity Fields Associated With Laboratory Seismic Cycles Using Deep Learning by G. Mastella, F. Corbi, J. Bedford, F. Funiciello, M. Rosenau

“…This laboratory‐based study may open new avenues for transfer learning applications with data from natural subduction zones.…”
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Estimation of Coupled Ocean/Atmosphere Impacts to the Satellite Detection of Nocturnal Maritime Low Clouds by Jesse D. Turner, Steven D. Miller, Yoo‐Jeong Noh, J. Christine Chiu, William E. Line, Christian D. Kummerow, Ryan G. Smith

“…Insights from this research can help forecasters and researchers determine which regions and conditions are prone to nighttime FLCs and thus may require either refinement of detection algorithms or independent sensor assessments.…”
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