Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review by Oksana V. Kryuchkova, Elena V. Schepkina, Natalia A. Rubtsova, Boris Y. Alekseev, Anton I. Kuznetsov, Svetlana V. Epifanova, Elena V. Zarya, Ali E. Talyshinskii

“…The most common machine-learning algorithms applied by the investigators were as follows: multiple logistic regression (76%), support vector machine (38%), and random forest (24%). …”
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Characterization of severity of hemolytic disease of the fetus and newborn due to Rhesus antigen alloimmunizationAJOG Global Reports at a Glance by Alexis A. Krumme, ScD, Robert Y. Suruki, ScD, Clair Blacketer, MPH, Jill Hardin, PhD, Joel N. Swerdel, PhD, May Lee Tjoa, PhD, Kara B. Markham, MD

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Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…As prolonged inactivity becomes a growing public health concern, researchers are increasingly utilizing machine learning (ML) techniques to examine and understand these patterns. …”
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Optical Remote Sensing for Global Flood Disaster Mapping: A Critical Review Towards Operational Readiness by Molan Zhang, Zhiqiang Chen, Jun Wang, Bandana Kar, Marlon Pierce, Kristy Tiampo, Ronald Eguchi, Margaret Glasscoe

“…We will cross-verify traditional machine learning and current deep learning methods and provide both benchmark databases and algorithms for the research community. Last, with this suite of data and algorithms, we will demonstrate the development of a cloud-computing-supported computing gateway, which houses the services of both our remote-sensing-based machine learning engine and a web-based user interface. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…However, it remains to answer the question of the need to improve the efficiency of an already implemented network, and, therefore, to conduct research on methods to improve the efficiency of networks, including finer tuning of parameters and learning algorithms, as well as architecture.A well-known and obvious drawback of using LSTMs is their exactingness in terms of equipment and resources, both during training (the training process takes a significant amount of time) and during startup, in our case, it is supplemented by increased requirements for the training sample and casts doubt on the advisability of further study of LSTM networks when solving this task.Conclusion. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…Through a rigorous synthesis of peer-reviewed research from 2020 to 2024, the study identifies key trends, challenges and opportunities in AI-driven education, offering a multidimensional perspective for educators, policymakers and researchers. …”
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Global soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS by Emanuele Santi, Davide Comite, Laura Dente, Leila Guerriero, Nazzareno Pierdicca, Maria Paola Clarizia, Nicolas Floury

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WU Hongchun1, ZHENG Youqi1, CAO Liangzhi1, DU Xianan1, WANG Xuesong2, ZU Tiejun1, LIU Zhouyu1, HE Qingming1, CHEN Ronghua1, GE Li1, YANG Rui2, GAO Xinzhao2, WANG Shixi2... by WU Hongchun1, ZHENG Youqi1, CAO Liangzhi1, DU Xianan1, WANG Xuesong2, ZU Tiejun1, LIU Zhouyu1, HE Qingming1, CHEN Ronghua1, GE Li1, YANG Rui2, GAO Xinzhao2, WANG Shixi2, A Reai2

“…Consequently, these algorithms demonstrate superior versatility and scalability, providing instrumental support for the research and development of China’s new generation of liquid-metal fast reactor.…”
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A Comprehensive Review of Thermal Management Methods and Ideal System Design for Improved Electric Vehicle Battery Pack Performance and Safety by M. Murugan, P. V. Elumalai, KCK Vijayakumar, M. Babu, K. Suresh Kumar, M. Ganesh, Liu Kuang, S. Prabhakar

“…The research study further evaluates the integration of TMS in vehicle design and its effects on battery lifespan, charging speeds, and environmental impacts. …”
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Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired Key Generation and Encryption by Israel Edem Agbehadji, Richard C. Millham, Emmanuel Freeman, Wanqing Wu, Xianbin Zhang

“…The methods to extract features from ECG signals are time domain-based; however, the challenge with relying only on the time-domain or frequency-domain method is the inability to capture the intra-leading relationship of Variational Mode Decomposition signals. In this research, fusing multiple domains ECG feature and adaptive Variational Mode Decomposition approaches are utilized to mitigate the challenge of losing the intra-leading correlations of mode decompositions, which might reduce the robustness of encryption algorithms. …”
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A Nondestructive Detection Method for the Muti-Quality Attributes of Oats Using Near-Infrared Spectroscopy by Linglei Li, Long Li, Guoyuan Gou, Lang Jia, Yonghu Zhang, Xiaogang Shen, Ruge Cao, Lili Wang

“…Subsequently, the optimal PLS model was obtained by integrating feature wavelength selection algorithms (CARS, SPA, UVE, LAR). After SD-SPA, total starch reached its optimal state (<i>R</i>_p² = 0.768, <i>RMSEP</i> = 2.057). …”
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Synergizing Intelligence and Privacy: A Review of Integrating Internet of Things, Large Language Models, and Federated Learning in Advanced Networked Systems by Hongming Yang, Hao Liu, Xin Yuan, Kai Wu, Wei Ni, J. Andrew Zhang, Ren Ping Liu

“…Finally, this review identifies critical open questions and promising future research paths, including ultra-lightweight models, robust algorithms for heterogeneity, machine unlearning, standardized benchmarks, novel FL paradigms, and next-generation security. …”
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A Pilot Study on Mixed-Reality Approaches for Detecting Upper-Limb Dysfunction in Multiple Sclerosis: Insights on Cerebellar Tremor by Etty Sabatino, Miriam Moschetta, Andrea Lucaroni, Giacinto Barresi, Carlo Ferraresi, Jessica Podda, Erica Grange, Giampaolo Brichetto, Anna Bucchieri

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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

“…However, long-term, high-resolution datasets on seasonal pasture distribution remain scarce, which has significantly constrained related research and management practices. In this study, we developed an automated seasonal pasture classification framework based on the Google Earth Engine (GEE) platform. …”
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An Experimental Dataset for Search and Rescue Operations in Avalanche Scenarios Based on LoRa Technology by Michele Girolami, Fabio Mavilia, Andrea Berton, Gaetano Marrocco, Giulio Maria Bianco

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Video-Driven Artificial Intelligence for Predictive Modelling of Antimicrobial Peptide Generation: Literature Review on Advances and Challenges by Jielu Yan, Zhengli Chen, Jianxiu Cai, Weizhi Xian, Xuekai Wei, Yi Qin, Yifan Li

“…By integrating video analysis with computational modelling, researchers can visualise and quantify AMP–microbe interactions at unprecedented levels of detail, thereby informing both experimental design and the refinement of predictive algorithms. …”
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Noise Reduction in CWRU Data Using DAE and Classification with ViT by Jun-gyo Jang, Soon-sup Lee, Se-yun Hwang, Jae-chul Lee

“…These technological advancements have played a significant role in the dramatic growth of the predictive maintenance market for mechanical equipment, prompting active research on noise removal techniques and classification algorithms for the accurate determination of the causes of equipment failure. …”
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Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease feat... by Vivien Batoumeni, Yeranuhi Hovhannisyan, Bénédicte Gobert, Keyhan Alvandipour, Jennifer Arthur Ataam, Ombline Conrad, David Hoffmann, Nicolas Wiest-Daesslé, Jochen Dobner, José Américo Nabuco Leva Ferreira Freitas, Hakim Hocini, Zhenlin Li, Laurent Brino, Andrea Rossi, Onnik Agbulut, Peter Sommer, Pierre Joanne, Konstantinos Gkatzis

“…Finaly, we developed a machine learning prediction model to classify cellular phenotypes, which can be used for translational research, including drug candidate screening. This research opens new avenues for understanding the molecular mechanisms of desmin-related cardiomyopathies and fosters the development of novel therapeutic strategies.…”
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Glaucoma Trials Simplified by Arshi Singh, Kirti Singh, Khushboo Chawla

“…In the past few decades, glaucoma research has produced a veritable alphabet soup of clinical trials. …”
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Application of Self-Organizing Maps to Explore the Interactions of Microorganisms with Soil Properties in Fruit Crops Under Different Management and Pedo-Climatic Conditions by Francesca Antonucci, Simona Violino, Loredana Canfora, Małgorzata Tartanus, Ewa M. Furmanczyk, Sara Turci, Maria G. Tommasini, Nika Cvelbar Weber, Jaka Razinger, Morgane Ourry, Samuel Bickel, Thomas A. J. Passey, Anne Bohr, Heinrich Maisel, Massimo Pugliese, Francesco Vitali, Stefano Mocali, Federico Pallottino, Simone Figorilli, Anne D. Jungblut, Hester J. van Schalkwyk, Corrado Costa, Eligio Malusà

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