Machine learning study on magnetic structure of rare earth based magnetic materials by Dan Liu, Jiahe Song, Zhixin Liu, Jine Zhang, Weiqiang Chen, Yinong Yin, Jianfeng Xi, Xinqi Zheng, Jiazheng Hao, Tongyun Zhao, Fengxia Hu, Jirong Sun, Baogen Shen

“…In this work, 11 machine learning algorithms were trained to predict the material magnetic structure. …”
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Strengthening health information in India: are artificial intelligence based solutions enough to manage health infodemic? by Rohit Jangra, Divya Sharma, Arun Kumar Aggarwal, Ashish Behera, Pankaj Arora, Mohit Kumar, Pulak Syal, Pritam Halder, Kapil Goel, Vineeth Rajagopal, Tanvi Kiran

“…This system should include advanced algorithms and AI to monitor and analyze health-related information, authoritative sources like the Ministry of Health and Family Welfare, public education initiatives, a robust legal and regulatory framework, and continuous research. …”
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Modeling, optimization, and thermal management strategies of hydrogen fuel cell systems by Abubakar Unguwanrimi Yakubu, Liu Qingsheng, Meng Kai, Chen Jinwei, Omer Abbaker Ahmed Mohammed, Jiahao Zhao, Qi Jiang, Xuanhong Ye, Junyi Liu, Qinglong Yu, Muhammad Aurangzeb, Shusheng Xiong

“…This review synthesizes over one hundred studies published between 2015 and 2025, highlighting advancements in steady-state and dynamic modeling, AI-driven multi-objective optimization, and integrated thermal management. Optimization algorithms such as PSO, WOA, MIGA, and NSGA-II have shown promising results, including up to 15 % reduction in hydrogen consumption and 20 to 30 % improvement in thermal uniformity. …”
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CURRENT PRINCIPLES AND TRENDS OF ATRIAL FIBRILLATION PHARMACOTHERAPY by Yu. A. Bunin

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Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease by Salvatore Falciglia, Laura Caffi, Claudio Baiata, Chiara Palmisano, Ioannis Ugo Isaias, Alberto Mazzoni

“…High prediction accuracy (>90%) was achieved in four PD patients with chronic DBS over months of recordings, independently of stimulation parameters. …”
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Building occupancy type classification and uncertainty estimation using machine learning and open data by Tom Narock, J. Michael Johnson, Justin Singh-Mohudpur, Arash Modaresi Rad

“…Multiple ML algorithms are compared. We address strategies to handle significant class imbalance and introduce Bayesian neural networks to handle prediction uncertainty. …”
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A Nighttime Driving-Scene Segmentation Method Based on Light-Enhanced Network by Lihua Bi, Wenjiao Zhang, Xiangfei Zhang, Canlin Li

“…Subsequently, the output of the light enhancement network is input into the segmentation network to obtain the final segmentation prediction. Experimental results show that the proposed method achieves mean Intersection over Union (mIoU) values of 59.4% on the Dark Zurich-test dataset, outperforming other segmentation algorithms for nighttime driving-scenes.…”
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Application of a Texture Appearance Model for Segmentation of Lung Nodules on Computed Tomography of the Chest by F. Shariaty, V. A. Pavlov, S. V. Zavjalov, M. Orooji, T. M. Pervunina

“…The results of applying the described TAM method to normal and noisy CT images are presented and compared to those obtained using the Region Growing and Active Contour algorithms, as well as the combination of Active Contour and Watershed algorithms. …”
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Discovering action insights from large-scale assessment log data using machine learning by Minyoung Yun, Minjeong Jeon, Heyoung Yang

“…This approach demonstrates potential applications in personalized education, healthcare diagnostics, and consumer behavior prediction, advancing the understanding of human behavior through digital footprints.…”
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Bounds on the initial macroporosity of sea ice pressure ridges by Sönke Maus

“…The proposed macroporosity prediction can be useful for modeling the consolidation and property evolution of sea ice ridges and rubble fields and for improving thickness redistribution algorithms in sea ice models.…”
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Inertial Subrange Optimization in Eddy Dissipation Rate Estimation and Aircraft-Dependent Bumpiness Estimation by Zhenxing Gao, Qilin Zhang, Kai Qi

“…This study can be further applied to estimate the turbulence severity on a particular airway, while the bumpiness of specific aircraft can be predicted.…”
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Enabling disaggregation of Asian American subgroups: a dataset of Wikidata names for disparity estimation by Qiwei Lin, Derek Ouyang, Cameron Guage, Isabel O. Gallegos, Jacob Goldin, Daniel E. Ho

“…We show that these data, when combined with public geography-race distributions to predict subgroup membership, outperform existing deterministic name lists in key prediction settings, and enable critical Asian disparity assessments.…”
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Radiomics in glioma: emerging trends and challenges by Zihan Wang, Lei Wang, Yinyan Wang

“…Furthermore, radiomics analysis helps understand the glioma immune microenvironment by predicting immune‐related biomarkers and characterizing immune responses within tumors. …”
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A review of machine learning approaches for the discovery of thermoelectric materials by Övgü C. Yelgel, Celal Yelgel

“…Recent progress in computational infrastructure, along with the advent of data-centric approaches such as machine learning (ML), has transformed the landscape of thermoelectric research. ML algorithms, trained on comprehensive datasets including experimental measurements, crystallographic data, and density functional theory (DFT) results can predict key TE metrics, such as the figure of merit (ZT), with remarkable speed and accuracy. …”
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Missile Strike Simulation in a Video Game Engine by Oleksandr Toshev, Oleksii Maksymov, Maksym Kiriakidi, Maksym Maksymov

“…Firstly, the research focuses on enhancing prediction models for calculating the damage inflicted by missile strikes on opposing naval forces. …”
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Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence by Chadaga Krishnaraj, Khanna Varada Vivek, Prabhu Srikanth, Sampathila Niranjana, Chadaga Rajagopala, Palkar Anisha

“…Hence, supervised machine learning (ML) algorithms and several hyperparameter tuning techniques, including Bayesian optimization, have been utilized in this study to predict MS in patients. …”
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Target repositioning using multi-layer networks and machine learning: The case of prostate cancer by Milan Picard, Marie-Pier Scott-Boyer, Antoine Bodein, Mickaël Leclercq, Julien Prunier, Olivier Périn, Arnaud Droit

“…Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. Using prostate cancer as a case study, the best features were identified and utilized to train machine learning algorithms to predict 5 novel promising therapeutic targets for prostate cancer: IGF2R, C5AR, RAB7, SETD2 and NPBWR1.…”
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Shipyard Manpower Digital Recruitment: A Data-Driven Approach for Norwegian Stakeholders by Bogdan Florian Socoliuc, Andrei Alexandru Suciu, Mădălina Ecaterina Popescu, Doru Alexandru Plesea, Florin Nicolae

“…The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. …”
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An advanced structural health monitoring IoT platform for offshore wind turbine blades by Zhou Xingguo, Tian Yankang, Qin Yi, Charitidis Costas A., Milickovic Tanja K., Termine Stefania

“…This research focuses on developing a comprehensive, real-time monitoring system that utilises advanced sensor networks and edge computing, empowering advanced predictive algorithms to strengthen in-time maintenance of turbine blades, improving operational efficiency and reducing maintenance cost.…”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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