Global trends in the use of artificial intelligence for urological tumor histopathology: A 20-year bibliometric analysis by Fazhong Dai, Yifeng He, Juan Duan, Kangjian Lin, Qian Lv, Zhongxiang Zhao, Yesong Zou, Jianhong Jiang, Zongtai Zheng, Xiaofu Qiu

“…Recent advances in digital pathology and artificial intelligence (AI) offer transformative potential by standardizing diagnoses, improving accuracy, and bridging healthcare disparities. …”
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Perspective of Chinese GF-1 high-resolution satellite data in agricultural remote sensing monitoring by Qing-bo ZHOU, Qiang-yi YU, Jia LIU, Wen-bin WU, Hua-jun TANG

“…However, it is still at the initial stage of GF-1 data application in agricultural remote sensing monitoring. Advanced algorithms for estimating agronomic parameters and soil quality with GF-1 data need to be further investigated, especially for improving the performance of remote sensing monitoring in the fragmented landscapes. …”
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A novel gene signature for predicting outcome in colorectal cancer patients based on tumor cell-endothelial cell interaction via single-cell sequencing and machine learning by Lina Pang, Qingxia Sun, Wenyue Wang, Mingjie Song, Ying Wu, Xin Shi, Xiaonan Shi

“…Prognostic signatures were developed using various machine learning algorithms based on marker genes linked to the identified cell subpopulations. …”
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A Comparison of Recent Global Time-Series Land Cover Products by Peilin Li, Yan Wang, Chisheng Wang, Lin Tian, Meijiao Lin, Siyao Xu, Chuanhua Zhu

“…This study highlights challenges in dynamic datasets, including classification system discrepancies, resolution effects, and reference data limitations, and suggests that future advancements should focus on improving classification algorithms, refining sampling methods, and developing assessment systems that incorporate high-precision, real-time validation data.…”
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In Vitro Oral Cavity Permeability Assessment to Enable Simulation of Drug Absorption by Pankaj Dwivedi, Priyata Kalra, Haiying Zhou, Khondoker Alam, Eleftheria Tsakalozou, Manar Al-Ghabeish, Megan Kelchen, Giovanni M. Pauletti

“…<b>Conclusions</b>: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. …”
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Research on Quantitative Evaluation of Defects in Ferromagnetic Materials Based on Electromagnetic Non-Destructive Testing by Xiangyi Hu, Ruijie Xie, Ruotian Wang, Jiapeng Wang, Haichao Cai, Xiaoqiang Wang, Xiang Li, Qingzhu Guan, Jianhua Zhang

“…., inaccurate quantification, over-reliance on algorithms, and non-intuitive result presentation, among others) in quantitative defect evaluation. …”
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Enhanced Metabolic Control in a Pediatric Population with Type 1 Diabetes Mellitus Using Hybrid Closed-Loop and Predictive Low-Glucose Suspend Insulin Pump Treatments by Irina Bojoga, Sorin Ioacara, Elisabeta Malinici, Victor Chiper, Olivia Georgescu, Anca Elena Sirbu, Simona Fica

“…Background: Insulin pumps coupled with continuous glucose monitoring sensors use algorithms to analyze real-time blood glucose levels. …”
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The essence and structure of the scientific outlook of future teachers of natural and mathematical specialties by Zelinha Yulia, Halitsan Olha

“…The article highlights the author’s position regarding the algorithms for structuring the scientific outlook, as a category characterized by multidimensionality and a complex multifunctional composition. …”
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Temporal scalability analysis of spectral remote sensing and Machine Learning-Based models for forest mapping in the tropical region of Nigeria by K. Pawłuszek-Filipiak, D. Włodarczyk, K. Stuchły, F.E. Ikuemonisan

“…The integration of machine learning (ML) algorithms with remote sensing (RS) data offers significant potential for enhancing dynamic forest characterization and change detection through high temporal density mapping. …”
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Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…The simulated TWSAs (BNML_TWSA) outperformed the TWSAs from LSM outputs when evaluated against GRACE datasets. Improvements are particularly noted in river basins such as the Godavari, Krishna, Danube and Amazon, with median correlation coefficient, Nash–Sutcliffe efficiency, and RMSE values for all grid cells in the Godavari Basin, India, being 0.927, 0.839 and 63.7 mm, respectively. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…The optimized QNN model has an improvement of more than 20.5% in precision, an enhancement of over 23.2% in recall, and an increase of over 22.3% and 21.8% in accuracy and F1 score. …”
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Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…EBM, LightGBM, and AdaBoost algorithms were applied to generate a discriminatory model between RA and controls. …”
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Integrated Bioinformatics and Experimental Validation Reveal Macrophage Polarization-Related Biomarkers for Osteoarthritis Diagnosis by He Q, Liu L, Hu X, Lin L, Song Z, Xia Y, Lin Q, Wei J, Li S

“…Least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to identify hub genes and construct a diagnostic model validated through internal datasets and multiple external bulk RNA-seq and single-cell RNA-seq data. …”
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UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma by Haofeng Yin, Yibo Xue, Chen Wang, Yanqin Wu, Yuchen Guo, Chunzhen Li, Yunyan Zhang, Shulei Yin, Tiejun Zhao

“…The absence of reliable biomarkers and the heterogeneity in treatment responses continue to hinder improvements in patient prognosis. This study aimed to identify novel biomarkers capable of predicting patient outcomes and therapeutic responsiveness, while also assessing their potential as intervention targets for LUAD.MethodsMultiple cohorts from public databases were employed to screen key prognostic genes, followed by external validations. …”
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Using Pleiades Satellite Imagery to Monitor Multi-Annual Coastal Dune Morphological Changes by Olivier Burvingt, Bruno Castelle, Vincent Marieu, Bertrand Lubac, Alexandre Nicolae Lerma, Nicolas Robin

“…Among different potential sources of errors, shadow areas due to the steepness of the dune stoss slope and crest, along with planimetric errors that can also occur due to the steepness of the terrain, remain the major causes of errors still limiting accurate enough volumetric change assessment. However, ongoing improvements on the stereo matching algorithms and spatial resolution of the satellite sensors (e.g., Pleiades Neo) highlight the growing potential of Pleiades images as a cost-effective alternative to other mapping techniques of coastal dune topography.…”
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Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

“…Additionally, we explore three meta-learning paradigms and three FL algorithms to investigate their effectiveness and suggest the optimal choices for performance improvement. …”
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The performance of artificial intelligence in image-based prediction of hematoma enlargement: a systematic review and meta-analysis by Wenjing Fan, Zhiping Wu, Wangyang Zhao, Luzhu Jia, Shuze Li, Wei Wei, Xin Chen

“…Background Accurately predicting hematoma enlargement (HE) is crucial for improving the prognosis of patients with cerebral haemorrhage. …”
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Energy-Aware and Reliability-Based Localization-Free Cooperative Acoustic Wireless Sensor Networks by Junaid Qadir, Ubaid Ullah, Beatriz Sainz-De-Abajo, Begona Garcia Zapirain, Goncalo Marques, Isabel de la Torre Diez

“…In addition, the overall 12.40&#x0025; improvement is achieved in the packet&#x2019;s reliability. …”
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Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recog... by Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

“…ResultsThe study is supported by the Program for the Improvement of Working Conditions for Members of the SNII and SNCA (PROSNII U006EST), and APPAC-VII-CUCS-2025 for Article Publication Fees, from the University of Guadalajara. …”
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Technical note: Evolution of convective boundary layer height estimated by Ka-band continuous millimeter wave radar at Wuhan in central China by Z. Zhang, Z. Zhang, Z. Zhang, K. Huang, K. Huang, K. Huang, F. Yi, F. Yi, F. Yi, W. Cheng, F. Liu, F. Liu, F. Liu, J. Zhang, Y. Jia

“…The CBLHs from the MMCR <span class="inline-formula"><i>w</i></span> in the selected durations are compared with those estimated by the lidar range-corrected signal (RCS) and radiosonde temperature based on different algorithms, showing good agreement with each other. …”
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