Age- and Sex-Based Developmental Biomarkers in Eye Movements by Frederick Robert Carrick, Melissa Hunfalvay, Takumi Bolte, Sergio F. Azzolino, Mahera Abdulrahman, Ahmed Hankir, Matthew M. Antonucci, Nouf Al-Rumaihi

“…However, eye movement features provide biomarkers that are useful for disease classification with superior accuracy and robustness compared to previous classifiers for neurological diseases. …”
Get full text

Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

“…This integrated architecture facilitates collaborative learning among generative modelling, attention-driven feature refinement, and physics-based enhancement. …”
Get full text

Closing the Domain Gap: Can Pseudo-Labels from Synthetic UAV Data Enable Real-World Flood Segmentation? by Georgios Simantiris, Konstantinos Bacharidis, Costas Panagiotakis

“…Experimental results on five state-of-the-art flood segmentation models show that synthetic data can closely match real data in training performance, and combining both sources improves model robustness by 1–7%. …”
Get full text

Domain Adaptation Using the Replay Buffer: Adaptive Sampling Using Domain-Specific Classifier by Seokmin Kim, Youngbae Hwang

“…This approach enhances the quality of the training set, ensuring the model focuses on high-quality, domain-relevant data. …”
Get full text

Design of a Transformer-GRU-Based Satellite Power System Status Detection Algorithm by Guoqi Xie, Xinhao Yang, Jiayu Zhao, Zhou Huang

“…Experimental results on satellite power system status detection demonstrate that the modified Transformer-GRU model achieves superior detection performance compared to baseline approaches. …”
Get full text

An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data by Huiyu Zhao, Chuang Miao, Yidi Zhu, Yijun Shu, Xiangsong Wu, Ziming Yin, Xiao Deng, Wei Gong, Ziyi Yang, Weiwen Zou

“…In addition, two interpretable methods are applied to help clinicians understand the model-based decisions. Model performance was evaluated through accuracy, precision, specificity, sensitivity, F1-score, area under the curve (AUC), and matthews correlation coefficient (MCC). …”
Get full text

Immune Evasion Mechanism Mediated by ITPRIPL1 and Its Prognostic Implications in Glioma by Zou Xiaoyun, Ye Wenhao, Wu Huan, Yang Yuanyuan, Liu Changqing, Wen Hebao, Ma Caiyun

“…Methods: A comprehensive analysis was performed using datasets from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO). …”
Get full text

An efficient trustworthy cyberattack defence mechanism system for self guided federated learning framework using attention induced deep convolution neural networks by Louai A. Maghrabi, Alanoud Subahi, Nouf Atiahallah Alghanmi, Turki Althaqafi, Nahla J. Abid, Nasser N. Albogami, Mahmoud Ragab

“…The Dung Beetle Optimization (DBO) technique is used in the feature selection process to identify the most relevant and non-redundant features. …”
Get full text

Machine learning identification of key genes in cardioembolic stroke and atherosclerosis: their association with pan-cancer and immune cells by Tianxiang Zhang, Chunhui Yuan, Mo Chen, Jinjiang Liu, Wei Shao, Ning Cheng

“…Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed to explore the functions of common FR-related DEGs (FRDEGs). …”
Get full text

Gait stability prediction through synthetic time-series and vision-based data by Mauricio C. Cordeiro, Ciaran O. Cathain, Ciaran O. Cathain, Ciaran O. Cathain, Vitor B. Nascimento, Thiago B. Rodrigues

“…SHAP analysis revealed that the synthetic data approach enhanced feature attribution alignment with established principles, particularly for step width, BMI, and fall history.DiscussionTherefore, our results show that: (1) synthetic data accurately replicated gait parameters with high fidelity; (2) synthetic data-trained models outperformed real data-trained models in MoS prediction; and (3) step width, BMI, and fall history were the most significant predictors of MoS in older adults. …”
Get full text

Elucidating the dynamic tumor microenvironment through deep transcriptomic analysis and therapeutic implication of MRE11 expression patterns in hepatocellular carcinoma by Ruiqiu Chen, Chaohui Xiao, Zizheng Wang, Guineng Zeng, Shaoming Song, Gong Zhang, Lin Zhu, Penghui Yang, Rong Liu

“…Furthermore, MRE11 dynamically enhanced macrophage regulation, exhibiting immunosuppressive and tumor-invasive features. Finally, our prognostic model exhibited strong predictive accuracy across multiple datasets. …”
Get full text

Artificial Intelligence in the Analysis of Upper Gastrointestinal Disorders by Chang Seok Bang

“…Neural networks were used to detect, classify, and delineate various images of lesions because the local feature selection and optimization of the deep learning model enabled accurate image analysis. …”
Get full text

Redundancy Design and Workspace Analysis of 3-PRS Parallel Mechanism by Junjie Huang, Pengfei Wang, Bowen Zhang, Junwei Zhao

“…The redundancy feature of the parallel mechanism can increase the effective workspace，realize the fault-tolerant motion，which improves the performance of the parallel mechanism. …”
Get full text

Digital Transformation in Lesson Planning: Automating Semester Learning Plans to Improve Pedagogical Effectiveness by Uswatun Hasanah, Annas Ribab Sibilana

“…Product testing results on aspects such as feature compatibility with RPS formulation needs, application functionality quality, user interface, application performance efficiency, curriculum alignment, and data reliability and security, as assessed by expert validators, are deemed highly feasible. …”
Get full text

Novel Condition Monitoring Method for Wind Turbines Based on the Adaptive Multivariate Control Charts and SCADA Data by Qinkai Han, Zhentang Wang, Tao Hu

“…Multivariate regression analysis is utilized to obtain the normal condition prediction model of wind turbine with fault-free SCADA data. …”
Get full text

Design and prediction of high optical density photovoltaic polymers using machine learning-DFT studies by Aljaafreh Mamduh J., Hassan Abrar U.

“…The results show that extra gradient boosting regressor and random forest regressor are the best-performing models among all the tested ML models, whose good R-squared (R 2) values reveal their prediction accuracy. …”
Get full text

DeeWaNA: An Unsupervised Network Representation Learning Framework Integrating Deepwalk and Neighborhood Aggregation for Node Classification by Xin Xu, Xinya Lu, Jianan Wang

“…This paper introduces DeeWaNA, an unsupervised network representation learning framework that unifies random walk strategies and neighborhood aggregation mechanisms to improve node classification performance. Unlike existing methods that treat these two paradigms separately, our approach integrates them into a cohesive model, addressing limitations in structural feature extraction and neighborhood relationship modeling. …”
Get full text

ObjectDetection in Agriculture: A Comprehensive Review of Methods, Applications, Challenges, and Future Directions by Zohaib Khan, Yue Shen, Hui Liu

“…Persistent challenges, such as environmental variability, limited labeled data, and model generalization, are critically examined, with proposed solutions including multi-modal data fusion and lightweight models for edge deployment. …”
Get full text

BreNet: Attention-Enhanced Multi-Scale CNN Framework for Breast Cancer Classification in Histopathological Images by Helala M. Alshehri

“…By combining three pre-trained CNN backbones with complementary channel and spatial attention mechanisms, BreNet refines feature representations across multiple scales. The model achieves strong and consistent performance on both the BreakHis and IDC datasets, reaching classification accuracies of 99.96% and 88.26% respectively, while maintaining low false-positive and false-negative rates. …”
Get full text

Context-dependent similarity searching for small molecular fragments by Atsushi Yoshimori, Jürgen Bajorath

“…With active analogue series as a model system to establish a global structure–activity context, we demonstrate that this approach is applicable to systematic similarity searching for substituents and increases the performance of standard descriptor representations. …”
Get full text