MCAF-Net: Multi-Channel Temporal Cross-Attention Network with Dynamic Gating for Sleep Stage Classification by Xuegang Xu, Quan Wang, Changyuan Wang, Yaxin Zhang

“…Automated sleep stage classification is essential for objective sleep evaluation and clinical diagnosis. While numerous algorithms have been developed, the predominant existing methods utilize single-channel electroencephalogram (EEG) signals, neglecting the complementary physiological information available from other channels. …”
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MHFS-FORMER: Multiple-Scale Hybrid Features Transformer for Lane Detection by Dongqi Yan, Tao Zhang

“…Furthermore, a significant drawback of most existing lane-detection algorithms lies in their reliance on complex post-processing and strong prior knowledge. …”
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Using video for reconstruction in SfM. The Capo d’Omo Tower on Mount Argentario by Fabio Lanfranchi, Piero Barlozzini, Luca Martelli

“…Even more widespread are so-called unmanned aircraft systems (UAS), inoffensive and lighter than 250 g, due to the simplification of the related standards and continued improvements in their acquisition devices. The most advanced photo-modelling programs are now able to process video clips directly, automatically selecting the photos suitable for input in scale-invariant feature transform (SIFT) and speeded up robust features (SURF) algorithms, essential aspects of structure from motion (SfM). …”
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Diabetic Retinopathy Detection Using DL-Based Feature Extraction and a Hybrid Attention-Based Stacking Ensemble by Sanjana Rajeshwar, Shreya Thaplyal, Anbarasi M., Siva Shanmugam G.

“…Our work proposed a hybrid attention-based stacking ensemble with the mentioned models in the base layer and logistic regression model as meta layer, which further enhanced accuracy. …”
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An AI framework for counterattack detection and decision-making evaluation in football by Jiangyan Yang, Huanmin Ge, Yixiong Cui

“…A dataset of 101,710 frames was selected based on specific algorithmic rules from synchronized StatsBomb event data and tracking data of 580 Premier League matches. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…Conclusions An artificial intelligence–enabled ECG demonstrates accurate detection of both LVSD and RVSD in pediatric patients. While adult‐trained models offer good performance, improvements are seen when training pediatric‐specific models.…”
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Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer by Junyi Li, Shixin Li, Dongpo Zhang, Yibing Zhu, Yue Wang, Xiaoxiao Xing, Juefei Mo, Yong Zhang, Daixiang Liao, Jun Li

“…To address these limitations, this study systematically analyzed RNA-seq high-throughput data and combined 10 machine learning algorithms to construct 117 models. The optimal algorithm combination, StepCox[both] and ridge regression, was identified, and an immune-related gene signature (IRGS) composed of 12 genes was developed. …”
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Drought Detection in Satellite Imagery: A Layered Ensemble Machine Learning Approach by Muhammad Owais Raza, Naeem Ahmed Mahoto, Mana Saleh Al Reshan, Ali Alqazzaz, Adel Rajab, Asadullah Shaikh

“…The validation of the model is computed using the stratified split method. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…The model’s performance was also improved by a fine-tuned procedure between k-nearest neighbor and its normalized distance of each data point, including precision of 0.833 ± 0.134, specificity of 0.930 ± 0.054, recall of 0.838 ± 0.118, and accuracy of 0.915 ± 0.025, respectively. …”
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Decentralized energy trading in smart grid using secured post quantum encryption by S. Sofana Reka, Anantharaman Prasad, Prakash Venugopal, Fawaaz Sammil, Visakh Pradeep, Swaroop S Kaimal, Manoj Kumar Rajagopal

“…With the shifting from traditional grids to smart grids, there is an immense shift towards decentralized energy trading wherein “prosumers” can enter peer-to-peer transactions. This model decreases dependence on centralized utilities and maximizes efficient, flexible, and resilient energy distribution. …”
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A novel data-driven based high-precision building roof contour full-automatic extraction and structured 3D reconstruction method combining stereo images and LiDAR points by Xiongwu Xiao, Kai Wang, Zhichao Zhong, Wenhu Qu, Weiwei Wu, Zhigao Cui, Yanzhao Su, Aihua Li, Jianya Gong, Deren Li

“…Firstly, an improved Sobel-based-operator is designed, which effectively improves the detection rate of building-edge-features. …”
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Closed-Loop Clustering-Based Global Bandwidth Prediction in Real-Time Video Streaming by Sepideh Afshar, Reza Razavi, Mohammad Moshirpour

“…To overcome these challenges, we propose closed-loop clustering-based Global Forecasting Models (GFMs) for SBP. Unlike local models, GFMs apply the same function to all traces enabling cross-learning, and leveraging relationships among traces to address the performance issues seen in current SBP algorithms. …”
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Comprehensive analysis of methods for estimating actual paddy evapotranspiration—A review by Kiran Bala Behura, Sanjay Kumar Raul, Jagadish Chandra Paul, Sheelabhadra Mohanty, Prachi Pratyasha Jena, Sanat Kumar Dwibedi, Subhankar Ghosh, Laishram Kanta Singh, Sougrakpam Roma Devi, Arun Kumar Singha, Amulya Kumar Mohanty

“…Utilizing modernized technologies and hybrid models, the research investigation aims to deepen the understanding of ET variability for rice cropping systems to promote improved water resources management and sustainable agriculture practices as areas for future work suggest the application of vegetation indices incorporating high-resolution multi-spectral imagery to accurately estimate ET and appropriately differentiate between evaporation and transpiration in these complex agricultural systems.…”
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Scientific Machine Learning for Elastic and Acoustic Wave Propagation: Neural Operator and Physics-Guided Neural Network by Nafisa Mehtaj, Sourav Banerjee

“…Through comparative analysis of existing NO algorithms applied across different engineering fields, this study demonstrates how NOs improve generalization, accelerate inference, and enhance scalability for practical wave modeling scenarios. …”
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H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…In addition, H-NMR metabolomics improved the prediction of future cardiometabolic disease in comparison with models relying on just anthropometric measures. …”
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Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis by Ahmed Alfakeeh, Mhd Saeed Sharif, Abin Daniel Zorto, Thiago Pillonetto

“…The study revealed that data balancing and augmentation on the ensemble machine learning algorithms boost the efficacy of clinical predictive models and can help clinics decide which data types are most important when examining patients and diagnosing sepsis early through intelligent human-machine interface.…”
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Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea by Na Hyeon Yu, Daeun Shin, Ik Hee Ryu, Tae Keun Yoo, Kyungmin Koh

“…Various machine learning algorithms were trained by incorporating all features from the health check-up data in the development set. …”
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A novel device-free Wi-Fi indoor localization using a convolutional neural network based on residual attention by Mashael Maashi, Alanoud Al Mazroa, Shoayee Dlaim Alotaibi, Asma Alshuhail, Muhammad Kashif Saeed, Ahmed S. Salama

“…This improvement demonstrates the model’s ability to handle complex indoor environments and proves its practical applicability in real-world scenarios.…”
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‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion by Manash Sarma, Subarna Chatterjee

“…DL classifier is used for developing models of both categories while GB (Gradient Boost), SVM (Support Vector Machine) classifier based models are built to identify AD stages from NCBI participants. …”
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State-of-the-art review on Automatic Vertical Drilling Tools: Addressing vibrational load challenges in oil and gas operations by Jialin Tian, Ameer Dheyaa

“…Frameworks for addressing these gaps are proposed, emphasizing the need for advanced computational techniques, including simulation-driven design, smart control algorithms, and innovative material applications. Recommendations for future research highlight strategies to extend tool life, improve drilling accuracy, and minimize environmental impact. …”
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