Analyzing the performance of biomedical time-series segmentation with electrophysiology data by Richard Redina, Jakub Hejc, Marina Filipenska, Zdenek Starek

“…Faster R-CNN and SVM showed moderate performance, while the rule-based method had the lowest accuracy (77.7 %). …”
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Parameter-Efficient Vehicle Trajectory Prediction Based on Attention-Enhanced Liquid Structural Neural Model by Ruochen Wang, Yue Chen, Renkai Ding, Qing Ye

“…Notably, it reduces computational complexity and model size while maintaining superior accuracy, making it well suited for deployment in resource-constrained systems. …”
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A deep learning framework for predicting disease-gene associations with functional modules and graph augmentation by Xianghu Jia, Weiwen Luo, Jiaqi Li, Jieqi Xing, Hongjie Sun, Shunyao Wu, Xiaoquan Su

“…ModulePred performs graph augmentation on the protein interaction network using L3 link prediction algorithms. It builds a heterogeneous module network by integrating disease-gene associations, protein complexes and augmented protein interactions, and develops a novel graph embedding for the heterogeneous module network. …”
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Privacy-Preserving Federated Learning for Space–Air–Ground Integrated Networks: A Bi-Level Reinforcement Learning and Adaptive Transfer Learning Optimization Framework by Ling Li, Lidong Zhu, Weibang Li

“…Specifically, (1) an adaptive knowledge-sharing mechanism based on transfer learning is designed to balance device heterogeneity and data distribution divergence through dynamic weighting factors; (2) a bi-level reinforcement learning device selection strategy is proposed, combining meta-learning and hierarchical attention mechanisms to optimize global–local decision-making and enhance model convergence efficiency; (3) dynamic privacy budget allocation and robust aggregation algorithms are introduced to reduce communication overhead while ensuring privacy. …”
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RouteLAND: An Integrated Method and a Geoprocessing Tool for Characterizing the Dynamic Visual Landscape Along Highways by Loukas-Moysis Misthos, Vassilios Krassanakis

“…To this end, we developed an integrated method and a Python (version 2.7.16) tool, named “RouteLAND”, for implementing an algorithmic geoprocessing procedure; through this geoprocessing tool, sequences of composite dynamic geospatial analyses and geometric calculations are automatically implemented. …”
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Machine learning frameworks to accurately estimate the adsorption of organic materials onto resin and biochar by Raouf Hassan, Mohammad Reza Kazemi

“…The findings underscore the effectiveness of machine learning methods, particularly XGBoost, LightGBM, and CatBoost, in forecasting adsorption levels with high precision while offering actionable insights into key variables driving adsorption mechanisms.…”
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CPR-Induced Consciousness during Ventricular Fibrillation: Case Report and Literature Review by Xiaoqing Zhou, Boru Sun

“…It is crucial to develop clear algorithms that focus not only on identifying this phenomenon but also on determining the best approaches to manage it. …”
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Predicting emergency department visits for non-traumatic dental-related conditions among Medicaid beneficiaries by Sung Eun Choi, Rindala Fayyad, Daniel Nolte, Christine Riedy, Sharon-Lise Normand

“…We sought to predict future “ED users” for non-traumatic dental-related conditions using machine learning algorithms and identify associated risk factors to help Medicaid outreach programs better target populations in most need of improvement in access to dental care. …”
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Archetype Identification and Energy Consumption Prediction for Old Residential Buildings Based on Multi-Source Datasets by Chengliang Fan, Rude Liu, Yundan Liao

“…Furthermore, XGBoost and Random Forest machine learning algorithms were used to predict city-scale old residential building energy consumption. …”
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Infant rat ultrasonic vocalizations in the neurodevelopmental model of schizophrenia by Agnieszka Potasiewicz, Zuzanna Mincikiewicz, Piotr Popik, Agnieszka Nikiforuk

“…Offspring USVs were recorded upon maternal separation on the 6th, 9th, and 12th postnatal days (PND), while maternal potentiation was tested on the 10th PND. …”
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Capturing the songs of mice with an improved detection and classification method for ultrasonic vocalizations (BootSnap). by Reyhaneh Abbasi, Peter Balazs, Maria Adelaide Marconi, Doris Nicolakis, Sarah M Zala, Dustin J Penn

“…Here we evaluate their advantages and disadvantages in a full, systematic comparison, while also presenting a new approach. This study aims to 1) determine the most efficient USV detection tool among the existing methods, and 2) develop a classification model that is more generalizable than existing methods. …”
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A hybrid theoretical–numerical–experimental framework for robust health monitoring of thin-walled hollow composite members using guided waves by Akshay Prakash Kalgutkar, Shirsendu Sikdar, Sauvik Banerjee, Karl Walton, Rakesh Mishra

“…Results show that abrasion-induced damages cause substantial changes in GW features in terms of DIs and statistical parameters, while hairline cracks marginally affect the damage indices and wave features, aiding in distinguishing between different damage types. …”
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Using machine learning to predict anesthetic dose in fish: a case study using nutmeg oil by Mert Minaz, Cem Alparslan, Akif Er

“…The most accurate models were obtained for WBC across all species, while induction and recovery times varied depending on fish physiology. …”
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Health conspiracy theories: a scoping review of drivers, impacts, and countermeasures by Adnan Kisa, Sezer Kisa

“…Their rapid spread, amplified by social media algorithms and digital misinformation networks, exacerbates public health challenges, highlighting the urgency of understanding their prevalence, key drivers, and mitigation strategies. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The Transformer model focuses on learning complex time-based dependencies, while XGBoost adds robustness to the final predictions by reducing overfitting and improving generalization. …”
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Developmental trends in headache: an Italian school-based study of age- and gender-related changes in clinical characteristics and burden from childhood to adolescence by Federico Salfi, Gennaro Saporito, Simone Cesarano, Federica Guerra, Pamela Silva, Dina Di Giacomo, Elisabetta Tozzi, Michele Ferrara, Bruno Colombo, Francesca Pistoia

“…Age-by-gender interactions revealed that older females experienced greater frequency and a more pronounced impact, while headache frequency affected quality of life with increasing age. …”
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Innovative approaches in marketing for the development of the tourism industry by Yuliia Stasiuk, Andrii Kobchenko

“…For instance, AI-powered chatbots and virtual assistants provide real-time customer support, while machine learning algorithms analyze booking patterns to offer personalized travel recommendations. …”
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Inference of population structure using dense haplotype data. by Daniel John Lawson, Garrett Hellenthal, Simon Myers, Daniel Falush

“…In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. …”
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Neural Network Models for the Half-Cell Potential of Reinforced Slabs with Magnesium Sacrificial Anodes Subjected to Chloride Ingress by Yogesh Murthy

“…Out of all the training algorithms used, the overall performance was best with LM in all stages of modelling (>96%). …”
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Artificial Intelligence and Li Ion Batteries: Basics and Breakthroughs in Electrolyte Materials Discovery by Haneen Alzamer, Russlan Jaafreh, Jung-Gu Kim, Kotiba Hamad

“…Recent advancements in artificial intelligence (AI), particularly in algorithms and computing power, have led to the widespread adoption of AI techniques in various scientific and engineering disciplines. …”
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