Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamics by Minhyuk Jeung, Min-Chul Jang, Kyoungsoon Shin, Seung Won Jung, Sang-Soo Baek

“…The high interpretive power of GNNs provides deep insights into the structural relationships among variables, serving as a connection matrix in deep learning algorithms. However, there is insufficient understanding of how interactions between input variables affect model outputs during training. …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…In this manuscript, an Underwater Object Detection and Classification Utilizing the Ensemble Deep Learning Approach and Hybrid Optimization Algorithms (UODC-EDLHOA) technique is developed. The UODC-EDLHOA technique mainly detects and classifies underwater objects using advanced DL and hyperparameter models. …”
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The Importance of Worldview Paradigms in Formation of the Conceptual Foundation Social Forecast by R. V. Fedorov, L. A. Pafomova

“…The unification of the nature of the interaction algorithms does not mean the exclusion of national interests and the levelling of the civilizational characteristics of the actors. …”
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Artificial intelligence for surgical outcome prediction in glaucoma: a systematic review by Zeena Kailani, Lauren Kim, Joshua Bierbrier, Michael Balas, David J. Mathew, David J. Mathew

“…Studies were included if they applied AI models to glaucoma surgery outcome prediction.ResultsSix studies met inclusion criteria, collectively analyzing 4,630 surgeries. A variety of algorithms were applied, including random forests, support vector machines, and neural networks. …”
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Does metaverse improve recommendations quality and customer trust? A user-centric evaluation framework based on the cognitive-affective-behavioural theory by Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Osama Halabi, Raian Ali

“…They can analyse large amounts of data using machine learning algorithms and predictive analytics capabilities to provide highly relevant recommendations to users. …”
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Sustainable financial infrastructure and governance: A fuzzy multi-criteria decision-making analysis of open service innovation in unstable economies by Homa Molavi, Lihong Zhang, Mohammad Khanbabaei

“…This includes highlighting the role of regulatory sandboxes in fostering innovation while ensuring compliance, the importance of data governance in maintaining trust and stability in the financial system, and the impact of AI implementation and AI-driven algorithms in driving open innovation within an unstable banking and economic system. …”
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Machine-Learning-Driven Approaches for Assessment, Delegation, and Optimization of Multi-Floor Building by Abtin Baghdadi, Harald Kloft

“…This study presents a novel integrated framework for the structural analysis and optimization of multi-floor buildings by combining validated theoretical models with machine learning and evolutionary algorithms. The proposed Process–Action–Response System (PARS-Solution) accurately computes key structural responses—such as deformations, shear forces, and bending moments—based on eleven critical design parameters (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mn>1</mn></msub></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mn>11</mn></msub></semantics></math></inline-formula>). …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…The back end of the methodology uses support vector machine (SVM) and extreme gradient boosting (XGB) classification algorithms to establish the relationship between the retrieved feature vector and breast functionality. …”
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Multi-label Classification Based on Label-Aware Variational Autoencoder by SUN Hongjian, XU Pengyu, LIU Bing, JING Liping, YU Jian

“…Experimental results obtained on datasets from four different domains show that the proposed method can effectively enhance feature and label embedding and fully capture the higher-order correlation information between labels for multi-label classification tasks, and the significant superiority of the proposed method in performance is verified through a comparative analysis with state-of-the-art algorithms in terms of multiple evaluation metrics.…”
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Elevated Serum Levels of CCL23 Are Associated with Poor Outcome after Resection of Biliary Tract Cancer by Christoph Roderburg, Simon Labuhn, Jan Bednarsch, Sven A. Lang, Anne T. Schneider, Linda Hammerich, Mihael Vucur, Tom F. Ulmer, Ulf P. Neumann, Tom Luedde, Sven H. Loosen

“…The preoperative identification of ideal surgical candidates has remained a major challenge and easily accessible algorithms including parameters of the individual tumor biology are missing. …”
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Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic by Muhammed Ballı, Asli Ercan Dogan, Sevin Hun Senol, Hale Yapici Eser

“…Data from 924 university students seeking mental health services were analyzed using seven machine learning algorithms. Suicidal ideation was assessed through the 9th item of the Patient Health Questionnaire-9. …”
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The risks of telehealth in radiation oncology: challenges and mitigation strategies by Sotiri Stathakis, Niko Papanikolaou, Jessica Ashford, Jason Stephens, Aaron LaRose

“…These include safeguarding sensitive patient data against cybersecurity threats, navigating the inherent limitations of remote clinical assessments, overcoming technological barriers that contribute to the digital divide, adhering to a complex and evolving regulatory and reimbursement environment, maintaining the crucial therapeutic patient-provider relationship, seamlessly integrating telehealth workflows into existing clinical operations, and upholding ethical principles, particularly concerning equitable access and algorithmic bias. While initial concerns about potential risks, such as increased rates of misdiagnosis or reduced patient satisfaction, were prominent during the early phase of rapid adoption, a growing body of recent empirical literature provides valuable insights into the actual impact of telehealth in radiation oncology and the effectiveness of various mitigation strategies. …”
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Early detection of woody plant encroachment in Canadian prairies using UAV imagery and transformer-based deep learning by Yihan Pu, Xiaojing Lu, Irini Soubry, Xulin Guo

“…This study evaluates the potential of UAV-RGB imagery and deep learning algorithms for early detection and classification of three dominant woody species (Wolf Willow – Elaeagnus commutata, Western Snowberry – Symphoricarpos occidentalis, and Trembling Aspen - Populus tremuloides) in the Canadian Prairies. …”
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Diseases with major salivary glands enlargement and orbits, nose and paranasal sinuses lesions in the practice of a rheumatologist by E. V. Sokol, A. V. Torgashina, B. D. Chaltsev, Yu. I. Khvan, O. A. Golovina

“…Nasal lesions in the form of chronic rhinosinusitis with or without nasal septum perforation, were found in 18 patients, 12 of whom suffered GPA and 6 – IgG4-RD.Two algorithms, that can facilitate the choice of additional studies and the direction of diagnostic search have been proposed for practicing rheumatologists.Conclusion. …”
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Short-term scheduling optimization of battery electric buses in the context of sustainable energy resources under uncertainty by Muhammad Ahmad Iqbal, Ismail I. Almaraj

“…Due to the large-scale nature of the problem, metaheuristic algorithms are used to solve the proposed model. The objective seeks to maximize the profit of the transportation company (TC), which owns both CSs and BEBs, by optimally scheduling the CS selection for its in-transit buses. …”
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Understanding the Influence of Image Enhancement on Underwater Object Detection: A Quantitative and Qualitative Study by Ashraf Saleem, Ali Awad, Sidike Paheding, Evan Lucas, Timothy C. Havens, Peter C. Esselman

“…Finally, we perform an overlap analysis between the generated enhanced sets to identify cases where the enhanced images of different enhancement algorithms unanimously outperform, equally perform, or underperform the original images. …”
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Interdisciplinary Distance Learning Workshop for IT Students by I. A. Andrianov, S. A. Rzheutskaya, M. V. Kharina

“…An example of using the learning workshop in the course “Mathematical Logic and Theory of Algorithms” is presented, in which the implementation of automatic checking of problem solutions required non-standard solutions to refine the learning workshop. …”
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Prognostic, oncogenic roles, and pharmacogenomic features of AMD1 in hepatocellular carcinoma by Youliang Zhou, Yi Zhou, Jiabin Hu, Yao Xiao, Yan Zhou, Liping Yu

“…Multidimensional bioinformatic algorithms were utilized to establish a risk score model for ARGs. …”
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A machine learning prediction model for Cardiac Amyloidosis using routine blood tests in patients with left ventricular hypertrophy by Yuling Pan, Qingkun Fan, Yu Liang, Yunfan Liu, Haihang You, Chunzi Liang

“…We divided the dataset into training and testing cohorts, applying ML algorithms such as logistic regression, random forest, and XGBoost for automated learning and prediction. …”
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Ensuring Measurement Integrity in Petroleum Logistics: Applying Standardized Methods, Protocols, and Corrections by Asta Meškuotienė, Paulius Kaškonas, Benas Gabrielis Urbonavičius, Justina Dobilienė, Edita Raudienė

“…This necessitates that all measurement results are traceable to reference conditions (mass in vacuum, volume at +15 °C). The proposed algorithms for oil mass and volume measurement and recalculation highlight the need for unified international regulations and a robust system.…”
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