Exploration of Hub Genes and Pathogenetic Pathways in Systemic Lupus Erythematosus Complicated with Early Onset Atherosclerosis by Han Zhang, Yinde Huang, Xin Li, Wenbin Chen, Yu Lun, Jian Zhang

“…Finally, 12 hub genes, including PTPRC, TYROBP, FCGR3A, ITGAX, LCP2, IL1B, IRF8, LILRB2, CD68, C1QB, CCR7, and C1QA were identified by using seven different algorithms in Cytohubba. The functional analysis illustrates that these genes were predominantly enriched in immune and inflammation response, lipid and atherosclerosis, and osteoporosis. …”
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RMVAD-YOLO: A Robust Multi-View Aircraft Detection Model for Imbalanced and Similar Classes by Keda Li, Xiangyue Zheng, Jingxin Bi, Gang Zhang, Yi Cui, Tao Lei

“…Aircraft detection technology plays a vital role in civilian applications, with significant attention being devoted to research on related algorithms in recent years. However, most existing research predominantly focuses on aircraft detection from a single top–down viewpoint, which constrains the applicability of detection technology across diverse scenarios. …”
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Determination of Colles fracture risk index by X-ray images with the computer vision application by Wisam A. Hussein, Hussain J. AlKhatteib, Jawad K. Abbas

“…By implementing image thresholding, normalization and registration techniques, validated bone images were obtained and analyzed using computer vision algorithms. Results. A comparative analysis of forearm image intensity between subjects from the control group and patients with Colles fractures resulted in a 1.09 relative index of bone intensity (mean 82 ± 5 vs. 75 ± 6 pixels, respectively). …”
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Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques by Yashashree Mahale, Shrikrishna Kolhar, Anjali S. More

“…Six machine learning models, including logistic regression, support vector machine, decision tree, and random forest, along with gradient boosting algorithms using extreme gradient boost (XGBoost) and light gradient boosting machine frameworks, were implemented. …”
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Correlating gene expression levels with transcription factor binding sites facilitates identification of key transcription factors from transcriptome data by Tinghua Huang, Siqi Niu, Fanghong Zhang, Binyu Wang, Jianwu Wang, Guoping Liu, Min Yao

“…Then, Kendall’s tau correlation statistical algorithms implementing the standard (STD), LINEAR, MIX-LINEAR, DENSITY-CURVE, and MIXED-DENSITY-CURVE weighting methods were used to identify key transcription factors. …”
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Development and validation of a chronic kidney disease progression model using patient-level simulations by Mafalda Ramos, Laetitia Gerlier, Anastasia Uster, Louise Muttram, Dominik Steubl, Andrew H Frankel, Mark Lamotte

“…A series of literature reviews informed the selection of risk factors and identified existing risk equations/algorithms for kidney replacement therapy (KRT), CV events, other CKD-related complications, and mortality. …”
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Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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Prediction Model for the Chloride Ion Permeability Resistance of Recycled Aggregate Concrete Based on Machine Learning by Pengfei Gao, Yuanyuan Song, Jian Wang, Zhiyong Yang, Kai Wang, Yongyu Yuan

“…Based on the experimental data, four algorithms, including artificial neural network (ANN), support vector machine (SVM), random forest (RF) and extreme gradient boosting (XGBoost), were adopted to establish the machine learning prediction models and study the relationships between the electric flux of RAC and the IFs. …”
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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The extracted features were then processed by a set of ML algorithms along with a voting ensemble approach. Additionally, Gradient-weighted Class Activation Mapping (Grad-CAM) was integrated as an explainable AI (XAI) technique for enhancing model transparency by highlighting key influencing regions in the CT scans, which improved interpretability and ensured reliable and trustworthy results for clinical applications. …”
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Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…This approach is computationally lightweight; inference time is below 5 ms, and can be easily embedded in optimization algorithms for load dispatch or in microcontroller applications for building automation systems.…”
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Review and prospect of floating car data research in transportation by Chi Zhang, Yuming Zhou, Min Zhang, Bo Wang, Yuhan Nie

“…Future research could focus on leveraging transformer and graph neural networks to explore spatiotemporal features of data, developing lightweight real-time FCD processing algorithms, and constructing multimodal refined models tailored to specific traffic scenarios.…”
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Mathematical model of a stacker crane with a slewing boom by Korytov M.S., Bezrodina A.E.

“…The developed simulation mathematical model is intended to determine the energy costs in the drives of a new design crane with a rotating boom at given displacements of links, as well as, in the future, to verify the control algorithms.…”
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A State-of-the-Art Review on the Freeze–Thaw Resistance of Sustainable Geopolymer Gel Composites: Mechanisms, Determinants, and Models by Peng Zhang, Baozhi Shi, Xiaobing Dai, Cancan Chen, Canhua Lai

“…In comparison with empirical models, the models established by machine learning algorithms exhibit higher predictive accuracy. This review promotes a more profound understanding of the factors affecting the F-T resistance of GCs and their mechanisms, providing a basis for engineering and academic research.…”
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Leveraging machine learning to identify determinants of zero utilization of maternal continuum of care in Ethiopia: Insights from SHAP analysis and the 2019 mini DHS. by Shimels Derso Kebede, Agmasie Damtew Walle, Daniel Niguse Mamo, Ermias Bekele Enyew, Jibril Bashir Adem, Meron Asmamaw Alemayehu

“…The dataset was preprocessed and modeled using various machine learning algorithms through the PyCaret library, with lightGBM emerging as the best model after various models trained and evaluated based on classification performance metrics. …”
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Wave propagation-based tests for concrete piles – an overview by Reham Samaan, Abdelsalaam Mokhtar, Mohamed Saafan, Ahmed Ebid

“…This investigation establishes the practical and theoretical basis for implementing advanced machine learning predictive models that combine previous records with pattern recognition algorithms, potentially converting traditional PIT interpretation from an uncertain process to a reliable and precise evaluation system. …”
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Aedes mosquito and dengue fever in Iran and worldwide: medical significance, prevention, and control by Reza Hosseiniara, Vahid Mohammadi-Shahrokhi, Sadegh Zarei, Rouhullah Dehghani

“…A comprehensive understanding of clinical manifestations, prognostic indicators, diagnostic algorithms, and laboratory methods is crucial for accurate diagnosis, risk assessment, and effective disease management. …”
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A novel ensemble of hybrid starling murmuration optimized stacked gated Ghostnets for robust classification of DDoS attacks by P. Mamatha, S. Balaji, S. Sai Anuraghav

“…Due to hostile user techniques and the complexity of DDoS, advanced defensive measures are mandatorily required. As the algorithms of Artificial Intelligence (AI) serves as a key factor in developing the the intelligent intrusion detection systems which accurately differentiates the known and unknown attacks. …”
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A Fused Multi-Channel Prediction Model of Pressure Injury for Adult Hospitalized Patients—The “EADB” Model by Eba’a Dasan Barghouthi, Amani Yousef Owda, Majdi Owda, Mohammad Asia

“…This study aims to construct a novel fused multi-channel prediction model of PIs in adult hospitalized patients using machine learning algorithms (MLAs). Methods: A multi-phase quantitative approach involving a case–control experimental design was used. …”
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Processing streams in a monitoring cloud cluster by Alexey N. Nazarov

“…Hadoop web-programming environment is the technological basis for the development of algorithmic and software solutions for the synthesis of monitoring clusters, including information security and information counteraction systems. …”
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Hierarchical Sensing Framework for Polymer Degradation Monitoring: A Physics-Constrained Reinforcement Learning Framework for Programmable Material Discovery by Xiaoyu Hu, Xiuyuan Zhao, Wenhe Liu

“…This paper introduces a novel physics-informed deep learning framework that integrates multi-scale molecular sensing data with reinforcement learning algorithms to enable intelligent characterization and prediction of polymer degradation dynamics. …”
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