GCBRGCN: Integration of ceRNA and RGCN to Identify Gastric Cancer Biomarkers by Peng Zhi, Yue Liu, Chenghui Zhao, Kunlun He

“…It demonstrates exceptional performance, surpassing traditional machine learning and graph neural network algorithms with an area under the curve (AUC) of 0.8172 in the task of predicting GC biomarkers. …”
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Urban sentinel: advancing structural health monitoring for building damage measurement in districts through IoT integration and self-optimizing machine learning by Parsa Parsafar

“…These sensors transmit data using LoRaWAN wireless technology to a centralized management system, where a regression AI model harnesses the power of machine learning algorithms to analyze the data and predict the health status of the buildings. …”
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Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches by Burcu Ramazanli, Oyku Yagmur, Efe Cesur Sarioglu, Huseyin Enes Salman

“…Accurate BCs can enhance ML predictions, increasing the clinical applicability. …”
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Adjusted imbalance ratio leads to effective AI-based drug discovery against infectious disease by Ons Masmoudi, Afef Abdelkrim, Emna Harigua-Souiai

“…We trained five machine learning and six deep learning algorithms to predict the anti-pathogen activity of chemical compounds, derived from PubChem Bioassays targeting four infectious diseases. …”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…Multiple machine learning algorithms were used to generate the LUSC classification. …”
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Evaluating the strength properties of high-performance concrete in the form of ensemble and hybrid models using deep learning techniques by Zhe Wang, Tao Sun, Yan Sun, Na Liu

“…Deep learning techniques, including hybrid and ensemble methods, were developed to predict these properties with high accuracy. This paper focuses on forecasting models using T-SFIS, GBMBoost, and Decision Tree, combined with metaheuristic algorithms (GWO, QPSO) in hybrid and ensemble frameworks. …”
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Dataset on the long-term monitoring of foundation vertical deformations on medium-expansive soilMendeley Data by Hawkar Hashim Ibrahim, Rizgar Ali Hummadi

“…It is particularly useful in developing machine learning algorithms that can be used to predict foundation behavior in response to different environmental conditions, optimize foundation designs on expansive soils, and specifically predict foundation heave. …”
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Elucidating Early Radiation-Induced Cardiotoxicity Markers in Preclinical Genetic Models Through Advanced Machine Learning and Cardiac MRI by Dayeong An, El-Sayed Ibrahim

“…Despite normal global left ventricular ejection fraction in both groups, strain analysis showed significant reductions in the anteroseptal and anterolateral segments of irradiated rats. …”
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The Method of Elimination of Vibrations and Forces Excited by Unbalanced Rotary Machines with Inaccesible Rotor by J. Michalczyk, G. Cieplok

“… Possibilities of application of the method of synchronous elimination to the reduction of vibrations and forces in unbalanced rotary machines with inaccessible axes were considered in this paper. …”
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Real-Time Accurate Determination of Table Tennis Ball and Evaluation of Player Stroke Effectiveness with Computer Vision-Based Deep Learning by Zilin He, Zeyi Yang, Jiarui Xu, Hongyu Chen, Xuanfeng Li, Anzhe Wang, Jiayi Yang, Gary Chi-Ching Chow, Xihan Chen

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Buoy and Winch Collaborative Control System Based on Deep Reinforcement Learning by Yang Gu, Jianjun Ni, Zaiming Geng, Bing Zhao, Haowen Yang

“…The main contributions include the development of two simulation environments for training DRL agents, designing a reward function to guide the exploration process, proposing a buoy control algorithm based on the discrete soft actor-critic (SAC) algorithm, and proposing a winch cable length prediction algorithm based on a lightweight transformer model. …”
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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Multiscale features are then extracted with Inception v3 and combined with principal component analysis (PCA) for dimensionality reduction. Finally, an SVM classification algorithm is employed for personnel detection. …”
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Transitional Grid Maps: Joint Modeling of Static and Dynamic Occupancy by Jose Manuel Gaspar Sanchez, Leonard Bruns, Jana Tumova, Patric Jensfelt, Martin Torngren

“…Autonomous agents rely on sensor data to construct representations of their environments, essential for predicting future events and planning their actions. …”
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Research on Image Feature Extraction and Environment Inference Based on Invariant Learning by Yujian Ding, Xiaoxu Ma, Bingxue Yang

“…On the basis of this model, GRAD-CAM algorithm is used to extract environmental features of images. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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IASB Framework: Construction of Data Asset Accounting System Based on PO-BP Model by Haixia Guo

“…The PO algorithm optimizes the weights and biases of the BP neural network, improving its global search and local development capabilities. …”
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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…Thus, in this paper, a hybrid innovative Gaussian Particle Swarm Optimization and fuzzy logic model is proposed to optimize the Bayesian Neural Networks in weight and structure. A hybrid algorithm to improve the performance of Neural Networks and the total number of weights in Neural Networks by determining the size of each particle, which is inspired by the prediction process. …”
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Identifying Capsule Defect Based on an Improved Convolutional Neural Network by Junlin Zhou, Jiao He, Guoli Li, Yongbin Liu

“…Given the actual demand for capsule production, this study proposes a capsule defect detection and recognition method based on an improved convolutional neural network (CNN) algorithm. The algorithm is used for defect detection and classification in capsule production. …”
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Track initialisation for multiple formations based on neutrosophic Hough transform by Yang Penggang, Wang Kun, Feng Guangdong

“…To solve this problem, the authors propose a track initialisation algorithm. It uses characteristics of formation flight to find centroids of each formation with DBSCAN algorithm. …”
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Privacy-Oriented Successive Approximation Image Position Follower Processing by Ying Miao, Danyang Shao, Zhimin Yan

“…The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom-up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. …”
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