A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…These findings demonstrate that the proposed MHMXAI method effectively integrates metaheuristic algorithms and XAI tools, improving CKD stage prediction accuracy and clinical interpretability.…”
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Apple Rootstock Cutting Drought-Stress-Monitoring Model Based on IMYOLOv11n-Seg by Xu Wang, Hongjie Liu, Pengfei Wang, Long Gao, Xin Yang

“…The neck part is optimized by the KFHA module (Kalman filter and Hungarian algorithm model), and the head part enhances post-processing effects through HIoU-SD (hierarchical IoU–spatial distance filtering algorithm). …”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…IntroductionMachine learning (ML) models have been increasingly applied to predict post-heart transplantation (HT) mortality, aiming to improve decision-making and optimize outcomes. …”
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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The optimized deep-SORT outperforms pre-processing, inference, NMS post-processing, and update time, achieving higher FPS on foggy and the BDD100K dataset video sequences compared to the baseline deep-SORT and strong-SORT vehicle tracking algorithms. …”
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Industrial-scale prediction of cement clinker phases using machine learning by Sheikh Junaid Fayaz, Néstor Montiel-Bohórquez, Shashank Bishnoi, Matteo Romano, Manuele Gatti, N. M. Anoop Krishnan

“…Our models remain robust under varying operations and are evaluated for uncertainty and rare-event scenarios. Through post hoc explainable algorithms, we interpret the hierarchical relationships between clinker oxides and phase formation, providing insights into the functioning of an otherwise black-box model. …”
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Two-Step Screening for Depression and Anxiety in Patients with Cancer: A Retrospective Validation Study Using Real-World Data by Bryan Gascon, Joel Elman, Alyssa Macedo, Yvonne Leung, Gary Rodin, Madeline Li

“…<b>Conclusions:</b> The present study is among the first to demonstrate that a two-step screening algorithm for depression may improve depression screening in cancer using real-world data. …”
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Methods to Quantitatively Evaluate the Effect of Shale Gas Fracturing Stimulation Based on Least Squares by DENG Cai, SUN Kexin, WEN Huan, HU Chaolang

“…This method identified the precise number of active perforations and calculated their average diameter after erosion during the fracturing process. Advanced optimization algorithms were employed to efficiently address both the fitting and calculation tasks. …”
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Transmission scheme for collaborative‐RIS‐aided NOMA system with multiple channels by Heyi Li, Hong Wang, Peiqi Li, Peiyu Wang

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Discrete Phase Shift IRS-Assisted Energy Harvesting in Cognitive Radio Networks With Spectrum Sensing by Lilian Chiru Kawala, Guoquan Li, Mihertie Habtamu Demeke, Junzhou Xiong, Hao Xiong, Hang Hu

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Two-stage resilience enhancement method for integrated electricity-gas systems through linepack and mobile compressors by Chao Qin, Yongxue Wang, Shuaihu Ye

“…The progressive hedging algorithm is employed to further improve the solution efficiency. …”
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A PSO-XGBoost Model for Predicting the Compressive Strength of Cement–Soil Mixing Pile Considering Field Environment Simulation by Jiagui Xiong, Yangqing Gong, Xianghua Liu, Yan Li, Liangjie Chen, Cheng Liao, Chaochao Zhang

“…A cement–soil preparation system considering actual immersion conditions was established, based on controlling the initial water content state of the foundation soil before pile formation and applying submerged conditions post-formation. Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. …”
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Analysis of injured-skin SS-OCT images based on combined attention UNet. by Xiyu Zheng, Jingyuan Wu, Qiong Ma, Diantao Luo, Qingyu Cai, Haiyang Sun, Hongxing Kang

“…To enhance image clarity, we applied noise reduction using the BM3D algorithm. We employed an improved UNet network model that incorporates SimAM and PSA modules, forming three attention mechanisms: TandemAT-UNet, ParallelAT-UNet, and NestedAT-UNet. …”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

“…Finally, the proposed algorithm is applied to a post-disaster rescue scenario, where the task allocation results further demonstrate its superior performance.…”
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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…However, the new transformer attention-based approach to MOT has removed the need for complex post-processing steps, such as graph optimization, allowing for end-to-end query tracking across frames. …”
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MAB-Based Online Client Scheduling for Decentralized Federated Learning in the IoT by Zhenning Chen, Xinyu Zhang, Siyang Wang, Youren Wang

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A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

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