Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…The E2E ensemble learning method used bagging, AdaBoost, Random Forest, Extra Tree Classifier and XGBoost algorithms as base classifier to perform maximum voting-based prediction. …”
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The large, viscous thrombus is aspirated by using the cyclic suction technique by Lin Shenqi, Yu Ling, Hong Ruiting, Dong Runcheng, Liu Bohao, Ruan Wencong, Sun Tao, Zhou Dongqing, Zhou Yixuan, Chen Shi

“…By using optimal timing data, the suction tube of the device can generate impacts to break large thrombi while effectively preventing them from escaping to other parts of the vessel during the suction process, ensuring the smooth completion of thrombectomy. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…Feedforward neural networks outperformed recurrent architectures (+3.1%), while Model Predictive Control (MPC) excelled for SMA actuators (+5.8% accuracy) but underperformed for MSMAs (−7.7%). …”
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A Distributed Collaborative Navigation Strategy Based on Adaptive Extended Kalman Filter Integrated Positioning and Model Predictive Control for Global Navigation Satellite System/... by Wanqiang Chen, Yunpeng Jing, Shuo Zhao, Lei Yan, Quancheng Liu, Zichang He

“…In the field of multi-robot cooperative localization and task planning, traditional filtering algorithms encounter synchronization and consistency issues during multi-source data fusion. …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…The procedure-based measures were derived from specific quality-facts of 21 stages/procedures (e.g., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). …”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. …”
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Designing a Multi-Objective Stable Mathematical Model for Routing Municipal Waste Collection Vehicles by Afrouz Rahmandoust, Ashkan Hafezalkotob, Bijan Rahmani Parchikolaei, َAmir Azizi

“…Multi-objective meta-heuristic algorithms were applied to solve the model in scenarios with larger dimensions. …”
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Beam Scanning with Ultra‐Low Sidelobes and In‐Band Ultra‐Low Scattering Characteristics Empowered by Single Space‐Time‐Coding Radiation‐Scattering Metasurface by Lixin Jiang, Yongfeng Li, Hao Yang, Mingbao Yan, Jinming Jiang, Yunwei Zhang, Zhe Qin, Wanwan Yang, Hongya Chen, Yongqiang Pang, Zhihao Guo, Lin Zheng, Jiafu Wang, Shaobo Qu

“…Furthermore, the proposed strategy does not necessitate the utilization of optimization algorithms and exhibits low SLLs and low SBLs, which will make it flourish in RF stealth applications, such as covert communication systems.…”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…Abstract Accurate estimation of permeability reduction in clay-rich sandstones during low-salinity water flooding is critical for optimizing enhanced oil recovery (EOR) strategies and ensuring efficient reservoir management. …”
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Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience by Pratap Khattri, Rachel Sayers, Kunwar K. Singh, Ryan Slapikas, Chet Bahadur Tamang, Dinee Tamang, Brad Sagara, Ariel BenYishay

“…We conducted a geospatial impact evaluation (GIE), which integrated remote sensing data and econometric techniques, including optimal full matching (OFM) and difference-in-differences (DID). …”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

“…Seven survival machine learning algorithms were used: LASSO, Ridge, RSF, E-NET, GBS, C-GBS, and FS-SVM. …”
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Comparing the potential of tree-based and area-based forest height metrics for aboveground biomass estimation in complex forest landscapes by Weiyan Liu, Yuling Chen, Haitao Yang, Guangcai Xu, Shiyu Yan, Lingjun Li, Ling Chen, Qinghua Guo

“…Two modeling approaches—parametric mixed-effects models (MEM) and non-parametric machine learning (ML) algorithms—were applied to evaluate predictive accuracy. …”
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Artificial intelligence in vaccine research and development: an umbrella review by Rabie Adel El Arab, May Alkhunaizi, May Alkhunaizi, Yousef N. Alhashem, Alissar Al Khatib, Munirah Bubsheet, Salwa Hassanein, Salwa Hassanein

“…AI‑driven multi‑omic integration accelerated epitope mapping, shrinking discovery timelines by months, while predictive analytics optimized manufacturing workflows and supply‑chain operations (including temperature‑controlled, “cold‑chain” logistics). …”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…AI integrated approaches such as stress prediction, irrigation optimization, and image-based phenotyping have enhanced agriculture, while machine learning models like Random Forest and Gradient Boosting improve stress management. …”
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Using Machine Learning to Assess the Effects of Biochar-Based Fertilizers on Crop Production and N₂O Emissions in China by Yuan Zeng, Sujuan Chen, Yunpeng Li, Li Xiong, Cheng Liu, Muhammad Azeem, Xiaoting Jie, Mei Chen, Longjiang Zhang, Jianfei Sun

“…This study uses a global dataset of BBF field experiments to build predictive models with three machine learning algorithms for crop yields and N₂O emissions, and to assess BBFs’ potential to increase yields and mitigate emissions in China’s major crops. …”
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Research on the spatial layout of the elderly care industry based on explainable machine learning: A case study of Hangzhou(基于可解释性机器学习的养老产业空间布局研究)... by 曾笑奇(ZENG Xiaoqi), 赵秋皓(ZHAO Qiuhao), 冯友建(FENG Youjian)

“…The results indicate that∶ (1) SHAP effectively interprets the results of the machine learning algorithms; (2) Most factors, such as population size and government institutions, positively impact the layout of elderly care facilities, whereas other factors, such as financial service facilities, negatively impact their layout; (3) Future construction of elderly care facilities in Hangzhou should prioritize the central districts of Shangcheng and Gongshu as well as their surrounding areas, while development in Fuyang and Lin'an districts could be moderated. …”
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Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

“…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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Systemic immune-inflammatory biomarkers combined with the CRP-albumin-lymphocyte index predict surgical site infection following posterior lumbar spinal fusion: a retrospective stu... by Zixiang Pang, Jiawei Liang, Jiayi Chen, Yangqin Ou, Qinmian Wu, Shengsheng Huang, Shengbin Huang, Yuanming Chen

“…Internal validation employed ROC analysis and calibration curves, while Shapley Additive Explanations (SHAP) values interpreted feature importance in the optimal model.ResultsAmong 2,921 screened patients, 1,272 met inclusion criteria. …”
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Surface Clay and Mineral Exploration Using Hyperspectral Imaging: Advanced Techniques for Geospatial Analysis by S. Raut, N. Andure, A. Kadam, A. Dongare, A. Fulari, G. M. Sayyad, S. B. Sayyad, S. K. Shaikh, S. Sawant

“…Traditional approaches such as geological mapping, geochemical assays, and field surveys, while fundamental, often prove inefficient in terms of time and resources, especially in the challenging topography of the Aravalli Range. …”
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A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

“…Conclusions Compared with the baseline model, YAC-Net optimizes the model structure and simplifies the parameters while ensuring the detection performance. …”
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