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

“…Current research focuses mainly on improving the safety and effectiveness of thrombectomy devices and reducing complications during surgical procedures. …”
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A Multi-Strategy Active Learning Framework for Enhanced Peripheral Blood Cell Image Detection by Yuheng Feng, Jiangtao He, Linjin Wang, Wuchen Yang, Sihan Deng, Lanlin Li, Xinwei Li

“…The framework reduces annotation costs and improves detection performance by combining uncertainty-based selection, diversity querying, and density-based querying to prioritize the most informative and diverse samples. …”
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Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review by Xikuan Zhang, Jin Chai, Yongfu Zhan, Danfeng Cui, Xin Wang, Libo Gao

“…Despite significant progress in design and application, challenges remain, particularly in mass production, wireless integration, real-time data processing, and long-term stability. To improve mass production feasibility, optimizing fabrication processes, reducing material costs, and incorporating automated production lines are essential for scalability and defect reduction. …”
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UAV as a Bridge: Mapping Key Rice Growth Stage with Sentinel-2 Imagery and Novel Vegetation Indices by Jianping Zhang, Rundong Zhang, Qi Meng, Yanying Chen, Jie Deng, Bingtai Chen

“…Based on the maximum relevance minimum redundancy (mRMR) algorithm, we identified an optimal subset of features that were both highly correlated with rice growth stages and mutually complementary. …”
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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

“…Automated detection can eliminate the dependence on professionals, but the current detection algorithms require large computational resources, which increases the lower limit of automated detection. …”
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Performance of Various Artificial Intelligence Models for Predicting Temperature in an Industrial Building—A Case Study by Johan Roussel, Zoubeir Lafhaj, Pascal Yim, Thomas Danel, Laure Ducoulombier

“…The main objective is to identify an optimal algorithm that enables efficient thermal management, which is essential for ensuring product quality, maintaining process safety, and optimizing energy consumption. …”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Methods A multi-layered design approach was adopted. PQC algorithms (e.g., CRYSTALS-Dilithium) were integrated at the blockchain consensus layer to resist quantum attacks. …”
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2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration by Ke-Yu Yao, Derek Ka-Hei Lai, Hyo-Jung Lim, Bryan Pak-Hei So, Andy Chi-Ho Chan, Patrick Yiu-Man Yip, Duo Wai-Chi Wong, Bingyang Dai, Xin Zhao, Siu Hong Dexter Wong, James Chung-Wai Cheung

“…Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. …”
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A deep contrastive learning-based image retrieval system for automatic detection of infectious cattle diseases by Veerayuth Kittichai, Morakot Kaewthamasorn, Apinya Arnuphaprasert, Rangsan Jomtarak, Kaung Myat Naing, Teerawat Tongloy, Santhad Chuwongin, Siridech Boonsang

“…The findings may aid in the early diagnosis of anaplasmosis infections in remote areas without access to veterinary care or costly molecular diagnostic tools.…”
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Deep Residual Transfer Ensemble Model for mRNA Gene-Expression-Based Breast Cancer by Job Prasanth Kumar Chinta Kunta, Vijayalakshmi A. Lepakshi

“…Being consensus-driven solution, it improved reliability of breast cancer prediction results. …”
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A bayesian network model for neurocognitive disorders digital screening in Chinese population: development and validation study by Yifan Yu, Shuaijie Zhang, Hongkai Li, Fuzhong Xue

“…Early screening for neurocognitive disorders is conducive to improving patients’ quality of life and reducing healthcare costs. …”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…., sparse spike-driven operations and bio-plausible learning rules) for improving energy efficiency and performance, thereby enabling efficient CL algorithms (e.g., unsupervised learning approach) executed in dynamically-changed environments with resource-constrained computing systems. …”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Their implementation in the industry can reduce maintenance costs, optimize motor operation, and prevent unexpected failures.…”
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Analysis of Energy Sustainability and Problems of Technological Process of Primary Aluminum Production by Yury Valeryevich Ilyushin, Egor Andreevich Boronko

“…In this work, a methodological analysis of modern theoretical and numerical methods for studying MHDS was carried out, and approaches to optimizing magnetic fields and control algorithms aimed at stabilizing the process and reducing energy costs were considered. …”
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The impact of artificial intelligence on the economic productivity of enterprises by Šović Milena, Brkić Ivana

“…It also analyses the challenges of implementing AI technology, such as ethical concerns, data privacy, and integration costs. The research findings provide insight into best practices and guidelines for the optimal use of AI in the business sector, with the aim of improving business performance and ensuring long-term business sustainability.…”
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The Impact of AI Software on Financial Transactions by Li Boyang

“…This paper explores AI’s applications in quantitative trading, risk forecasting, and intelligent customer interactions, demonstrating its ability to optimize decision-making and reduce operational costs. …”
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Investigating the hydrogen renaissance in the global energy transition with AI integration by Abderrahim Lakhouit

“…In storage, AI-driven algorithms are improving the management of hydrogen in large-scale storage systems, helping to mitigate issues such as leakage and optimizing storage conditions. …”
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The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials by Vera Malheiro, Beatriz Santos, Ana Figueiras, Filipa Mascarenhas-Melo

“…AI has revolutionized drug discovery and development by enabling rapid and effective analysis of vast volumes of biological and chemical data during the identification of new therapeutic compounds. The algorithms developed can predict the efficacy, toxicity, and possible adverse effects of new drugs, optimize the steps involved in clinical trials, reduce associated time and costs, and facilitate the implementation of innovative drugs in the market, making it easier to develop precise therapies tailored to the individual genetic profile of patients. …”
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A Novel Ensemble Classifier Selection Method for Software Defect Prediction by Xin Dong, Jie Wang, Yan Liang

“…The presence of software defects significantly impacts the quality of software systems and increases development and maintenance costs. To improve system quality and reduce costs, it is necessary to predict software defects in the early stages of the software development lifecycle. …”
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