Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…The framework’s ability to proactively adapt to evolving access patterns while maintaining computational efficiency makes it particularly suitable for large-scale machine learning and scientific computing environments where data placement critically impacts overall system performance.…”
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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…The integration of UAV remote sensing, dynamic modeling, and machine learning distinguishes this work from conventional static systems, offering a scalable and adaptive framework for sustainable farming practices.…”
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Verticox+: vertically distributed Cox proportional hazards model with improved privacy guarantees by Florian van Daalen, Djura Smits, Lianne Ippel, Andre Dekker, Inigo Bermejo

“…Abstract Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. …”
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Intelligent resource allocation in internet of things using random forest and clustering techniques by Nahideh Derakhshanfard, Lida Hosseinzadeh, Fahimeh Rashid Jafari, Ali Ghaffari

“…Numerous current resource allocation methods, such as evolutionary algorithms and multi-agent reinforcement learning, are grossly inefficient at adapting well to IoT networks in light of dynamic and rapid changes due to the inherent computational complexity and high cost. …”
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Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology by Chao-Ming Wang, Cheng-Hao Shao, Yu-Ching Lin

“…In this study, it aims to utilize artificial intelligence (AI) technology to offer the elderly with a healthy and enjoyable exercise and leisure experience. A human–machine interactive system is designed using computer vision, a subfield of AI, to promote positive physical adaptation for the elderly. …”
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Optimizing a Dynamic Vehicle Routing Problem with Deep Reinforcement Learning: Analyzing State-Space Components by Anna Konovalenko, Lars Magnus Hvattum

“…Our goal is to develop an application that can make real-time decisions to maximize total performance while adapting to the dynamic nature of incoming orders. …”
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Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…Developing an intelligent system for analyzing semistructured data requires innovative methods and approaches that combine natural language processing (NLP), machine learning algorithms and big data analytics techniques. …”
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Cryptographic hardness assumptions identification based on discrete wavelet transform by Ke Yuan, Yu Du, Yizheng Liu, Rongjin Feng, Bowen Xu, Gaojuan Fan, Chunfu Jia

“…To address the challenges posed by high-dimensionality, complex data distributions, and difficulty fitting ciphertext features, an ensemble learning model called MHERF is constructed, which combines four classifiers: Decision Tree, Adaptive Boosting, Support Vector Machines, and Gradient Boosting. …”
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Thermal comfort and energy related occupancy behavior in Dutch residential dwellings by Anastasios Ioannou

“…In addition, when indoor temperatures were below the comfort bandwidth, tenants often reported that they felt ‘neutral’. The adaptive model could overestimate as well as underestimate the occupant’s adaptive capacity towards thermal comfort. …”
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Data-Efficient Sowing Position Estimation for Agricultural Robots Combining Image Analysis and Expert Knowledge by Shuntaro Aotake, Takuya Otani, Masatoshi Funabashi, Atsuo Takanishi

“…These findings highlight the potential of interpretable, low-data machine learning models for rapid adaptation to complex agroecological systems and demonstrate a practical approach to combining structured human expertise with sensor-based automation in biodiverse farming environments.…”
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Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases by Htet Yamin Ko Ko, Nitin Kumar Tripathi, Chitrini Mozumder, Sombat Muengtaweepongsa, Indrajit Pal

“…Telemedicine and remote patient monitoring (RPM) systems have been gaining interest and received adaptation in healthcare sectors since the COVID-19 pandemic due to their efficiency and capability to deliver timely healthcare services while containing COVID-19 transmission. …”
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Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

“…To accelerate initialization, software-to-hardware algorithm and structure are developed to automate initialization data sources for different topologies. …”
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Holistic Pose Estimation and Dynamic Motion Analysis for Telerehabilitation of Physically Disabled Individuals by Aleena Kamal, Shaheryar Najam, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Bayan Alabdullah, Jeongmin Park

“…The proposed pipeline begins with depth image preprocessing, followed by human detection using a pre-trained Histogram of Oriented Gradients (HOG)-Support Vector Machine (SVM) model. The human silhouette is segmented using the GrabCut algorithm, enabling robust region-of-interest extraction. …”
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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

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A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy by Barbora Salovska, Wenxue Li, Oliver M. Bernhardt, Pierre-Luc Germain, Qinyue Wang, Tejas Gandhi, Lukas Reiter, Yansheng Liu

“…Here we present a robust workflow that integrates a machine learning algorithm and channel-specific statistical filtering, enabling dynamic adaptation to channel ratio changes across multiplexed experiments and enhancing both coverage and accuracy of protein turnover profiling. …”
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In-Season Automated Mapping of Xinjiang Cotton Based on Cumulative Spectral and Phenological Characteristics by Yongsheng Huang, Yaozhong Pan, Yu Zhu, Xiufang Zhu, Xingsheng Xia, Qiong Chen, Jufang Hu, Hongyan Che, Xuechang Zheng, Lingang Wang

“…Second, using the maximum between-class variance method (OTSU) and Sauvola algorithms, a new local adaptive threshold method (Otsu–Sauvola) was developed for the automatic determination of the classification threshold. …”
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From 6G to <i>SeaX-G</i>: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems by Anastasios Giannopoulos, Panagiotis Gkonis, Alexandros Kalafatelis, Nikolaos Nomikos, Sotirios Spantideas, Panagiotis Trakadas, Theodoros Syriopoulos

“…Furthermore, the critical Artificial Intelligence/Machine Learning (AI/ML) concepts and algorithms are described to highlight their potential in optimizing maritime functionalities. …”
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Unravelling Antimicrobial Resistance in <i>Mycoplasma hyopneumoniae</i>: Genetic Mechanisms and Future Directions by Raziallah Jafari Jozani, Mauida F. Hasoon Al Khallawi, Darren Trott, Kiro Petrovski, Wai Yee Low, Farhid Hemmatzadeh

“…Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. …”
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A Systematic Literature Review of Concept Drift Mitigation in Time-Series Applications by Mujaheed Abdullahi, Hitham Alhussian, Norshakirah Aziz, Said Jadid Abdulkadir, Yahia Baashar, Abdussalam Ahmed Alashhab, Afroza Afrin

“…The findings show that Support Vector Machines (SVM) is the most effective learning algorithms for the detection and adaptation of CD in regression and classification tasks using time-series data. …”
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