The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations—a narrative review by Prasanthi Samathoti, Rajasekhar Komarla Kumarachari, Sarad Pawar Naik Bukke, Eashwar Sai Komarla Rajasekhar, Ashish Ashokkumar Jaiswal, Zohre Eftekhari

“…Nanomedicine leverages nanoparticles for targeted drug delivery, enhancing therapeutic efficacy while minimizing adverse effects. Concurrently, AI algorithms facilitate early cancer detection, personalized treatment planning, and predictive analytics, thereby optimizing clinical outcomes. …”
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Techno-economic modeling and analysis of a PV EV charged with battery energy storage system (BESS) on Kalimantan Island by Aripriharta, Satria Adiguna, Arif N. Afandi, Muhammad Cahyo Bagaskoro

“…Results show Tarakan as the most optimal location, generating 215,804.88 kWh for IDR 916.9/kWh and lowering emissions by 435,884.29 kgCO2e, while Samarinda is the least optimal location. …”
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Implementation and Performance of Lightweight Authentication Encryption ASCON on IoT Devices by Gabriela Cagua, Valerie Gauthier-Umana, Carlos Lozano-Garzon

“…Lightweight cryptographic algorithms have emerged to address these challenges, with ASCON gaining recognition for its robustness and efficiency. …”
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A Systematic Review of CNN Architectures, Databases, Performance Metrics, and Applications in Face Recognition by Andisani Nemavhola, Colin Chibaya, Serestina Viriri

“…Overall, the findings emphasize the need for advanced algorithms capable of handling large-scale, real-world challenges while optimizing accuracy and computational efficiency in face recognition systems.…”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…So far, most studies of NPs have focused on low-dimensional datasets of highly-correlated tasks. While these homogeneous datasets are useful for benchmarking, they may not be representative of realistic transfer learning. …”
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Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals by Bangbei Tang, Bangbei Tang, Yan Li, Yingzhang Wu, Yilun Li, Qizong Yue

“…For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. …”
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Novel channel attention-based filter pruning methods for low-complexity semantic segmentation models by Md. Bipul Hossain, Na Gong, Mohamed Shaban

“…Examples of widely used semantic segmentation models are the U-Net and DeeplabV3+ models. While the aforementioned models have been deemed very successful in segmenting medical targets including organs and diseases in high resolution images, the computational complexity represents a burden for the real-time application of the algorithms or the deployment of the models on resource-constrained platforms. …”
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A Trajectory Data-Driven Study on the Evolution Mechanism and Control Strategies of Lane-Changing Behavior in Intersection Areas of Expressways by Jiayou Wu, Yongwei Lei, Shaoliu Liu, Qiang Luo

“…After analyzing the sample data using traffic flow theory and statistical theory, the following results were obtained: the speeds increase upon entering and decrease upon exiting weaving zones, while headway distances consistently grow. Vehicles in the inner lanes exhibit smoother transitions and higher speeds, while lane-changing speeds range from 10 to 55 km/h (median: 29 km/h) and durations vary from 2 to 18 s (median: 8.5 s). …”
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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…Results indicate that a WNN, using wavelet scattering features ranked by one-way anova, is optimal due to its consistency and reliability, while these features enhance computational efficiency by reducing classifier size. …”
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The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education by Chengchen Hu, Fang Li, Shengguo Wang, Zhi Gao, Shan Pan, Maofeng Qing

“…Moreover, AI-driven innovations in dental biomaterials are optimizing material selection and prosthetic design, while robotic-assisted systems are enhancing precision in clinical training and treatment procedures. …”
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Real-Time Algal Monitoring Using Novel Machine Learning Approaches by Seyit Uguz, Yavuz Selim Sahin, Pradeep Kumar, Xufei Yang, Gary Anderson

“…Monitoring algal growth rates and estimating microalgae concentration in photobioreactor systems are critical for optimizing production efficiency. Traditional methods—such as microscopy, fluorescence, flow cytometry, spectroscopy, and macroscopic approaches—while accurate, are often costly, time-consuming, labor-intensive, and susceptible to contamination or production interference. …”
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Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…In axSpA, AI-driven models using imaging techniques such as sacroiliac radiography, magnetic resonance imaging, and computed tomography have increased diagnostic accuracy, especially for early inflammatory changes. Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
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Towards a smart debt collection system: a Design Science Research approach by Michał Przybyłek, Adam Przybyłek, Konrad Wojciechowski, Illia Shkroba

“…Abstract While manual, expert-based approaches to debt collection have long dominated the industry, the growing complexity and volume of data—resulting in information overload—highlight the need for machine-learning solutions. …”
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Artificial intelligence in personalized rehabilitation: current applications and a SWOT analysis by Elpidio Attoh-Mensah, Arnaud Boujut, Arnaud Boujut, Mikaël Desmons, Anaick Perrochon

“…In conclusion, AI holds immense promise for transforming personalized rehabilitation. While current applications are largely in early stages or proof-of-concept phases, ongoing research, ethical foresight, and strategic collaboration are essential to maximize benefits and minimize risks for optimal patient outcomes.…”
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A Comprehensive Review of Blockchain and Machine Learning Integration for Peer-to-Peer Energy Trading in Smart Grids by Sameen Fatima, Muhammad Junaid Arshad

“…Blockchain enhances energy transactions by making them safer, more transparent, and tamper-proof, while ML optimizes grid performance by improving predictions, fault detection, and anomaly identification. …”
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Computational and experimental study of thermal behavior in the oral cavity for biosensing applications by Yuanzhe Zhao, Jeroen H.M. Bergmann

“…In particular, they offer insights for optimizing sensor placement in thermally stable regions and designing data-driven calibration algorithms capable of compensating for transient environmental disturbances, thereby enhancing the accuracy and reliability of wearable biosensing systems in dynamic conditions.…”
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Evaluation of a Polarimetric Contrast Enhancement Technique as Preprocessing Step for Vessel Detection in SAR Images: Comparison of Frequency Bands and Polarimetric Modes by Alejandro Mestre-Quereda, Juan M. Lopez-Sanchez

“…A potential solution to this issue is to develop methodologies that suppress backscattered signals from the sea while preserving the radar returns from ships. In this work, we analyse a contrast enhancement method which is designed to suppress unwanted sea clutter while preserving signals from potential ships. …”
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SDGTrack: A Multi-Target Tracking Method for Pigs in Multiple Farming Scenarios by Tao Liu, Dengfei Jie, Junwei Zhuang, Dehui Zhang, Jincheng He

“…In pig farming, multi-object tracking (MOT) algorithms are effective tools for identifying individual pigs and monitoring their health, which enhances management efficiency and intelligence. …”
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synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package by Kangning Diao, Zack Li, Richard D. P. Grumitt, Yi Mao

“…This facilitates powerful inference algorithms, such as Hamiltonian Monte Carlo (HMC) and gradient-based optimization, which enables inference over models that would otherwise be computationally prohibitive. …”
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