Ten-year cardiovascular risk estimation in type 2 diabetes in Europe using the novel SCORE2-Diabetes model by G. G. Arabidze, M. N. Mamedov, H. R. Akhundova

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Real-Time Parameter Control for Trajectory Generation Using Reinforcement Learning With Zero-Shot Sim-to-Real Transfer by Chang-Hun Ji, Gyeonghun Lim, Youn-Hee Han, Sungtae Moon

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Comparing the Effectiveness of R and S Roughness Parameters on Surfaces Lubricated with Standardized Nominal Particle Size Lubricants by Leire Mendieta-Echevarría, María Ana Sáenz-Nuño, Eva María Rubio

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Spatial and temporal characteristics of water conservation services and rapid response framework for water yield in key ecological zones of the Yiluo River basin by Junqiang Xu, Fan Wang, Chao Ren, Jianmin Bian, Tao Li, Zikai Ping

“…The artificial neural network-based prediction framework achieved high performance with Pearson correlation coefficients exceeding 0.90 across all datasets. …”
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Application of Machine Tool Thermal Error Compensation in Digital Twin-based System by MA Chi, LI Minging, LIU Jialan, HE Jialong, HUA Chunlei, WANG Liang

“…Moreover, a novel collinearity exclusion-based thermal error method is proposed in this work based on the modified tolerance value. A novel prediction model utilizing a strong-convergence chimp optimization algorithm combined with a minimal gated unit-attention mechanism is proposed to characterize the dependence of the current thermal error on the historical thermal informant data, forming strong-convergence chimp optimization algorithm-minimal gated unit-attention ( SC-ChOA-MGU-A) model,ensuring data integrity. …”
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The Intelligent Recognition of Speech Emotions: Survey Study by Ali Abdulwahhab Yehya al_saffar, Fawziya Ramo

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Options for Strengthening the Ensemble of Hypotheses under Uncertainty of the Objective Learning Function Formation by A. F. Chernyavsky, A. I. Kazlova

“…Intelligent learning systems traditionally consist of three main components: a student model, which is a block with information about the student; a model of the learning process that sets the form for presenting information to the student and the type of quality assessment of the student’s activity; the model interface as a link between the expert block of the intelligent learning system and other learning algorithms in the components of educational systems. …”
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Why are Some Recommendation Systems Preferred? by Gaofeng Yi

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Perform The Complex EFG Transform in Cryptography by Emad Kuffi

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Product Dictionary Learning-Based SAR Target Configuration Recognition by Ming Liu, Shichao Chen, Fugang Lu, Junsheng Liu

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Distinguishing Human From Machine: A Review of Advances and Challenges in AI-Generated Text Detection by Serena Fariello, Giuseppe Fenza, Flavia Forte, Mariacristina Gallo, Martina Marotta

“…This advancement offers benefits in various domains, including medicine, education, law, coding, and journalism, but also has negative implications, mainly related to ethical concerns. …”
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Diagnostic Value of F-FDG PET/CT Radiomics in Lymphoma: A Systematic Review and Meta-Analysis by Chaoying Liu MD, Jun Zhao PhD, Heng Zhang PhD, Xinye Ni PhD

“…Six meta-regressions were conducted on study performance, considering sample size, image modality, region of interest (ROI) selection, ROI segmentation, radiomics mode, and algorithms. Results In total, 20 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement were included for this systematic review and meta-analysis. …”
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Wearable Artificial Intelligence for Sleep Disorders: Scoping Review by Sarah Aziz, Amal A M Ali, Hania Aslam, Alaa A Abd-alrazaq, Rawan AlSaad, Mohannad Alajlani, Reham Ahmad, Laila Khalil, Arfan Ahmed, Javaid Sheikh

“…The primary selection criterion was the inclusion of studies that utilized AI algorithms to detect or predict various sleep disorders using data from wearable devices. …”
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Standardized conversion model for retinal thickness measurements between spectral-domain and swept-source optical coherence tomography based on machine learning by Zhongping Tian, Yinning Guo, Xi Chen, Qifeng Zhou, Yuan Liu, Zhizhu Yi, Li Zhang, Li Zhang

“…Machine learning models exhibited superior performance in central subfield thickness (CST) prediction, achieving test set R2 values of 0.930 (LR), 0.926 (LASSO), 0.936 (SVR), and 0.892 (RF). …”
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A comprehensive review on safe reinforcement learning for autonomous vehicle control in dynamic environments by Rohan Inamdar, S. Kavin Sundarr, Deepen Khandelwal, Varun Dev Sahu, Nitish Katal

“…Safe reinforcement learning (SRL) algorithms have been developed to address this issue, prioritizing safe and reliable decisions. …”
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Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours by Venkata V. Chebrolu, Daniel Saenz, Dinesh Tewatia, William A. Sethares, George Cannon, Bhudatt R. Paliwal

“…Novel morphological processing and successive localization (MPSL) algorithms were designed and implemented for achieving autosegmentation. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The proposed procedure ensures building models of outstanding predictive power while using small training datasets, which is beyond the capabilities of benchmark algorithms.…”
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Artificial intelligence in nursing: an integrative review of clinical and operational impacts by Salwa Hassanein, Salwa Hassanein, Rabie Adel El Arab, Rabie Adel El Arab, Amany Abdrbo, Mohammad S. Abu-Mahfouz, Mastoura Khames Farag Gaballah, Mohamed Mahmoud Seweid, Mohamed Mahmoud Seweid, Mohammed Almari, Husam Alzghoul

“…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”
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Forecast Model of TV Show Rating Based on Convolutional Neural Network by Lingfeng Wang

“…Therefore, this paper introduces the convolutional neural network structure to predict the TV program rating data. First, it briefly introduces artificial neural networks and deep learning methods and focuses on the algorithm principles of convolutional neural networks and support vector machines. …”
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Study on the Effect of Apple Size Difference on Soluble Solids Content Model Based on Near-Infrared (NIR) Spectroscopy by Xiaogang Jiang, Mingwang Zhu, Jinliang Yao, Yuxiang Zhang, Yande Liu

“…To better address the effects of apple size differences, data fusion techniques were used to perform an intermediate fusion of apple fruit diameter and spectra, firstly, the competitive adaptive reweighting algorithm (CARS) and the continuous projection algorithm (SPA) were used to select spectral variables and build their prediction models for apple SSC, respectively, and the results showed that the models built with 61 spectral variables selected by CARS had better performance, greatly reduced the amount of data involved in modeling, effectively simplified the model, and improved the stability of the model. …”
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