Evaluation of four clinical decision rules in children with minor head trauma: NEXUS II, PECARN, CHALICE, and CATCH by Majid Zamani, Farhad Heydari, Farzin Feyzollahi, Mehrdad Esmaillian, Amir Bahador Boroumand

“…Background: Clinical decision rules could potentially help emergency department (ED) trauma triage, allowing clinicians to prioritize treatment for the most severely injured patients.Objectives: This study evaluated and compared the diagnostic accuracy of the National Emergency X-radiography Utilization Study II (NEXUS II), the Pediatric Emergency Care Applied Research Network (PECARN), the Canadian Assessment of Tomography for Childhood Head Injury (CATCH), and the Children’s Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) in identifying intracranial injury (ICI) in children with minor head trauma.Methods: This prospective, cross-sectional, descriptive-comparative study was conducted on children with mild head trauma who presented to the ED. …”
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Cost-Effectiveness Analysis of a Machine Learning–Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at... by Charlotte Havreng-Théry, Arnaud Fouchard, Fabrice Denis, Jacques-Henri Veyron, Joël Belmin

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Global Three‐Dimensional Water Vapor Feature‐Tracking for Horizontal Winds Using Hyperspectral Infrared Sounder Data From Overlapped Tracks of Two Satellites by Amir Ouyed, Nadia Smith, Xubin Zeng, Thomas Galarneau Jr., Hui Su, Ross D. Dixon

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Improved Water Level Retrieval in Complex Riverine Environments: Sentinel‐3 and Sentinel‐6 Altimetry Over China's Rivers by Chenqi Fang, Di Long, Qi Huang, Fanyu Zhao, Huaichuan Liu, Xingwu Duan, Aizhong Hou

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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…The approbation of the developed models on real experimental curves showed a high quality of their approximation, comparable to other methods. Thus, the k-nearest neighbor algorithm and SVM can be used to predict the rheological parameters of polymers as an alternative to artificial neural networks and the CatBoost algorithm, requiring less effort to preset adjustment. …”
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Dose-Weighted Network Pharmacology: Evaluating Traditional Chinese Medicine Formulations for Lumbar Disc Herniation by Zhou C, Xiang T, Yu Y, Ma H, Liu C, Yang F, Yang L

“…This study introduces dose-weighted network pharmacology, a novel approach that incorporates drug dosage as a quantitative factor into network analysis to evaluate better and compare the therapeutic potential of TCM formulations.Methods: This study combines drug dosage with the PPI network to propose a theoretical algorithm for comparing the therapeutic efficacy of different traditional Chinese medicine formulations. …”
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Evaluation and Choice of an Anti-Aircraft Missile System under Uncertain Conditions Based on Fuzzy-Integral Calculus and Hierarchical Cluster Analysis by Sergey Sveshnikov, Victor Bocharnikov, Yuri Mudrak

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Nonlinear transformation of complex amplitudes via quantum singular value transformation by Naixu Guo, Kosuke Mitarai, Keisuke Fujii

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18F-FDG dose reduction using deep learning-based PET reconstruction by Ryuji Akita, Komei Takauchi, Mana Ishibashi, Shota Kondo, Shogo Ono, Kazushi Yokomachi, Yusuke Ochi, Masao Kiguchi, Hidenori Mitani, Yuko Nakamura, Kazuo Awai

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A novel method for power transformer fault diagnosis considering imbalanced data samples by Jun Chen, Yong Wang, Lingming Kong, Yilong Chen, Mianzhi Chen, Qian Cai, Gehao Sheng

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Calculating response functions of coupled oscillators using quantum phase estimation by Sven Danz, Mario Berta, Stefan Schröder, Pascal Kienast, Frank K. Wilhelm, Alessandro Ciani

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Combined mechanistic and machine learning method for construction of oil reservoir permeability map consistent with well test measurements by Evgenii Kanin, Alsu Garipova, Sergei Boronin, Vladimir Vanovskiy, Albert Vainshtein, Andrey Afanasyev, Andrei Osiptsov, Evgeny Burnaev

“…We also provide recommendations for further development of the proposed algorithm to account for geological realism.…”
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An optimized potential formula of the $ m \times n $ apple surface network and its application of potential in path planning by Yangming Xu, Yanpeng Zheng, Xiaoyu Jiang, Zhaolin Jiang, Zhibin Liu

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Optimization of emission scheduling in microgrids with electric vehicle integration by Peng Cao, Daowang Wang, Xingyang Jiang

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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

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A Hybrid Machine Learning Approach for Estimating Aboveground Biomass and Carbon Stock in Tanzania’s Miombo Woodlands by Emmanuel F. Chifunda, Ramkumar T. Balan, Peter J. Kirigiti

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Application of predator-prey optimization for task scheduling in cloud computing by Zahra Jalali Khalil Abadi, Behnam Mohammad Hasani zade, Najme Mansouri, Mohammad Masoud Javidi

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Methodology for Determining the Probability of Damage to UAV as a Result of Exposure to Atmospheric Environmental Factors by D. G. Belonozhko, I. D. Korolev, Yu. O. Chernyshev, N. N. Ventsov

“…The computational complexity of the algorithm implementing the technique depends significantly on the number of qualitative assessments of atmospheric impacts on UAV.Results. …”
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Bias-field digitized counterdiabatic quantum optimization by Alejandro Gomez Cadavid, Archismita Dalal, Anton Simen, Enrique Solano, Narendra N. Hegade

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Synthetic Ensemble Forecasts: Operations‐Based Evaluation and Inter‐Model Comparison for Reservoir Systems Across California by Zachary P. Brodeur, William Taylor, Jonathan D. Herman, Scott Steinschneider

“…Second, we develop a new synthetic ensemble forecasting algorithm and compare it to a previous algorithm using this validation framework across a set of stylized, hydrologically diverse reservoir systems in California. …”
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