Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder by Lei Tang, Liling Wu, Mengqin Dai, Nian Liu, Lu liu

“…By comparing the enrichment results across the five datasets, we found that the cell-killing signaling pathway was consistently present in the enriched signaling pathways of all datasets, suggesting that this pathway may play a crucial role in the pathogenesis of MDD. The random forest algorithm (AUC = 0.788) was selected as the optimal algorithm from 113 machine learning algorithms, leading to the development of a robust and predictive MDD algorithm, highlighting the important role of NPL in MDD. …”
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Vital Sign and Biochemical Data Collection Using Non-contact Photoplethysmography and the Comestai Mobile Health App: Protocol for an Observational Study by Gianvincenzo Zuccotti, Paolo Osvaldo Agnelli, Lucia Labati, Erika Cordaro, Davide Braghieri, Simone Balconi, Marco Xodo, Fabrizio Losurdo, Cesare Celeste Federico Berra, Roberto Franco Enrico Pedretti, Paolo Fiorina, Sergio Maria De Pasquale, Valeria Calcaterra

“…Sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and likelihood ratios will be calculated to determine the ability of the new app to accurately measure vital signs. …”
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Remote Sensing in the 15 µm CO₂ Band: Key Concepts and Implications for the Heat Balance of Mesosphere and Thermosphere by Alexander Kutepov, Artem Feofilov, Ladislav Rezac, Konstantinos S. Kalogerakis

“…We investigated the algorithms and physical models currently applied to remote sensing of the mesosphere and lower thermosphere (MLT) using space-based observations of the CO₂ 15 µm emission. …”
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Design, Construction, and Evaluation of an Automatic Feeder Control System for Sugarcane Billet Planters by B. Abbasian, M. E. Khorasani Ferdavani, H. Zaki Dizaji

“…It delivered performance that matches manual control in terms of cane spillage reduction and planting quality, all while eliminating the need for an operator. …”
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Results of a non-interventional multicenter observational study on the diagnosis and treatment of patients with axial psoriatic arthritis in rea-world clinical practice in the Russ... by T. V. Korotaeva, E. E. Gubar, E. Yu. Loginova, Yu. L. Korsakova, E. A. Vasilenko, I.-D. Yu. Ilyevsky, L. V. Ivanova, E. Yu. Akulinushkina, P. А. Shesternya, O. V. Matveychuk, Yu. Yu. Grabovetskaya, A. A. Barakat, M. A. Korolev, E. V. Zonova, O. A. Georginova, I. V. Kolotilina, I. M. Marusenko, I. B. Vinogradova, O. B. Nesmeyanova, N. E. Grigoriadi, A. V. Petrov, D. G. Krechikova, T. V. Kropotina, S. P. Yakupova, V. I. Mazurov

“…Switching therapy to bDMARDs led to a significant reduction in disease activity.In order to improve the quality of medical care, the Russian clinical guidelines for the treatment of patients with PsA and the algorithms for the diagnosis of axial involvement need to be comprehensively implemented.…”
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Research Progress on Selective Depolymerization of Waste Plastics to High-Quality Liquid Fuels by Xinze LI, Zhicheng LUO, Rui XIAO

“…Economically, catalytic pyrolysis shows near-term viability with a break-even cost of 0.8 – 1.2 $/L for diesel-range fuels, while photocatalysis requires a 50% – 70% reduction in catalyst synthesis costs (e.g., replacing Pt with Fe-Ni sulfides). …”
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Application of PSO-Optimized Twin Support Vector Machine in Medium and Long-Term Load Forecasting under the Background of New Normal Economy by Xiang He, Yan Chen, Kai Hu, Lin Wan

“…Moreover, this paper uses the algorithm to debug the filter and studies the accurate prediction of the fine model by the progressive spatial mapping algorithm and the processing of the data by the vector fitting algorithm. …”
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Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study by Xiao-Qin Luo, Ning-Ya Zhang, Ying-Hao Deng, Hong-Shen Wang, Yi-Xin Kang, Shao-Bin Duan

“…The eXtreme Gradient Boosting algorithm was applied to establish a prediction model for MAKE30. …”
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Principal Component Analysis for Weighted Data in the Procedure of Multidimensional Statistical Forecasting by V. V. Nikitin, D. V. Bobin

“…Therefore, the algorithm for predictive evaluation of a particular indicator is presented in a form that will be convenient for building and practical use of this rule in the future. …”
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Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy by Reshma Kodumuru, Soumavo Sarkar, Varun Parepally, Jignesh Chandarana

“…<b>Results:</b> Applications discussed herein focus on industrial predictive analytics and quality, underpinned by case studies showing improvements in product quality and reductions in downtime. …”
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Forecasting Financial Crashes: Revisit to Log-Periodic Power Law by Bingcun Dai, Fan Zhang, Domenico Tarzia, Kwangwon Ahn

“…We aim to provide an algorithm to predict the distribution of the critical times of financial bubbles employing a log-periodic power law. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…Subsequently, the backward reduction algorithm (BRA) is employed to streamline the resulting scenarios into a more feasible and representative subset, therefore mitigating excessive computational effort. …”
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…By employing regression machine learning algorithms, the research evaluates and enhances system performance, achieving remarkable R-squared accuracy levels of 98.86 % for heating output and 99.89 % for power output predictions. …”
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Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain by Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang, Hongbin Liang, Gang Zhao

“…This algorithm is based on opposition-based learning and its dominant strength. …”
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SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…The results show significant improvements in energy efficiency (21.6% reduction), throughput (14.5% increase), security strength (15.3% enhancement), latency (33.9% decrease), and packet loss rate (12.9% reduction) compared to state-of-the-art approaches. …”
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A Method of Intelligent Driving-Style Recognition Using Natural Driving Data by Siyang Zhang, Zherui Zhang, Chi Zhao

“…Finally, a comparative evaluation of SVM, Random Forest, and KNN recognition indicates the superiority of the SVM algorithm and highlights the effectiveness of dimensionality reduction in optimizing characteristic parameters. …”
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Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

“…Using the heuristic optimization algorithm and entropy-weighted method, the framework achieved average energy savings of 56.62%, a reduction in carbon emissions of 51.60%, and a 24.27% decrease in life-cycle costs. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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