Optimisation and Comparison of Markerless and Marker-Based Motion Capture Methods for Hand and Finger Movement Analysis by Valentin Maggioni, Christine Azevedo-Coste, Sam Durand, François Bailly

“…The objective of this study is to evaluate the performance of two markerless approaches (the Leap Motion Controller and the Google MediaPipe API) in comparison to a marker-based one, and to improve the precision of the markerless methods by introducing additional data processing algorithms fusing multiple recording devices. …”
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Constitutive modeling and workability characterization of pre-deformed AZ31 magnesium alloy during hot shear-compression deformation by Junsong Jin, Fangtao Chai, Jinchuan Long, Chang Gao, Shaolei Wang, Pan Zeng, Xuefeng Tang, Pan Gong, Mao Zhang, Lei Deng, Xinyun Wang

“…It introduces twins that promote dynamic recrystallization during hot deformation, thereby improving hot workability and weakening texture. However, uniaxial hot compression tests fail to reflect the deformation behavior of Mg alloys under hot shear-compression process. …”
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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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Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study by P. A. Makar, P. Cheung, C. Hogrefe, A. Akingunola, U. Alyuz, J. O. Bash, M. D. Bell, R. Bellasio, R. Bianconi, T. Butler, H. Cathcart, O. E. Clifton, O. E. Clifton, A. Hodzic, I. Kioutsioukis, R. Kranenburg, A. Lupascu, A. Lupascu, J. A. Lynch, K. Momoh, J. L. Perez-Camanyo, J. Pleim, Y.-H. Ryu, R. San Jose, D. Schwede, D. Schwede, T. Scheuschner, M. W. Shephard, R. S. Sokhi, S. Galmarini

“…</p> <p>Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH<span class="inline-formula">₃</span> bidirectional fluxes. …”
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Effectiveness evaluation of the complex medical and psychological method of treating patients with insomnia by A. V. Vasil'eva, T. A. Karavaeva, Yu. P. Kolesova, D. S. Radionov, D. A. Starunskaya, M. V. Fomicheva, S. M. Abdullaeva

“…The quantitative evaluation of the effectiveness of the method was carried out on seven indicators: (1) Improvement in the subjective characteristics of sleep, (2) Improvement in the quality of sleep, (3) Reduction of the insomnia severity index, (4) Reduction of daytime sleepiness, (5) Reduction of the consequences of sleep disorders, (6) Decreased anxiety, (7) Improved overall clinical impression. …”
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ORGANIZATIONAL ISSUES OF CARDIOREHABILITATION SERVICE IN RUSSIA. THE RESULTS OF PILOT PROJECT “DEVELOPMENT OF REHABILITATION SYSTEM OF CARDIOVASCULAR PATIENTS IN MEDICAL INSTITUTIO... by D. M. Aronov, M. G. Bubnova, S. A. Boytsov, G. Е. Ivanova, A. G. Andreev, О. L. Barbarash, V. V. Belova, V. N. Belov, B. V. Borisov, Е. V. Ivanov, I. М. Karamova, A. V. Karpukhin, V. B. Krasnitskiy, Е. S. Kyblanova, P. А. Lebedev, Е. А. Lisnyak, N. P. Lyamina, Т. N. Mizurova, О. F. Misyura, I. E. Mishina, О. V. Mischenko, S. Yu. Nikulina, N. I. Ostroushko, S. А. Poteshkina, А. S. Sidorov, А. А. Sprikut, I. S. Sukhinina, А. G. Tkacheva, S. А. Ustyugov, G. А. Chumakova

“…To analyze,  how is, under  the  framework of the  Pilot Project, organized and being conducted  the improvement of work of the known departments in exact medical institutions (MI) of RF for rehabilitation of cardiovascular  diseases (CVD) patients  at the  three  steps  under  the current “Order of medical care and medical rehabilitation”, and how do the scientifically proven and types and methods  of cardiorehabilitation (CR) being implemented,  and to try to elaborate  on an exact algorithm for patients course.Material and methods. …”
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Predicting Red Blood Cell Transfusion in Elective Cardiac Surgery: A Machine Learning Approach by Beatriz Lau, Daniel Ramos, Vera Afreixo, Luís M. Silva, Ana Helena Tavares, Miguel Martins Felgueiras, Diana Castro Paupério, João Firmino-Machado

“…Two machine learning algorithms, extreme gradient boosting and neural networks, were employed due to their efficiency in handling complex feature interactions. …”
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Application of the Integral Energy Criterion and Neural Network Model for Helicopter Turboshaft Engines’ Vibration Characteristics Analysis by Serhii Vladov, Maryna Bulakh, Denys Baranovskyi, Eduard Kisiliuk, Victoria Vysotska, Maksym Romanov, Jan Czyżewski

“…It averages the assessment of unique signal processing algorithms, which ensures reliable defect classification under flight vibration conditions. …”
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An intelligible AI-driven decision support system for poststroke mobility assessment by Jin Cheng Liaw, Dominik Raab, Malte Weber, Mario Siebler, Harald Hefter, Dörte Zietz, Marcus Jäger, Andrés Kecskeméthy, Francisco Geu Flores

“…Synergistic interactions between system, and experts via the computed key features may improve quality in diagnosis and objectify therapeutic targets. …”
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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

“…Additionally, data remediation techniques improve data set quality. The ensemble combines Long Short-Term Memory neural networks, Random Forest regression, and Support Vector Machines, optimizing their contributions using heuristic algorithms such as Particle Swarm Optimization. …”
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SSCD-YOLO: Semi-Supervised Cross-Domain YOLOv8 for Pedestrian Detection in Low-Light Conditions by Fangliang Cao, Kai Yan, Hongliang Chen, Zhen Wang, Yunliang Du, Zekang Zheng, Kefan Li, Baozhu Qi, Mingjia Wang

“…First, a CDF-CycleGAN cross-domain image fusion method is designed, which improves the input of CycleGAN using a diffusion model, integrates the self-attention mechanism into the residual network of the CycleGAN generator to design the SA-Block, replaces the linear layer in the CycleGAN discriminator with an autoencoder, and improves the training method of CycleGAN. …”
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Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury by Aref Andishgar, Maziyar Rismani, Sina Bazmi, Zahra Mohammadi, Sedighe Hooshmandi, Behnam Kian, Amin Niakan, Reza Taheri, Hosseinali Khalili, Roohallah Alizadehsani

“…Abstract Machine learning (ML) offers precise predictions and could improve patient care, potentially replacing traditional scoring systems. …”
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Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2... by Monoronjon Dutta, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne, Reda Alhajj

“…The initial algorithmic phase involved image pre-processing of the crop images, using a bilateral filter to improve image quality. …”
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Deep Learning−Driven Exophthalmometry through Facial Photographs in Thyroid Eye Disease by Joonhyeon Park, PhD, Jin Sook Yoon, MD, PhD, Namju Kim, MD, PhD, Kyubo Shin, PhD, Hyun Young Park, MD, PhD, Jongchan Kim, MS, Jaemin Park, MS, Jae Hoon Moon, MD, PhD, JaeSang Ko, MD, PhD

“…This tool presents a promising alternative to traditional exophthalmometry, potentially improving access to reliable proptosis measurement in both clinical and nonspecialist settings. …”
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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…This research offers a theoretical basis for alleviating soil salinization in irrigated area and improving the ecological circumstances of these locales.…”
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Enhancing Breast Cancer Diagnosis With Multi-Resolution Vision Transformers and Robust Decision-Making by Margo Sabry, Hossam Magdy Balaha, Khadiga M. Ali, Tayseer Hassan A. Soliman, Dibson Gondim, Mohammed Ghazal, Norah Saleh Alghamdi, Ayman El-Baz

“…A stacking ensemble method combines predictions from ViT models trained at these levels, improving classification robustness. Postprocessing techniques, including region-growing and fast-marching level set algorithms, refine whole-slide image (WSI) prediction and postprocessing quality. …”
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Advanced Estimation of Winter Wheat Leaf’s Relative Chlorophyll Content Across Growth Stages Using Satellite-Derived Texture Indices in a Region with Various Sowing Dates by Jingyun Chen, Quan Yin, Jianjun Wang, Weilong Li, Zhi Ding, Pei Sun Loh, Guisheng Zhou, Zhongyang Huo

“…Following a two-step variable selection method, Random Forest (RF)-LassoCV, five machine learning algorithms were applied to develop estimation models. …”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…This tool will allow for improved clinical trial designs and accelerate efforts seeking to prevent or delay the onset of T1D.…”
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MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions by Maham Misbah, Misha Urooj Khan, Zeeshan Kaleem, Ali Muqaibel, Muhamad Zeshan Alam, Ran Liu, Chau Yuen

“…To address these challenges, we present an improved YOLOv5 architecture named multiscale feature map GhostNet (MSF-GhostNet) by introducing GhostConv and C3Ghost modules to reduce the redundant operations in the head and neck. …”
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Functional Connectivity Metrics in Temporal Lobe Epilepsy: A Machine Learning Perspective With MEG by M. V. Suhas, N. Mariyappa, A. Karunakar Kotegar, M. Ravindranadh Chowdary, K. Raghavendra, Ajay Asranna, L. G. Viswanathan, H. Anitha, Sanjib Sinha

“…We employ machine learning algorithms to classify TLE and HC groups based on these metrics. …”
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