Combined Treatment of Giant Extra-Intracranial Arteriovenous Malformation by V. A. Lukyanchikov, V. A. Dalibaldyan, S. Yu. Roschin, I. I. Goncharova, G. K. Guseynova, S. V. Zhuravel, V. A. Karanadze, A. S. Koblik, V. E. Ryabukhin, A. V. Sachkov, A. A. Grin, V. V. Krylov

“…In addition, arteriovenous malformations can cause nutritional disorders (trophism) of the soft tissues located near them. Extracranial arteriovenous malformations are rare and dangerous vascular anomalies. …”
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AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review by Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala

“…The algorithms with the highest DSC deployed an encoder–decoder architecture. …”
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Machine learning for improved size estimation of complex marine particles from noisy holographic images by Zonghua Liu, Zonghua Liu, Marika Takeuchi, Yéssica Contreras, Thangavel Thevar, Alex Nimmo-Smith, John Watson, Sarah L. C. Giering

“…However, most standard algorithms fail to accurately size objects in reconstructed holograms owing to the high background noise. …”
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Automatic Differentiation‐Based Full Waveform Inversion With Flexible Workflows by Feng Liu, Haipeng Li, Guangyuan Zou, Junlun Li

“…The AD‐based framework not only includes forword modeling and associated gradient computations for wave equations in various types of media from isotropic acoustic to vertically or horizontally transverse isotropic elastic, but also incorporates a suite of objective functions, regularization techniques, and optimization algorithms. By leveraging state‐of‐the‐art AD, objective functions such as soft dynamic time warping and Wasserstein distance, which are difficult to apply in traditional FWI are also easily integrated into ADFWI. …”
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On the Synergy of IoMT Devices and Ceiling-Mounted Systems for Advanced Medical Data Analytics by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos K. Markakis, Athina Bourdena, George Mastorakis

“…Specifically, Twin-Delayed Deep Deterministic Policy Gradients (TD3) and Soft Actor-Critic (SAC) algorithms are adopted to optimize task scheduling and system decisions in dynamic, resource-constrained settings. …”
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Reconstruction of Tokamak Plasma Emissivity Distribution by Approximation with Basis Functions by Tomasz Czarski, Maryna Chernyshova, Katarzyna Mikszuta-Michalik, Karol Malinowski

“…The present study focuses on the development of a diagnostic system for measuring radiated power and core soft X-ray intensity emissions with the goal of detecting a broad spectrum of photon energies emitted from the central plasma region of the DEMO tokamak. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Here, the Random Forest Classifier, a soft computing tool, was utilized on a dataset encompassing 649 student records. …”
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Wave Attenuation by Australian Temperate Mangroves by Ruth Reef, Sabrina Sayers

“…Wave attenuation by natural coastal features is recognised as a soft engineering approach to shoreline protection from storm surges and destructive waves. …”
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Chondrogenic Cancer Grading by Combining Machine and Deep Learning with Raman Spectra of Histopathological Tissues by Gianmarco Lazzini, Mario D’Acunto

“…In particular, in the last years several studies have demonstrated how the diagnostic performances of RS can be significantly improved by employing machine learning (ML) algorithms for the interpretation of Raman-based data. …”
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Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins, Mark Shankle

“…Additionally, a soft-voting ML model ensemble approach is employed to improve performance of yield prediction. …”
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A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

“…Feature wavelengths were extracted using Bootstrap Soft Shrinkage (BOSS) and Competitive Adaptive Reweighted Sampling (CARS) algorithms. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Furthermore, process efficiency is often not fully realized due to the reliance on fixed operational recipes.This study presents a digital twin framework for a pilot-scale HGMS system, integrating real-time monitoring, automated control, advanced mechanistic models, and multi-objective optimization using Bayesian algorithms. The framework was validated for robustness, scalable data handling, and predictive control. …”
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EXPERIENCE OF SUCCESSFUL ACNEFORM ERUPTIONS TREATMENT IN PATIENT WITH MULTIPLE MELANOMA by O. V. Minkina, A. S. Dvornikov, P. A. Skripkina, T. A. Gaydina, E. V. Trushina

“…Subsequently, the patient was verified metastasis in the inginal lymph nodes, in the soft tissues of the hips, to liver. Acute adverse reaction has developed in a short time after getting the anti-tumor target therapy as generalized acneform rush and itching of the skin. …”
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Toward Salient Key Phrase for Candidate Topic Detection by Yasser S. Jude, Wafaa Al-Hameed

“…These results highlight the algorithm's ability to extract relevant information from text documents.…”
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Statistical Analysis of Compact Single-source Flares Observed by STIX by Michalina Litwicka, Tomasz Mrozek, Arun K. Awasthi, Marek Siarkowski, Marek Stęślicki, Janusz Sylwester, Barbara Sylwester

“…Accordingly, we present a statistical investigation of 550 flares showing one compact source in images reconstructed with the MARLIN, Expectation Maximization, and Forward Fit algorithms in the 6–10 keV soft X-ray (SXR) energy channel of the Spectrometer Telescope for Imaging X-rays (STIX), on board Solar Orbiter. …”
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Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Meanwhile, correlation analysis and recursive feature elimination were used for feature screening before machine learning model development. Then fifteen algorithms were used to establish models, and an ensemble model was established through soft voting based on the top five performance algorithms. …”
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Detection and Pattern Recognition of Chemical Warfare Agents by MOS-Based MEMS Gas Sensor Array by Mengxue Xu, Xiaochun Hu, Hongpeng Zhang, Ting Miao, Lan Ma, Jing Liang, Yuefeng Zhu, Haiyan Zhu, Zhenxing Cheng, Xuhui Sun

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Fuzzy Controlled MPPT to Grid Connected PV Systems by Sukumar G. Durga, Prasad R. Ramanjan, Vardhan R. Harsha, Pakkiraiah B., Krishna Ch. Leela

“…Among the various methods available, high- performance soft computing techniques serve as robust MPPT strategies. …”
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Artificial Intelligence Control Methodologies for Shape Memory Alloy Actuators: A Systematic Review and Performance Analysis by Stefano Rodinò, Giuseppe Rota, Matteo Chiodo, Antonio Corigliano, Carmine Maletta

“…This synthesis establishes AI as a transformative paradigm for SMA actuation, enabling precise control in aerospace, biomedical, and soft robotics applications.…”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. …”
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