Transabdominal ultrasound for the characterization and follow-up of cystic pancreatic lesions by Julian Seelig, Maria Heni, Max Seitzinger, Kien Vu Trung, Jürgen Feisthammel, Marcus Hollenbach, Robert Henker, Albrecht Hoffmeister, Jonas Rosendahl, Valentin Blank, Thomas Karlas

“…Cross-method morphological assessments were analysed, and a patient-specific algorithm for selecting the appropriate monitoring method was developed. …”
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Design and validation of a CFD model for energy-efficient Ni-Co-Mn cathode calcination process by Jaeseop Jo, Minyoung Hwang, Jungeui Lee, Joo Hyun Park

“…The primary objective is to quantitatively predict and optimize energy consumption in high-temperature solid-state synthesis processes. …”
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Brain structural features with functional priori to classify Parkinson’s disease and multiple system atrophy using diagnostic MRI by Kai Zhou, Jie Li, Rui Huang, Jiali Yu, Rong Li, Wei Liao, Fengmei Lu, Xiaofei Hu, Huafu Chen, Qing Gao

“…The structure constrained super-resolution network (SCSRN) algorithm was employed to reconstruct clinical 2D MRI data for 56 PD and 58 MSA patients. …”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…These technologies offer reliable and efficient solutions for predictive maintenance in agricultural machinery, enabling proactive intervention in the early stages of catastrophic failures. …”
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Filamentary Hierarchies and Superbubbles. I. Characterizing Filament Properties across a Simulated Spiral Galaxy by Rachel Pillsworth, Erica Roscoe, Ralph E. Pudritz, Eric W. Koch

“…By adapting the FilFinder algorithm of E. W. Koch & E. W. Rosolowsky, we extract over 500 filaments ranging up to 10 kpc in scale, to derive the probability distribution functions for filament masses and lengths, magnetic field orientations, and the gravitational stability and fragmentation patterns of filaments. …”
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Real-Time Interpretation Model of Reservoir Characteristics While Underbalanced Drilling Based on UKF by Miao He, Yihang Zhang, Mingbiao Xu, Jun Li, Jianjian Song

“…This study presents a novel interpretation model for reservoir characteristics while underbalanced drilling (UBD), by incorporating an unscented Kalman filter (UKF) algorithm in a three-phase variable mass flow model of oil, gas, and liquid. …”
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Data-Driven Approach for Passenger Mobility Pattern Recognition Using Spatiotemporal Embedding by Chao Yu, Haiying Li, Xinyue Xu, Jun Liu, Jianrui Miao, Yitang Wang, Qi Sun

“…Third, a density-based clustering algorithm is introduced to identify passenger mobility patterns based on the embedded dense trip vectors. …”
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Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network by Can Liu, Peng He, Ru Qiao, Xiaoyan Yang, Changsong Ding, Fuyuan He

“…In this study, we employed the random walk with restart (RWR) algorithm on the LUAD protein-protein interaction (PPI) network to predict ferroptosis-related target genes. …”
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In Situ Monitoring and Numerical Experiments on Vertical Deformation Profiles of Large-Scale Underground Caverns in Giant Hydropower Stations by Hao Wu, Jian Liu, Xiaogang Wang, Lipeng Liu, Zhenhua Tian

“…After fitting the complete VDP curve with a Levenberg-Marquardt algorithm, we verify its validity by comparing predicted data with in situ monitoring data. …”
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A Clinical Validation of a Diagnostic Test for Esophageal Adenocarcinoma Based on a Novel Serum Glycoprotein Biomarker Panel: PromarkerEso by Jordana Sheahan, Iris Wang, Peter Galettis, David I. Watson, Virendra Joshi, Michelle M. Hill, Richard Lipscombe, Kirsten Peters, Scott Bringans

“…A panel of glycoproteins: alpha-1-antitrypsin, alpha-1-antichymotrypsin, complement C9 and plasma kallikrein, were combined with clinical factors (age, sex and BMI) in an algorithm to categorize the samples by the risk of EAC. …”
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Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model by Bo Hu, Yue Sun, Wei Huang, Changzheng Shao, Tao Niu, Xin Cheng, Kaigui Xie

“…However, the price elasticity curve of the DR resources is influenced by consumers' behavioral uncertainty and therefore is difficult to predict. Consequently, additional risk may be introduced to composite power system reliability. …”
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Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence by Joss Langford, Ahmed Barakat, Engy Daghash, Harvinder Singh, Alex V. Rowlands

“…Results: We found that upper arm angle and posture type during sling wear can be predicted from a sling sensor alone (R² = 0.79, <i>p</i> < 0.001 and Cohen’s kappa = 0.886, respectively). …”
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LSAF-LSTM-Based Self-Adaptive Multi-Sensor Fusion for Robust UAV State Estimation in Challenging Environments by Mahammad Irfan, Sagar Dalai, Petar Trslic, James Riordan, Gerard Dooly

“…Validated on an in-house integrated UAV platform and evaluated against high-precision RTK ground truth, the algorithm incorporates deep learning-predicted fusion weights into an optimization-based odometry pipeline. …”
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Determining IFI44 as a key lupus nephritis’s biomarker through bioinformatics and immunohistochemistry by Yue Tan, Xueyao Wang, Deyou Zhang, Jiahui Wang, Shuxian Wang, Jinyu Yu, Hao Wu

“…Additionally, the study characterizes the immune profiles of LN patients through the CIBERSORT algorithm, focusing on the role of interferon-inducible protein 44 (IFI44) as a key biomarker.Results IFI44 shows elevated expression in LN-affected kidneys, compared to healthy controls. …”
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EEG-Driven Arm Movement Decoding: Combining Connectivity and Amplitude Features for Enhanced Brain–Computer Interface Performance by Hamidreza Darvishi, Ahmadreza Mohammadi, Mohammad Hossein Maghami, Meysam Sadeghi, Mohamad Sawan

“…After preprocessing (resampling, normalization, bandpass filtering), FBCSP and multi-lag PLV features were fused, and the ReliefF algorithm selected the most informative subset. A feedforward neural network achieved average metrics of: Pearson correlation 0.829 ± 0.077, R-squared value 0.675 ± 0.126, and root mean square error (RMSE) 0.579 ± 0.098 in predicting EMG amplitudes indicative of arm movement angles. …”
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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

“…The proposed approach enhances predictive performance and generalization by leveraging ensemble learning strategies such as bagging and adaptive boosting. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Identification of nitric oxide-mediated necroptosis as the predominant death route in Parkinson’s disease by Ting Zhang, Wenjing Rui, Yue Sun, Yunyun Tian, Qiaoyan Li, Qian Zhang, Yanchun Zhao, Zongzhi Liu, Tiepeng Wang

“…Using the Scaden deep learning algorithm, we predicted neurocyte subtypes and modelled dynamic interactions for five classic cell death pathways to identify the predominant routes of neuronal death during PD progression. …”
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Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study by Jirui Niu, Ruotian Deng, Zipu Dong, Xue Yang, Zhaohui Xing, Yin Yu, Jian Kang

“…However, despite the substantial benefits of AI and ML in vaccine innovation, challenges remain regarding data quality, algorithm reliability, and ethical considerations. …”
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Machine learning of automatic hierarchical multi-label classification method for identifying metal failure mechanisms by Ruitong Han, Chang-Bo Liu, Wanting Sun, Shuai Yu, Haoran Zheng, Lin Deng

“…To ensure that the model predictions are sufficiently reliable, a multi-level gradcam algorithm is also introduced for checking the regions of interest of the Hierarchical model at two levels and the comparisons are made with human experts. …”
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