Coprime dual-velocity encoding for extended velocity dynamic range in 4D flow magnetic resonance imaging by Marta Beghella Bartoli, Sara Boccalini, David Chechin, Loic Boussel, Philippe Douek, Damien Garcia, Monica Sigovan

“…Three patients with different cardiac pathologies were scanned in order to evaluate the in vivo feasibility of the proposed method. …”
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Modeling of snow cover on glaciers of the Caucasus and Kamchatka Peninsula by I. M. Sushintsev, E. D. Drozdov, P. A. Toropov, V. N. Mikhalenko, M. A. Vorobiev, A. G. Hayredinova

“…The paper evaluates the possibility of using a computing complex that includes a SNOWPACK model and an algorithm for calculating orographic precipitation addition to reproduce snow cover in mountainous areas. …”
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Express Immunochromatographic Detection of Rotavirus and Adenovirus Antigens in Pre-Hospital Differential Diagnosis of Acute Abdominal Pain in Children by Ekaterina A. Romanova, Leyla S. Namazova-Baranova, Elena Yu. Dyakonova, Aleksey Yu. Romanov, Kazbek S. Mezhidov, Zharadat I. Dohshukaeva

“…The frequency of leukocytosis detection in a clinical blood test was not different in patients with different results of ICA. …”
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Clinically interpretable multiclass neural network for discriminating cardiac diseases by Agnese Sbrollini, Chiara Leoni, Micaela Morettini, Cees A. Swenne, Laura Burattini

“…Classification performance was evaluated by the area under the curve of the receiver operating characteristics. …”
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Design and predict the potential of imidazole-based organic dyes in dye-sensitized solar cells using fingerprint machine learning and supported by a web application by Mohamed M. Elsenety

“…Based on the RDKit library, several fingerprints such as Molecular ACCess System, Avalon, Daylight, Pharmacophore and Morgan with different radius (r2, r3, r4), were studied. In addition, more than 20 ML algorithms using different cross validation (3, 5, 7, 10) were also evaluated. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari, M. Murugappan, Javeed Shaikh-Mohammed, Muhammad E. H. Chowdhury

“…Using three statistical measures Lyapunov exponents (LE), Correlation Dimension (CD), and approximate entropy (AE), we evaluated the performance of machine learning algorithms over different data lengths. …”
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Integrating taxonomic and phenotypic information through FISH-enhanced flow cytometry for microbial community dynamics analysis by Valérie Mattelin, Josefien Van Landuyt, Frederiek-Maarten Kerkhof, Yorick Minnebo, Nico Boon

“…Finally, a predictive algorithm was trained to correctly classify samples in the differently treated groups. …”
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Human identification via digital palatal scans: a machine learning validation pilot study by Ákos Mikolicz, Botond Simon, Aida Roudgari, Arvin Shahbazi, János Vág

“…Abstract Background This study aims to validate a machine learning algorithm previously developed in a training population on a different randomly chosen population (i.e., test set). …”
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Multi-Feature Fusion for Estimating Above-Ground Biomass of Potato by UAV Remote Sensing by Guolan Xian, Jiangang Liu, Yongxin Lin, Shuang Li, Chunsong Bian

“…Six advanced modeling algorithms, including random forest (RF), partial least squares regression (PLSR), multiple linear regression (MLR), simple linear regression (SLR), ridge regression (RR), and lasso regression (LR) models, were adopted to evaluate the ability of estimating AGB by single feature and multi-feature information fusion. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Screening of serum biomarkers in patients with PCOS through lipid omics and ensemble machine learning. by Ji-Ying Chen, Wu-Jie Chen, Zhi-Ying Zhu, Shi Xu, Li-Lan Huang, Wen-Qing Tan, Yong-Gang Zhang, Yan-Li Zhao

“…Results indicated that different lipid metabolites not only differ between groups but also have close effects on different corresponding clinical indexes. …”
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MRFB-Net: A Novel Attention Pooling Network With Modified Receptive Field Block for Uterine Fibroid Segmentation by Yun Jiang, Xiaokang Ding, Hongmei Zhou

“…The evaluation results demonstrate the accuracy and reliability of the proposed MRFB-Net, as well as its adaptability to different types of medical images. …”
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Proactive dynamic flooding regulations for river basins in China’s arid and semi-arid region of Xinjiang by Xintong Gong, Qiang Zhang, Senlin Tang, Yungang Bai, Vijay P. Singh, Zhenlin Lu

“…We used an improved pre-release constraint algorithm, such as the long-short-series mean correction method, and evaluated the flood stage potential during the aforementioned three intervals. …”
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A Fast Image Encryption Scheme Based on a Four-Dimensional Variable-Parameter Hyperchaotic Map and Cyclic Shift Strategy by Guidong Zhang, Yanhao Zhao, Yanpei Zheng, Yulin Shen, Jun Huang

“…Furthermore, to more accurately evaluate the algorithm’s resistance to differential attacks, we introduce improved metrics—namely, BL-NPCR and BL-UACI—which measure the subtle differences between encrypted images at the binary level. …”
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Registration of 2D C-Arm and 3D CT Images for a C-Arm Image-Assisted Navigation System for Spinal Surgery by Chih-Ju Chang, Geng-Li Lin, Alex Tse, Hong-Yu Chu, Ching-Shiow Tseng

“…Five similarity measure methods of 2D-3D image registration including Normalized Cross-Correlation, Gradient Correlation, Pattern Intensity, Gradient Difference Correlation, and Mutual Information combined with three optimization methods including Powell’s method, Downhill simplex algorithm, and genetic algorithm are applied to evaluate their performance in converge range, efficiency, and accuracy. …”
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Preoperative Prediction of Macrotrabecular-Massive Hepatocellular Carcinoma Using Machine Learning-Based Ultrasomics by Li Y, Duan S, Ren S, Li D, Ma Y, Bu D, Liu Y, Li X, Cai X, Zhang L

“…Ultrasomics models were constructed based on the ultrasound image features of the training set using five different ML algorithms, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), decision tree (DT), and logistic regression (LR). …”
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Landslide and Collapse Susceptibility Analysis in Wenchuan Earthquake-damaged Area Based on Ensemble Learning Methods by DING Jiawei, WANG Xiekang

“…Two state-of-the-art ensemble learning algorithms, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), are introduced to formulate dependable models for appraising susceptibility to landslides and collapses within the confines of Wenchuan County.MethodsA comprehensive evaluation of factors related to topography, geology, meteorology, and hydrology was conducted to select ten evaluative factors: Elevation, slope, aspect, terrain relief, distance to rivers, distance to faults, normalized difference vegetation index (NDVI), land cover type, average annual precipitation, and lithology. …”
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Optimal Selection of the Reference Potential Probe Point in DCPD Real-Time Monitoring of Crack Growth Rate by He Xue, Siyu Gou, Chenqiang Ni, Liang Zhang, Shuai Wang, Youjun Zhao

“…Finite element method is used to analyze the electric potential field of the compact tensile sample, a mathematical model of the measurability and crack independence of the reference potential difference are constructed, genetic algorithm is used to find the optimal reference potential difference (RPD) probe point position, and finally, the crack monitoring experiments are performed to evaluate the feasibility of algorithm optimization results. …”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…Our research introduces a novel multisensor dataset designed to support the creation and evaluation of advanced multisensor fall detection algorithms. …”
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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model by Tingting Hu, Liheng Zhao, Xueling Zhao, Lin He, Xiaoli Zhong, Zhe Yin, Junjie Chen, Yanting Han, Ka Li

“…Abstract Objective The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery. …”
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