University proceedings. Volga region. Technical sciences by A.A. Ignatiev, V.A. Dobryakov, V.A. Revyakin

“…The purpose of the work is to algorithmize the process of processing vibration measuring information when generating estimates of the dynamic quality of the machine by the stability margin of the dynamic system in order to identify the initial phase of catastrophic wear of the cutter. …”

AI-Driven Predictive Modeling for Lung Cancer Detection and Management Using Synthetic Data Augmentation and Random Forest Classifier by Nisreen Innab, Asma Aldrees, Dina Abdulaziz AlHammadi, Abeer Hakeem, Muhammad Umer, Shtwai Alsubai, Silvia Trelova, Imran Ashraf

“…Extensive experimental evaluation for this method included testing nine classification algorithms. …”
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Construction and validation of a readmission risk prediction model for elderly patients with coronary heart disease by Hanyu Luo, Benlong Wang, Rui Cao, Jun Feng

“…ROC curves and calibration plots were used to evaluate the prediction performance of the model. For external validation, 143 patients who were admitted between February and June 2023 from a different associated hospital in Lu'an City were also used.ResultsThe XGBoost model demonstrated the most accurate prediction performance out of the five machine learning techniques. …”
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A robust and accurate feature matching method for multi-modal geographic images spatial registration by Kai Ren, Weiwei Sun, Xiangchao Meng, Gang Yang, Jiangtao Peng, Binjie Chen, Jiancheng Li

“…Finally, the affine transformation parameters are calculated based on inliers, and multi-modal image registration is realized. RAMMR is evaluated on different multi-modal datasets and compared with some state-of-art methods. …”
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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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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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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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Development of a machine learning prediction model for loss to follow-up in HIV care using routine electronic medical records in a low-resource setting by Tamrat Endebu, Girma Taye, Wakgari Deressa

“…The performance of each algorithm was evaluated through a 10-fold cross-validation approach. …”
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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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A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis by Abbas Alili, Varun Nalam, Minhan Li, Ming Liu, Jing Feng, Jennie Si, He Huang

“…In addition, we used the developed framework to investigate whether amputee users can exhibit a preference between different profiles during walking and whether they can differentiate between their preferred profile and other profiles when blinded. …”
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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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