A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

“…Purpose: Our study aims to fill this crucial void and offers an algorithm to range Russian fairy-tales into classes based on the pre-set parameters. …”
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Integration of bulk RNA-seq and scRNA-seq reveals transcriptomic signatures associated with deep vein thrombosis by Bao-ze Pan, Ming-jun Jiang, Li-ming Deng, Jie Chen, Xian-peng Dai, Zi-xuan Wu, Zhi-he Deng, Dong-yang Luo, Yang-yi-jing Wang, Dan Ning, Guo-zuo Xiong, Guo-shan Bi

“…Topology analysis was performed using seven protein-protein interaction (PPI) network algorithms. The combination of weighted correlation network analysis (WGCNA) and clinical prediction models was employed to validate hub DEGs. …”
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Oil Commodity Movement Estimation: Analysis with Gaussian Process and Data Science by Mulue Gebreslasie, Indranil SenGupta

“…In this study, Gaussian process (GP) regression is used to normalize observed commodity data and produce predictions at densely interpolated time intervals. …”
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Multiplex immunophenotyping of human acute myeloid leukemia patients revealed single -cell heterogeneity with special attention on therapy sensitive and therapy resistant subpopula... by Nikolett Gémes, Benedek Rónaszéki, Szabolcs Modok, Zita Borbényi, Imre Földesi, Éva Trucza, Blanka Godza, Zsuzsanna László, Balázs Csernus, László Krenács, Enikő Bagdi, Enikő Szabó, László G. Puskás, László G. Puskás, Valeria Bertagnolo, Gábor J. Szebeni, Gábor J. Szebeni, Gábor J. Szebeni

“…Unsupervised clustering algorithms such as Uniform Manifold Approximation and Projection for Dimension Reduction (UMAP) and Flow cytometry data that builds Self-Organizing Maps (FlowSOM) were used to reveal the LAIP. …”
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An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

“…Furthermore, this investigation discusses the influence of deformation spatial resolution, the impacts of azimuth determination methodologies, and performance comparisons between non-hybrid and hybrid optimization algorithms. This study demonstrates that aligning the selection of deformation models with different types of prior geological information significantly improves the accuracy of underground goaf detection. …”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. Ten dental implants were retrospectively included in this IRB-approved study. …”
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An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto, Geraldo Pereira Rocha Filho

“…The system combines real-time monitoring, machine learning algorithms for behavioral analysis, and natural language processing to deliver personalized, actionable recommendations through a conversational interface. …”
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Potato precision planter metering system based on improved YOLOv5n-ByteTrack by Cisen Xiao, Changlin Song, Junmin Li, Min Liao, Yongfan Pu, Kun Du

“…The experimental results indicate that: 1) The improved YOLOv5n model exhibits a 56.8% reduction in parameters, a 56.1% decrease in giga floating point operations per second (GFLOPs), a 51.4% reduction in model size, and a 37.0% reduction in Embedded Device Inference Time compared to the YOLOv5n model. …”
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High-Throughput cDNA Screening Utilizing a Low Order Neural Network Filter by Guyang Matthew Huang, James Farkas, Leroy Hood

“…Evaluation of the detections with two other dissimilar computer prediction algorithms yielded strong transmembrane predictions for 15 of the detections, while 8 of the detections resulted in a definitive negative result. …”
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Simultaneous replacement of the aortic valve and hip joint in a patient with critical aortic stenosis and femoral neck fracture by S. V. Petrov, A. S. Peleshok, V. L. Ignatenko, O. M. Mutalibov, V. A. Krivopalov, G. G. Khubulava, N. G. Pilyugov

“…Developing the treatment algorithm for a combination of two or more diseases in this category of patients is the main task. …”
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EFFICACY OF CARDIOVERTER-DEFIBRILLATORS IN PREVENTION OF SUDDEN DEATH AND OVERALL MORTALITY DECREASE IN PATIENTS WITH THE SYNDROME OF DILATION CARDIOMYOPATHY: DIFFERENTIAL APPROA... by O. V. Blagova, A. V. Nedostup, E. V. Zaklyazminskaya

“…Main predictors of the shocks were genetic origin of DCMP (isolated or with myocarditis, 25/75%, comparing with 20/33% in patients with no shocks, p<0,01, HR 1,58, OR 10,93, sensitivity 94,1%, negative predictive value 99,2%), and sustained (HR 18,0, sensitivity 98,1%) and non-sustained ventricular tachycardia (HR 1,43, sensitivity and negative predictive value 100%), decrease of QRS voltage and absence of the signs of LV hypertrophy on ECG (negative predictive value 92,8% and 95,6%).Conclusion. …”
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ALGORITMOS SUPERVISADOS PARA LA PREDICCIÓN DEL ANCHO DE BANDA DE LAS APLICACIONES EN AMAZON WEB SERVICE DESDE UNA PYME RURAL by Ramiro Osorio Diaz, Martha Yaneth Segura Ruiz, Mauricio Alonso Villalba

“…A comparative study of threeneural network algorithms that model a multilayer neural network is performed, selecting the one that has a minimumerror that approaches zero; the selected algorithm is trained from a data source to predict the network traffic thatconnects to the cloud. …”
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Low-Rank Kernel-Based Semisupervised Discriminant Analysis by Baokai Zu, Kewen Xia, Shuidong Dai, Nelofar Aslam

“…Extensive experiments on public databases show that the proposed LRKSDA dimensionality reduction algorithm can achieve better performance than other related kernel SDA methods.…”
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An analysis of the relationship of triglyceride glucose index with diffuse large B-cell lymphoma prognosis: a retrospective study by QingQing Luo, Zhixiang Lei, Haizhou Miao, Ting Huang, Li Yu

“…Calibration curves showed good agreement between the nomogram predictions and actual outcomes, and DCA highlighted the high clinical utility of the model.ConclusionThe TyG index is an independent prognostic factor in DLBCL patients, and the TyG-based nomogram model provides enhanced predictive accuracy compared to the IPI. …”
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Development and evaluation of a triplex real-time PCR assay for enhanced plague diagnostics in Madagascar. by Beza Ramasindrazana, Zoé A Rahalison, Philippe Gauthier, Guillain Mikaty, Zaina I Bodoarison, Lanto A Maminirina, Soloandry Rahajandraibe, Mamy G Randriamanantsoa, Gilbert Kayoko, Jean-Claude Manuguerra, Anne-Sophie Le Guern, Andriamiliharison J Rasamindrakotroka, Minoarisoa Rajerison

“…Following the urban plague outbreak of 2017, a new molecular diagnostic algorithm was developed and introduced into routine use. …”
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Machine Learning Techniques for Classification of Stress Levels in Traffic by Amanda Trojan Fenerich, Egídio José Romanelli, Rodrigo Eduardo Catai, Maria Teresinha Arns Steiner

“… The aim of this study is to apply Machine Learning techniques for predicting and classifying the stress level of people commuting from home to work and also to evaluate the performance of prediction models using feature selection. …”
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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…The results indicate that Ensemble Learning and AdaBoost yield the highest accuracy algorithms in prediction capability as they tend to illustrate the lowest values of mean squared error and mean absolute relative error (%) and highest R-squared values. …”
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Hybrid energy system optimization integrated with battery storage in radial distribution networks considering reliability and a robust framework by Mohammad Javad Aliabadi, Masoud Radmehr

“…The robust optimization results show that in the 33-bus network, the system remains resilient to prediction errors under the worst-case uncertainty scenario, with a 44.53% reduction in production and a 22.18% increase in network demand for a 30% uncertainty budget. …”
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Effectiveness of biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: the BATCH RCT by Cherry-Ann Waldron, Philip Pallmann, Simon Schoenbuchner, Debbie Harris, Lucy Brookes-Howell, Céu Mateus, Jolanta Bernatoniene, Katrina Cathie, Saul N Faust, Josie Henley, Lucy Hinds, Kerry Hood, Chao Huang, Sarah Jones, Sarah Kotecha, Sarah Milosevic, Helen Nabwera, Sanjay Patel, Stéphane Paulus, Colin VE Powell, Jenny Preston, Huasheng Xiang, Emma Thomas-Jones, Enitan D Carrol

“…Children aged between 72 hours and 18 years admitted to hospital and being treated with IV antibiotics for suspected or confirmed bacterial infection were randomised (1 : 1 ratio of allocation) using minimisation for age and centre and using a secure 24-hour web-based randomisation programme to a PCT-guided algorithm versus usual standard care alone. The sample size of 1942 was determined, based on detecting a 1-day reduction in IV antibiotic use (90% power, two-sided) and on a non-inferiority margin of 5% absolute risk difference (RD) in the composite safety outcome (90% power, one-sided), while allowing for up to 10% loss to follow-up. …”
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Blood pressure abnormality detection and interpretation utilizing explainable artificial intelligence by Hedayetul Islam, Md. Sadiq Iqbal, Muhammad Minoar Hossain

“…We have used several ML algorithms (extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), decision tree (DT), and logistic regression (LR)) to predict blood pressure abnormality based on patient's data. …”
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