Machine Learning in the Teaching Quality of University Teachers: Systematic Review of the Literature 2014–2024 by Walter Zambrano-Romero, Ciro Rodriguez, Josselyn Pita-Valencia, Walter José Zambrano-Romero, José Manuel Moran-Tubay

“…The methodology used is PRISMA, which considers analyzing literature produced between 2014 and 2024 on factors, prediction algorithms, challenges, and limitations to predict the quality of teaching. …”
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Objective methods for assessing the severity of patients condition in a surgical intensive care unit by F. A. Pchelintseva, M. V. Petrova, I. S. Shmyr, K. A. Mironov, E. V. Gameeva

“…Analysis of the objective methods to evaluate the need for prognostic scalesin the intensive care unit for predicting the risk of complications and mortality of cancer patients after elective surgery. …”
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Virtual resource allocation method with the consideration of performance interference among virtual machines by Lei YANG, He-xu XING, Yu DAI, Sai XU, Hao WANG, Bin ZHANG

“…A method for allocating the virtual resource with the consideration of the performance interference among vir-tual machines was proposed.The model for evaluating the performance interference among virtual machines was formed and the method for predicting the performance interference was presented based on the workload pattern of the virtual machine.The predicted result of the performance interference among virtual machines was put into the evaluation of the resource allocation plan to be used as the basis for resource allocation.By doing this,the effectiveness of the resource al-location plan could be insured.The experiments show that the proposed virtual resource allocation method can insure the execution performance of the application deployed on the virtual machines.…”
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Performance Evaluation of CMIP6-GCMs Using Three Spatial Interpolation Methods Over Catchment Area of Koyna Reservoir, India by Sucheta Dumbre, Pradnya Dixit, Shreenivas Londhe

“…The present study evaluates the performance of general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and spatial interpolation methods over the catchment area of the Koyna reservoir in Maharashtra, India. …”
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Comparative Evaluation of Presented Strength Criteria of Anisotropic Rocks Based on Triaxial Experiments by Yongfeng Liu, Zhengxing Yu, Yongming Yin, Jinglin Wen

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Microstructural diffusion MRI for differentiation of breast tumors and prediction of prognostic factors in breast cancer by Xiaoyan Wang, Yan Zhang, Jingliang Cheng, Liangjie Lin, Ying Hu, Anfei Wang, Yong Zhang, Ruhua Wang, Ying Li, Kun Zhang, Wenhua Zhang

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Advancing Geotechnical Evaluation of Wellbores: A Robust and Precise Model for Predicting Uniaxial Compressive Strength (UCS) of Rocks in Oil and Gas Wells by Mohammadali Ahmadi

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Evaluation of the potential of diffusion tensor imaging biomarkers in prediction of white matter changes after brain radiation therapy: A systematic review by Baranoosh Rahmani, Abdurrahim Rahimian, Mahsa Mansourian, Iraj Abedi

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Integrating proximal geophysical sensing and machine learning for digital soil mapping: Spatial prediction and model evaluation using a small dataset by Danilo César de Mello, Gustavo Vieira Veloso, Murilo Ferre de Mello, Marcos Guedes de Lana, Isabelle de Angeli Oliveira, Fellipe Alcantara de Oliveira Mello, Rafael Gomes Siqueira, Lucas Carvalho Gomes, Elpídio Inácio Fernandes-Filho, Carlos Ernesto Gonçalves Reynaud Schaefer, Márcio Rocha Francelino, Emilson Pereira Leite, Tiago Osório Ferreira, José Alexandre Melo Demattê

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ARTIFICIAL INTELLIGENCE IN UNIVERSITY MARKETING: SOME REALITIES AND POSSIBLE APPLICATIONS by Eudochia JOMIR, Grigore BELOSTECINIC

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Structural Response Evaluation of Krylov Subspace-Based Reduced-Order Model for Real-Time Structural Health Monitoring and Prediction of Container Ships by Kichan Sim, Byoung Wan Kim, Jeong Sam Han, Kangsu Lee

“…To address irregular wave loading challenges, we applied a snapshot-based Krylov subspace method. Unlike conventional methods that use unit force vectors in axial directions, this approach considers time-varying pressure distributions from irregular waves. …”
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Comparative evaluation of several toric intraocular lens calculators for predicting postoperative refractive astigmatism in cataract surgery: a real-world study by Haocheng Xian, Bingzhen Li, Ziyao Xia, Chun Zhang, Xuemin Li

“…Six toric IOL calculators were evaluated: Barrett toric calculator (with predicted PCA, measured PCA, and TK), Kane formula (predicted PCA), and EVO 2.0 formula (predicted and measured PCA). …”
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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

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Construction and evaluation of a nomogram prediction model for the risk of epistaxis following nasotracheal intubation: a single-center retrospective cohort study by Jie Chen, Hao Fan, Yuxing Wang, Yuhang Zhu, Ren Zhou, Hua Kang, Hong Jiang

“…Clinical data and imaging findings were collected, and the least absolute shrinkage and selection operator (LASSO) regression, followed by multivariate logistic regression analysis, were used to identify predictors of epistaxis. A nomogram prediction model was constructed, and its performance was evaluated using receiver operating characteristic (ROC) curves, the Hosmer–Lemeshow test, and decision curve analysis. …”
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Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction by Hua Cai, Liuqing Zhou, Yao Hu, Tao Zhou

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Prospective evaluation of mpMRI-derived nomograms for detecting prostate cancer in PI-RADS v2.1 upgraded and non-upgraded lesions by Ying Yi, Hang Wang, Dongliang Cheng, Zhifeng Xu, Xianhai Zhang, Chun Luo, Hai Zhao

“…BackgroundLimited data exist on the performance of Prostate Imaging Reporting and Data System (PI-RADS) v2.1 upgraded and non-upgraded lesions, both alone and in combined with multiparametric MRI (mpMRI) features, for prostate cancer detection.ObjectiveTo evaluate the rates of prostate cancer (PCa) and clinically significant prostate cancer(csPCa) rates in PI-RADS v2.1 upgraded and non-upgraded lesions, and to identify mpMRI features that improve detection accuracy.MethodsThis study included men who underwent mpMRI and ultrasound-guided (US-guided) biopsy from March 2023 to April 2024. …”
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Development and evaluation of a nomogram prediction model for invasion and metastasis in primary liver cancer based on serum CD147 and IL-6 by Wei Zhang, Di Wu, Xinping Wang, Hua Zhang, Ming Yu

“…ObjectiveThis study aims to develop a prediction model for invasive metastasis of primary liver cancer based on serum extracellular matrix metalloproteinase-inducing factor (CD147) and interleukin-6 (IL-6).MethodsBetween July 2022 and August 2024, 170 surgically treated primary hepatocellular carcinoma patients at our hospital were recruited. …”
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Machine learning prediction models for mortality risk in sepsis-associated acute kidney injury: evaluating early versus late CRRT initiation by Chuanren Zhuang, Ruomeng Hu, Ke Li, Zhengshuang Liu, Songjie Bai, Sheng Zhang, Xuehuan Wen

“…Multiple machine learning models were developed and evaluated to predict patient prognosis, with Shapley Additive exPlanations (SHAP) analysis identifying key prognostic factors.ResultsAfter propensity score matching, late CRRT initiation was associated with improved survival probability, but led to increased hospital and ICU stays. …”
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A phase separation-related gene signature for prognosis prediction and immunotherapy response evaluation in gastric cancer with targeted natural compound discovery by Yanjuan Jia, Yuanyuan Ma, Zhenhao Li, Wenze Zhang, Rukun Lu, Wanxia Wang, Chaojun Wei, Chunyan Wei, Yonghong Li, Xiaoling Gao, Tao Qu

“…Conclusions Our study developed a novel PS-related risk model that predicts GC outcomes, characterizes tumor immune microenvironment, evaluates immunotherapy response, and identifies targeting small molecules. …”
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Predicting China’s Energy Consumption and CO₂ Emissions by Employing a Novel Grey Model by Meixia Wang

“…The results show that the optimization method is reasonable. Third, compared with the traditional models GM, GMO, and ARIMA, the OGMW(1,1) provides better simulation and prediction accuracy, and new information can be prioritized more effectively. …”
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