A Comparative Analysis of Machine Learning Models for Predicting EFL Student Language Performance in Smart Learning Environments by Banchakarn Sameephet, Wirapong Chansanam, Mahboubeh Rakhshandehroo, Chawin Srisawat, Kittichai Nilubol, Arnon Jannok, Bhirawit Satthamnuwong, Kornwipa Poonpon

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Predicting Travel Insurance Purchases in an Insurance Firm through Machine Learning Methods after COVID-19 by Shiuh Tong Lim, Joe Yee Yuan, Khai Wah Khaw, XinYing Chew

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Evaluating variable selection methods for multivariable regression models: A simulation study protocol. by Theresa Ullmann, Georg Heinze, Lorena Hafermann, Christine Schilhart-Wallisch, Daniela Dunkler, for TG2 of the STRATOS initiative

“…These methods will be compared with respect to false inclusion and/or exclusion of variables, consequences on bias and variance of the estimated regression coefficients, the validity of the confidence intervals for the coefficients, the accuracy of the estimated variable importance ranking, and the predictive performance of the selected models. …”
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Benchmarking of Anomaly Detection Methods for Industry 4.0: Evaluation, Ranking, and Practical Recommendations by Aurélie Cools, Mohammed Amin Belarbi, Sidi Ahmed Mahmoudi

“…Quality control and predictive maintenance are two essential pillars of Industry 4.0, aiming to optimize production, reduce operational costs, and enhance system reliability. …”
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Predictive potential of combined secretomics and image-based morphometry as a non-invasive method for selecting implanting embryos by Andrea Palomar, Roberto Yagüe-Serrano, Juan Vicente Martínez-Sanchis, Ignacio Iniesta, Alicia Quiñonero, Pedro José Fernández-Colom, Ana Monzó, José María Rubio, Inmaculada Molina, Francisco Domínguez

“…Forty-seven morphometric parameters related to the trophoblast, inner cell mass and blastocele dimension were evaluated in microphotographs of day 5 embryos with ImageJ software. …”
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Predictive maintenance of belt conveyor drives based on the analysis of lubricating oil parameters by Kuzin E.G., Mamaeva M.S., Komarov D.S.

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DATA ANALYSIS OF TRAFFIC ACCIDENTS AND THEIR CAUSES IN GOMEL FOR 2013 AND 2014 by S. A. Azemsha, V. N. Galushko, S. V. Skirkovski, Yu. A. Vrubel

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A Comprehensive Comparative Analysis of Deep Learning Models for Student Performance Prediction in Virtual Learning Environments: Leveraging the OULA Dataset and Advanced Resamplin... by Bayan A. Alnasyan, Mohammed Basheri, Madini O. Alassafi

“…Predicting student performance in Virtual Learning Environments (VLEs) has become increasingly important with the growth of online education. …”
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Evaluation and reliability prediction for highly reliable software and hardware systems: The case of data processing centers by G. V. Petushkov

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Evaluation of Shelf Life Prediction for Broccoli Based on Multispectral Imaging and Multi-Feature Data Fusion by Xiaoshuo Cui, Xiaoxue Sun, Shuxin Xuan, Jinyu Liu, Dongfang Zhang, Jun Zhang, Xiaofei Fan, Xuesong Suo

“…Broccoli shelf life prediction models were evaluated using three classification methods: RF, 1D-CNN, and 2D-CNN. …”
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Using Monte Carlo conformal prediction to evaluate the uncertainty of deep-learning soil spectral models by Y.-C. Huang, J. Padarian, B. Minasny, A. B. McBratney

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Evaluating the Accuracy of Land-Use Change Models for Predicting Vegetation Loss Across Brazilian Biomes by Macleidi Varnier, Eliseu José Weber

“…The predicted maps were evaluated by comparing them with reference land-use maps using rigorous accuracy methods. …”
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MACHINE LEARNING BASED PREDICTION AND INSIGHTS OF DIABETES DISEASE: PIMA INDIAN AND FRANKFURT DATASETS by Mohammad Raquibul Hossain, Md. Jamal Hossain, Md. Mijanoor Rahman, Mohammad Manjur Alam

“…This paper focused on predicting diabetes disease using machine learning models which is a very active and highly important area of research. …”
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Predicting deamidation and isomerization sites in therapeutic antibodies using structure-based in silico approaches by David Hoffmann, Joschka Bauer, Markus Kossner, Andrew Henry, Anne R. Karow-Zwick, Giuseppe Licari

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Evaluating combinations of rainfall datasets and optimization techniques for improved hydrological predictions using the SWAT+ model by Mahesh R. Tapas, Randall Etheridge, Thanh-Nhan-Duc Tran, Manh-Hung Le, Brian Hinckley, Van Tam Nguyen, Venkataraman Lakshmi

“…The combination of the GPM IMERG dataset and the GLUE method proved most effective, offering valuable guidance for selecting optimal datasets and methods to enhance prediction accuracy in complex watersheds.…”
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Critical evaluation of feature importance assessment in FFNN-based models for predicting Kamlet-Taft parameters by Yoshiyasu Takefuji

“…Mohan et al. developed a feed-forward neural network (FFNN) model to predict Kamlet-Taft parameters using quantum chemically derived features, achieving notable predictive accuracy. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

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Evaluation of physiological severity scores for predicting COVID-19 disease progression: a retrospective study by Sujaree Poopipatpab, Ratchaya Weerayutwattana, Pruchwilai Nuchpramool, Piyarat Phairatwet, Tospon Lertwattanachai, Konlawij Trongtrakul

“…Therefore, this study aimed to evaluate the performance of the severity scores upon admission in predicting the progression of COVID-19 patients to a severe condition within 14 days after hospitalization. …”
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Establishment and evaluation cuproptosis-related gene signature for predicting the prognosis and immunotherapy response of hepatocellular carcinoma by Shuo Wang, Xinzi Xue, Hongyan Bai, Junwen Qi, Sujuan Fei, Bei Miao

“…Immune checkpoint, drug sensitivity, and IPS were used to evaluate immunotherapy response. The model’s predictive ability was further validated with the ICGC database and IMvigor210 cohort. …”
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Evaluating variant pathogenicity prediction tools to establish African inclusive guidelines for germline genetic testing by Kangping Zhou, Kazzem Gheybi, Pamela X. Y. Soh, Vanessa M. Hayes

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