Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading by Yanxin Yang, Bai Yang, Chunhui Su, Jianlin Ma

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Optimized predictive maintenance for streaming data in industrial IoT networks using deep reinforcement learning and ensemble techniques by K. Varalakshmi, J. Kumar

“…Extensive simulations, evaluated using accuracy, precision, recall, F1-score, and latency, demonstrate superior performance over traditional methods, minimizing false positives and enhancing fault detection reliability. …”
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On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

“…When dissimilarity is high ([Formula: see text]), no CV method provides accurate evaluations. These results show the importance of considering feature space dissimilarity when working with geospatial machine learning predictions and can help researchers and practitioners to select more suitable CV methods for evaluating their predictions.…”
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Cardiac Clarity: Harnessing Machine Learning for Accurate Heart-Disease Prediction by Sujith Santhosh, Krishnaraj Chadaga, R.Vijaya Arjunan, Sandra D'Souza

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Development and Evaluation of a Machine Learning Model for Predicting 30-Day Readmission in General Internal Medicine by Abdullah M. Al Alawi, Mariya Al Abdali, Al Zahraa Ahmed Al Mezeini, Thuraiya Al Rawahia, Eid Al Amri, Maisam Al Salmani, Zubaida Al-Falahi, Adhari Al Zaabi, Amira Al Aamri, Hatem Al Farhan, Juhaina Salim Al Maqbali

“…This study aimed to develop and evaluate machine learning (ML) models for predicting 30-day readmissions in patients admitted under a GIM unit and to identify key predictors to guide targeted interventions. …”
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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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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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A systematic literature review of swimming performance prediction: methods, datasets, techniques and research trends by Ari Tri Fitrianto, Oddie Barnanda Rizky, Edi Rahmadi, Asary Ramadhan

“…Objective: This paper provides an extensive and systematic review of research in swimming performance prediction published from 2014 to 2024. Method: This swimming performance prediction research was conducted with a Systematic Literature Review (SLR). …”
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Comparative Analysis of Nonlinear Methods for Multivariable Water Level Prediction: The Case Study of the Atrato River by Jackson B. Renteria-Mena, Douglas Plaza, Eduardo Giraldo

“…In addition, a short-term water level prediction is developed for incorporation into a flood early warning system. …”
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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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Methodology for Evaluating Collision Avoidance Maneuvers Using Aerodynamic Control by Desiree González Rodríguez, Pedro Orgeira-Crespo, Jose M. Nuñez-Ortuño, Fernando Aguado-Agelet

“…Compared to constant-drag models, the panel method offers more accurate, orientation-dependent predictions. …”
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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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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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