Score-Predictive Scale for Assessing the Risk of Inguinal and Femoral Hernias Incarceration by B. V. Sigua, V. P. Zemlyanoy, A. A. Kozobin, D. S. Semin

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Social Media Management System for Educational Promotion by Yerik Afrianto Singgalen, Dorien Kartikawangi, Birgitta Narindri Rara Winayu

“…Educational institutions, particularly tourism study programs, face significant challenges in managing fragmented and inefficient social media promotion strategies that hinder student recruitment and weaken institutional visibility. …”
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Machine Learning-Driven Transcriptome Analysis of Keratoconus for Predictive Biomarker Identification by Shao-Hsuan Chang, Lung-Kun Yeh, Kuo-Hsuan Hung, Yen-Jung Chiu, Chia-Hsun Hsieh, Chung-Pei Ma

“…<b>Methods:</b> We analyzed the GSE77938 (PRJNA312169) dataset for differential gene expression (DGE) and performed gene set enrichment analysis (GSEA) using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to identify enriched pathways in keratoconus (KTCN) versus controls. Machine learning algorithms were then used to analyze the gene sets, with SHapley Additive exPlanations (SHAP) applied to assess the contribution of key feature genes in the model’s predictions. …”
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Immersive Technologies in the Educational Practice of Russian Universities by D. P. Ananin, A. Yu. Suvirova

“…Providing immersion of students in the real conditions of professional skills application, immersive educational products are designed to practice the algorithms of operations in standard and non-standard situations of their (future) occupations individually. …”
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Adaptive Event-Triggered Predictive Control for Agile Motion of Underwater Vehicles by Bo Wang, Junchao Peng, Jing Zhou, Liming Zhao

“…A novel adaptive event-triggered nonlinear model predictive control (AET-NMPC) algorithm is proposed and compared with traditional Cascaded Proportional–Integral–Derivative (PID) control and event-triggered cascaded PID control algorithms. …”
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Interpreting Predictive Models through Causality: A Query-Driven Methodology by Mahdi Hadj Ali, Yann Le Biannic, Pierre-Henri Wuillemin

“…Machine learning algorithms have been widely adopted in recent years due to their efficiency and versatility across many fields. …”
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Semantic Differential For Evaluation of Educational Pathway of Personality by Yana Sukhenko

“…The article deals with the issue of personal educational pathway, in particular experimental verification of theoretical ideas of the phenomenon, and the development of the “educational pathway” semantic differential as an adequate tool for its evaluation. …”
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Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching by Biao Kong, Che He

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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…However, machine learning models offer a time-efficient solution for predicting pavement performance. This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. …”
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A predictive model for damp risk in english housing with explainable AI by Gulala Aziz, Adam Hardy

“…This study develops a predictive model for damp risk, using 2,073 inspection records from a housing association across 125 local authorities. …”
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TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance by Xuanbai Yu, Olivier Caspary

“…These findings offer new insights to support reliable predictive maintenance in industrial settings and provide a new perspective for future research into active vibration control, where vibration signal analysis, feature extraction, and mathematical modeling play key roles in optimizing control algorithms and enhancing the efficiency of adaptive control systems.…”
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Personalization of Robot Behavior Using Approach Based on Model Predictive Control by Mateusz Jarosz, Bartlomiej Sniezynski

“…The results suggest that the proposed approach for robot behavior adaptation based on MPC works well, and the recommended algorithm for the user model is LGBM.…”
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Opportunities of Digitalization of Economic Subjects in Educational Process by L. N. Babkina, O. V. Skotarenko

“…In the conditions of the accelerated development of scientific and technical progress, and, first of all, information and computer technologies in scales not only one concrete country, and all set of the developed countries which are in a stage of a post-industrial service state, creation of intercountry communications, the great value is gained by a position of the higher education. Thus, institutions of higher professional education should become so-called points of growth or locomotives of growth of the level of application of information and computer technologies, algorithms for solving economic and management problems based on the use of economic and mathematical methods and models that students master in the process of studying the relevant disciplines. …”
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Predictive Analytics in Agriculture: Machine Learning Models for Coconut Tree Health by Goswami Anjali, Kirit Dhablia Dharmesh

“…The use of remote sensing data in conjunction with ML algorithm results in tremendous increase in predictive capability that facilitates timely interventions and directed management strategies. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Adopt four different noise reduction algorithms for data noise reduction on the raw data of the monitoring points at the intervals of different risk zones, and combine the time series prediction as well as the deep learning prediction method to get the prediction model for environmental risk zoning based on the environmental risk zoning. …”
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Predictive Modeling for Cardiovascular Disease in Patients Based on Demographic and Biometric Data by Abayomi Danlami Babalola, Kayode Francis Akingbade, Daniel Olakunle

“…Ensemble learning exhibits the highest overall accuracy, while SVM and ANN demonstrate strengths in specific aspects of prediction. The study concludes that Machine learning algorithms, particularly ensemble learning, hold significant promise for improving CVD risk assessment. …”
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Algorithm for cavo-tricuspid isthmus flutter on surface ECGs: the ACTIONS study by Daniel R Frisch, Eitan Frankel, Deanna Gill, Jad Al Danaf

“…Using the electrophysiology study as the gold standard, the algorithm had an accuracy of 81%, sensitivity of 81%, specificity of 82%, positive predictive value of 78% and negative predictive value of 84% in identifying CTI-AFL.Conclusion We developed a three-step ECG algorithm that provides a simple, sensitive, specific and accurate tool to identify CTI-AFL.…”
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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. …”
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A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors by Ahmad Aminzadeh, Sasan Sattarpanah Karganroudi, Soheil Majidi, Colin Dabompre, Khalil Azaiez, Christopher Mitride, Eric Sénéchal

“…Integrating machine learning algorithms leveraged by advanced data acquisition systems is emerging as a pivotal approach in predictive maintenance. …”
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An Integrated Algorithm with Feature Selection, Data Augmentation, and XGBoost for Ovarian Cancer by Jingxun Cai, Zne-Jung Lee, Zhihxian Lin, Chih-Hung Hsu, Yun Lin

“…With the rapid development of machine learning, numerous efficient classification prediction models have emerged. These new technologies offer significant opportunities and potential for developing ovarian cancer diagnostic prediction methods. …”
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