T2D-LVDD: neural network-based predictive models for left ventricular diastolic dysfunction in type 2 diabetes by Yu Rong, Wei Liu, Ke Li, Jian Guo, Xue-Ping Li

“…We trained an artificial neural network model to predict LVDD risk with patients’ clinical information. …”
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An Intraoperative Ultrasound Evaluation of Axillary Lymph Nodes: Cassandra Predictive Models in Patients with Breast Cancer—A Multicentric Study by Simona Parisi, Francesco Saverio Lucido, Federico Maria Mongardini, Roberto Ruggiero, Francesca Fisone, Salvatore Tolone, Antonio Santoriello, Francesco Iovino, Domenico Parmeggiani, David Vagni, Loredana Cerbara, Ludovico Docimo, Claudio Gambardella

“…A two-tiered model was finally set up, leveraging the strong predictive capabilities of SWEH and RI. …”
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Artificial Intelligence in Ovarian Cancer: A Systematic Review and Meta-Analysis of Predictive AI Models in Genomics, Radiomics, and Immunotherapy by Mauro Francesco Pio Maiorano, Gennaro Cormio, Vera Loizzi, Brigida Anna Maiorano

“…Pooled AUCs indicated strong predictive performance for genomics-based (0.78), radiomics-based (0.88), and immunotherapy-based (0.77) models. …”
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Predictive Models with Applicable Graphical User Interface (GUI) for the Compressive Performance of Quaternary Blended Plastic-Derived Sustainable Mortar by Aïssa Rezzoug, Ahmed A. Abdou Elabbasy, Muwaffaq Alqurashi, Ali H. AlAteah

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Identification of hub immune-related genes and construction of predictive models for systemic lupus erythematosus by bioinformatics combined with machine learning by Su Zhang, Weitao Hu, Yuchao Tang, Hongjie Lin, Xiaoqing Chen

“…In this study, we identified five hub DE-IRGs in SLE and constructed an effective predictive model. These hub genes are closely associated with immune cell in SLE. …”
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Evaluating microstructural and machine learning predictive models for friction drilling of sustainable snail shell reinforced aluminium matrix composites by Rajesh Jesudoss Hynes Navasingh, R. Sankaranarayanan, Priyanka Mishra, Angela Jennifa Sujana J, Jebasingh Jeremiah Rajesh, Jana Petru

“…Random Forest (RF), Multilayer Perceptron (MLP), Gaussian Process Regression (GPR) and Support Vector Machine (SVM) models were employed for the prediction of distinct output responses.…”
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Condition Monitoring and Predictive Maintenance in Industrial Equipment: An NLP-Assisted Review of Signal Processing, Hybrid Models, and Implementation Challenges by Jose Garcia, Luis Rios-Colque, Alvaro Peña, Luis Rojas

“…In response, advanced machine learning, deep learning, and sophisticated signal processing techniques have emerged as transformative solutions for fault detection and predictive maintenance. To address the complexity of these advancements and their practical implications, this review combines analyses from large language models with expert validation to categorize key methodologies—spanning classical machine learning models, deep neural networks, and hybrid physics–data approaches. …”
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Potential role of predictive models in assessment of liver inflammation in patients with hepatocellular carcinoma: a two-center cohort study by Wei Xu, Bolun Li, Huai Gong, Jingdong Li, Zhanwei Yang, Yu Liu

“…This study aimed to construct a clinically expedient predictive model to grade hepatic inflammation in HCC patients. …”
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Geochemical Pathways Defined by Predictive Regolith-Landform Models Using TanDEM-X Data in the Tanami Region, Australia by Richard Llewellyn Langford

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Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

Subjects: “…link prediction…”
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Unleashing Predicting a Comparative Study of Machine Learning for Bankruptcy Risk Prediction by Yupeng Li, Ke Sun

“…Predictive analytics are advanced through the utilization of sophisticated machine learning methodologies, specifically the Random Forest classification model (RFC), The Grasshopper Optimizer Algorithm (GOA), and the Artificial Rabbits Optimizer (ARO). …”
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A prediction model for guiding tumor microwave ablation surgery based on simulation by Lu Qian, Yamin Yang, Pan Chen, Jia Liu, Xiaofei Jin, Zhiyu Qian, Chunxiao Chen

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Boosting Cervical Cancer Prediction Leveraging a Hybrid FT-Transformer Model by Md Emamul Hossen, S. M. Mahim, Shakib Al Hasan, Md Khairul Islam, Md Shohidul Islam, Salahuddin Khan, Mohammad Alibakhshikenari, Peiman Parand, Md Sipon Miah

“…To address this critical clinical need, we propose an innovative Hybrid FT-Transformer model that synergistically integrates a Feature Tokenization (FT) Transformer with Depthwise convolutional neural networks and Long Short-Term Memory (LSTM) networks for precise CC prediction. …”
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Milling-Force Prediction Model for 304 Stainless Steel Considering Tool Wear by Changxu Wang, Yan Li, Feng Gao, Kejun Wu, Kan Yin, Peng He, Yunjiao Xu

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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…Multiple tests were performed by different machine learning classifiers, mainly in predicting learning style and recommending an assessment methodology. …”
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Analysis of a double Poisson model for predicting football results in Euro 2020. by Matthew J Penn, Christl A Donnelly

“…This paper examines the pre-tournament predictions made using this model for the Euro 2020 football tournament. …”
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Charging-Related State Prediction for Electric Vehicles Using the Deep Learning Model by De Zhao, Hua Wang, Zhiyuan Liu

“…Among all states, the proposed model has a higher prediction accuracy on “home stop” (89.0%). …”
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Predicting Market Value of Iranian Football Players using Linear Modeling Techniques by Rasool Nazari, Saeid Azari

“…Purpose: The purpose of this study was to predict the market value of professional football players in the Iranian Premier League in the 2020-2021 season of Iranian football.Methods: method of the present study was descriptive-survey. …”
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Predicting Course Grades Through Comprehensive Modeling of Students’ Learning Behavioral Patterns by Danial Hooshyar, Yeongwook Yang

“…This study aims to model students’ online learning behavior and accordingly predict their course achievement. …”
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Spherical assembly model and prediction of pressure loss of porous media flow in goaf by Fangxing CHEN, Xiaoli HAO, Shiqiang CHEN, Yiqun LI, Shilin LI, Yi LU

“…The model is used to predict the pressure loss, and the simulation results are compared with the predicted values of Ergun equation. …”
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