Damage Prediction in the Wire Drawing Process by Álvaro González, Marcela Cruchaga, Diego Celentano, Jean-Philippe Ponthot

“…The previously characterized damage models were applied to evaluate their fracture prediction capabilities. A novel presentation method using three-dimensional graphs was employed to indicate the level of damage for each angle and reduction, providing greater sensitivity and insight into the damage values. …”
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Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques by Kiavash Hossein Sadeghi, Mahmood Shafikhah, Arash Marashian, Emad Roshandel, Abolhassan Razminia

“…In this study, we utilized the prediction error method (PEM), a robust algorithm for system identification, to capture the plant’s operational characteristics with precision. …”
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Prediction of 28-day mortality in patients with sepsis based on a predictive model: A retrospective cohort study by Yi Sun, Tingting Wang, Mengna Zhang, Shuchen Cao, Liwei Hua, Kun Zhang

“…The predictive performance of the developed model was evaluated via receiver operating characteristic curves, decision curve analysis, and calibration curves. …”
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Improving appendix cancer prediction with SHAP-based feature engineering for machine learning models: a prediction study by Ji Yoon Kim

“…We propose a framework that integrates SHAP for feature selection, construction, and weighting to enhance accuracy and clinical relevance. Methods Data from the Kaggle Appendix Cancer Prediction dataset (260,000 samples, 21 features) were used in this prediction study conducted from January through March 2025, in accordance with TRIPOD-AI guidelines. …”
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The Predictive Value of Systemic Inflammatory Biomarkers in Predicting Postoperative Systemic Inflammatory Response Syndrome After Percutaneous Nephrolithotomy by Wei Q, Liu A, Sun Z, Zhang S, Hao Z

“…Qi Wei,1,2 AiMin Liu,2 ZhiYong Sun,2 Shuang Zhang,2 ZongYao Hao1 1Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China; Anhui Medical University and Anhui Province Key Laboratory of Genitourinary Diseases, Anhui Medical University, Hefei, People’s Republic of China; 2Department of Urology, Dongcheng Branch of The First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of ChinaCorrespondence: ZongYao Hao, Email haozongyao@163.comPurpose: The aim of the study was to evaluate the predictive significance of several systemic inflammatory biomarkers, namely neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR) and systemic immune inflammatory index (SII) in relation to the occurrence of systemic inflammatory response syndrome (SIRS) after percutaneous nephrolithotomy (PCNL).Methods: A cohort of 317 patients who underwent PCNL were retrospectively recruited and evaluated. …”
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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…This study examines the application of advanced machine learning techniques, combined with metaheuristic optimization methods, to improve predictive models for intradialytic hypotension (IDH) in hemodialysis patients. …”
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Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model by Iolanda Ferreira, Joana Simões, João Correia, Ana Luísa Areia

“…Consequently, concerns on a potential rise in cesarean section (CS) rates after induction of labor (IOL) demand for improved counseling on delivery mode within this context. Material and Methods We aim to develop a prognostic model for predicting vaginal delivery after labor induction using computational learning. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…The experimental results show the exceptional strengths of the proposed LGWO-BP method, particularly its accuracy and reliability compared to GWO-BP, and show that it achieves comparative results against state-of-the-art (SOTA) methods. …”
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Hot question prediction in Stack Overflow by Li Xian Zhao, Li Zhang, Jing Jiang

“…The performance of the VSAF method based on a training set and two different test sets has been evaluated. …”
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Conformational ensembles for protein structure prediction by Jiaan Yang, Wen Xiang Cheng, Peng Zhang, Gang Wu, Si Tong Sheng, Junjie Yang, Suwen Zhao, Qiyue Hu, Wenxin Ji, Qiong Shi

“…The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.…”
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Comparative analysis of sandstone microtomographic image segmentation using advanced convolutional neural networks with pixelwise and physical accuracy evaluation by Mazaher Hayatdavoudi, Mohammad Emami Niri, Ahmad Kalhor

“…Abstract The introduction of deep learning techniques has revolutionized the automated segmentation of digital rock images. These methods enable precise evaluations of critical properties such as porosity and fluid flow characteristics, thereby enhancing the efficiency of reservoir characterization. …”
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Evaluation methods and engineering applications of in-situ stress in deep, strong heterogeneity terrestrial shale oil and gas reservoirs: a case study of jurassic shales in the Yin... by Shujun Yin, Jianliang Zhang, Hucheng Deng, Hucheng Deng, Hao Qin, Wenhao Xia, Yu Du, Ming Gong, Tao Huang, Chang Li

“…A transversely isotropic in-situstress prediction model was developed to evaluate the stress distribution, aiming to identify target layers favorable for hydraulic fracturing.ResultComprehensive analysis indicates that the in-situstress orientation of Jurassic shale in the Yingshan-Pingchang area generally aligns with the regional stress orientation (NE90° ± 10°). …”
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The Functional Characterization of Venous Thromboembolic Disease (FUVID) study: rationale, design, and methods of a prospective, observational, multicenter study to evaluate mechan... by Ayesha Zia, Michael D. Nelson, Jimin Ren, Song Zhang, Robert F. Mattrey, Brian L. Han, Tarique Hussain, Joshua S. Greer, Manal Al-Qahtani, Kendra Malone, Sonja E. Stutzman, Deseray V. Sida, Sharon Primeaux, Marcela D. Torres, Clay T. Cohen, Shelley Crary, Jonathan Bernstein, Hilary B. Whitworth, Riten Kumar, Kisha A. Beg, Osman Khan, Madhvi Rajpurkar, Kerry Hege, Beverly A. Schaefer, Gary M. Woods, Lauren E. Amos, Marisol Betensky, Rukhmi V. Bhat, Sarah O’ Brien, Julie Jaffray, Rohit Jesudas, Martha M. Pacheco, Cristina Tarango, Angela C. Weyand, Hope P. Wilson, Jessica Garcia, Mary P. Dang, Ruchika Sharma, Neil A. Goldenberg, Frederikus A. Klok, Christoph Male, Benjamin Levine, Bryce N. Balmain, Tony G. Babb, Leah M. Adix, BS, Steven Ambrusko, MD, Shames Alaesa, BSc, Kristen Bradley, BSN, RN, Brain R. Branchford, MD, Katie Carlberg, MD, James D. Cooper, MD, Susan A. Corley, MPH, Marissa Di Miero, MBA, Anna Eidenberger, Edith Freyer, DNP, Kevin Guerrero, Arun Gurunathan, MD, Brandon Hathorn, BSc, Muhammad Khan, Shawn D. Lade, BS, Deanna M. Maida, MD, Marie Martinelli, MD, Corey Mozingo, BS, Raksa Moran, RN, Sharon A. Primeaux, MS, Leslie Raffini, MD, MSCE, Rhea Robinson, BSN, Cynthia Sabo, MSN, Negin Saleh, Anjali A. Sharathkumar, MBBS, MD, MS, Rachel Simon, DNP, APRN, CPNP-PC, Lakshmi Srivaths, MD, MacKenzie Tasset, BS, Katrina Williams, BS, Rebekah Summerall Woodward, MPH, Benjamin Levine, Neil A. Goldenberg, MD, PhD, Frederikus A. Klok, MD, PhD, Christoph Male, MS, MSc, Tony G. Babb, PhD, Madhvi Rajpurkar, MD, Song Zhang, PhD

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Modern trends in diagnostics and prediction of results of anti-vascular endothelial growth factor therapy of pigment epithelial detachment in neovascular agerelated macular degener... by E. V. Kozina, S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, L. E. Aksenova

“…Dynamic registration of such biomarkers expands the ability of clinicians to predict morphological changes in pigment epithelial detachment during anti-VEGF therapy, as well as to optimize treatment regimens to prevent complications in the form of pigment epithelium tear leading to a decrease in visual acuity.Modern methods of deep machine learning and the use of neural networks allow achieving higher accuracy in diff erentiating the types of retinal fluids and automating the quantitative determination of fl uid under the pigment epithelium. …”
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Predicting the spatial demand for public charging stations for EVs using multi-source big data: an example from jinan city, china by Qimeng Ren, Ming Sun

“…By using multi-source big data, this paper analyzes the population distribution, traffic organization, infrastructure, land use and regional economy of Jinan urban area, China, and constructs a comprehensive evaluation index system to predict the spatial demand of PCS for EVs. …”
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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. This experimental research focuses on evaluating existing robust cross-validation variants to address the issues of validating credit default models. …”
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Modeling the Impact of Climate Change on Soil Health Using Predictive Analytics by Alsalami Zaid, Mandapati A. H. A. Hussein, Sundari Venkata Rama

“…To answer the problem of soil degradation under climate stress, this research develops and evaluates predictive models capable of predicting soil health indicators. …”
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Teaching microbiological food safety through case studies by Florence Dubois-Brissonnet, Laurent Guillier, Murielle Naıtali

“…This was addressed by designing a specific food safety module (24 hours) in which students were shown how to predict microbiological risks in food products i.e. they were asked to determine product shelf-life according to product formulation, preservation methods and consumption habits using predictive microbiology tools. …”
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Predictive Value of PLR, PNI, and HALP Scores in Ovarian Cancer Staging by Genc SO, Gulturk EA, Kurt B

“…PNI, however, was less predictive. These findings suggest that PLR and HALP could complement existing staging methods, aiding in clinical decision-making. …”
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Predictive modeling of ICU-AW inflammatory factors based on machine learning by Yuanyaun Guo, Wenpeng Shan, Jie Xiang

“…Three machine learning methods, logistic regression (LR), random forest (RF), and extreme gradient boosting (XGB), were used in the 70% participant training set to construct six different models, which were validated and evaluated in the remaining 30% of the participants as the test set. …”
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