Scientific basis for predicting the spread of pests by A. Fedorenko, O. Borzykh, V. Fedorenko, V. Chaika, L. Yushchenko

“…To analyze the existing theories of mass reproduction of insects, to evaluate and test the established and newest methods of monitoring and prospects for their use in modern conditions of pest spread. …”
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Stroke Prediction Based on Machine Learning by Zhang Yuhan

“…Machine learning technology can analyze patients’ historical health data and biometrics to identify high-risk individuals in a timely manner, thereby effectively predicting stroke.This paper evaluates the predictive performance Random Forest and Support Vector Machine (SVM). …”
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Robust Prediction of Wildfire Spread in Australia by Michael Palk, Katharina Knappmann, Stefan Voss, Raka Jovanovic

“…As exact computational simulations of wildfires are not feasible yet, several subtasks such as the estimation of the spread rate were analyzed with various methods in the literature. In this paper, different types of predictive models are evaluated to forecast the spread of wildfires on a daily and weekly basis in a comparative study. …”
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Evaluating Material Parameter Influence on Drapability Using VStitcher by Malin Schiller, Soraya Flohr, Jeanne Marisol Delmas, Anja Krüger, Anne-Marie Miene, Patrizia Zimmermann, Lena Wolf, Miriam Seffers, Michelle-Sophie Ruchay-Drammeh, Ulrike Reinhardt, Lilia Sabantina

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Laryngeal ultrasound for the prediction of severe laryngomalacia. by Arisa Duantaweesook, Vannipa Vathanophas, Kitirat Ungkanont, Archwin Tanphaichitr, Thanakrit Wannarong, Ramida Amornsitthiwat

“…LUS demonstrated diagnostic efficiency for laryngomalacia in 7 out of 19 infants, with a sensitivity of 26.92%, specificity of 100%, negative predictive value of 47.22%, and positive predictive value of 100%. …”
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Prediction of the risk of recurrence of the leprosy process by G. N. Genatullina, A. L. Yasenyavskaya, A. A. Tsibizova, M. A. Samotrueva

“…The aim of the study was to study the degree of neutrophil granulocyte myeloperoxidase activity in peripheral blood of patients with leprosy in order to predict the possible recurrence of the infectious process.Materials and methods. …”
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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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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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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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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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Prediction of soil permeability coefficient using the GEP approach by Mina Torabi, Hamed Sarkardeh, S.Mohammad Mirhosseini

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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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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…The assessment methods for estimating the behavior of the complex mechanics of reinforced concrete (RC) structural elements were primarily based on experimental investigation, followed by the collective evaluation of experimental databases from the available literature. …”
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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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