Predictive model of small choroidal melanoma progression after eye-saving treatment based on clinical, morphometric and immunological parameters by E. B. Myakoshina, I. G. Kulikova, N. V. Balatskaya, L. A. Katargina, S. V. Saakyan

“…A formula was calculated where P (z) is the value of the logistic function; Z, linear combination of symptoms; bo , intercept (free term), bi – regression coefficients for parameters Zi.P (z) = 1 : 1 + e – b0– b1z1– b2z2– b3z3– b4z4The logistic function increases monotonically and takes the values from 0 to 1 for any b and Z values [P∈ (0;1)]. …”
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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
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Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures by Nishchal K. Verma

“…The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. …”
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Drug Release Analysis and Optimization for Drug-Eluting Stents by Hongxia Li, Yihao Zhang, Bao Zhu, Jinying Wu, Xicheng Wang

“…The diffusion coefficients and the coating thickness are selected as design variables. …”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Low-frequency rTMS modulates small-world network properties in an AVH-related brain network in schizophrenia by Lin Zhang, Li Guo, Xiaohui Liu, Jing Han, Yuanqiang Zhu, Chaozong Ma, Ye Li, Weiliang Ye

“…Resting-state fMRI data were collected before and after treatment to assess functional connectivity within the predefined 35-region AVH-related network. small-worldness (σ), normalized clustering coefficient (γ), and normalized characteristic path length (λ), as well as functional segregation (clustering coefficient [Cp], local efficiency [El]) and functional integration (global efficiency [Eg], characteristic path length [Lp])—were analyzed before and after rTMS. …”
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Peroral endoscopic myotomy for complex achalasia and the POEM difficulty score: An update by Carmen Ching Hui Yee, Michael Youssef, Matthew Woo, Robert Bechara

“…PDS correlates moderately with procedural efficiency with a correlation coefficient of 0.595 (Spearman's p < 0.001). …”
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Non-Iterative Estimation of Multiscale Geographically and Temporally Weighted Regression Model by Ya-Di Dai, Hui-Guo Zhang

“…The results demonstrate that the non-iterative estimation method for MGTWR significantly enhances computational efficiency while effectively capturing the scale effects of spatiotemporal variation in the regression coefficient functions for each predictor.…”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…The increase of groove parameters (groove width and depth) can enhance the contact pressure, and at the same time, increase the equivalent stress, which may lead to local strength deficiency.Through the sensitivity analysis, the sensitivity coefficients of the radius of the metal seal ring to the equivalent force and contact pressure were found to reach 0.67 and 0.82, which were the dominant variables affecting the sealing performance; the width and depth of the grooves regulated the stress distribution through the geometric compensation mechanism. …”
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On a Solution of a Third Kind Mixed Integro-Differential Equation with Singular Kernel Using Orthogonal Polynomial Method by Ahmad Alalyani, M. A. Abdou, M. Basseem

“…While when using the separation method, we are able to obtain FIE with time coefficients, and these functions are described as an integral operator in time. …”
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Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

“…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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Influence of structural surface roughness on the strength of layered fill bodies based on PFC2D by Jinxing WANG, Zongsheng HU, Huazhe JIAO, Xiaolin YANG, Qi ZHANG, Xiaohui LIU, Ping XU, Junqiang XU, Xun CHEN

“…The relationship between cemented surface roughness and backfill strength is examined by analyzing variables such as cemented surface roughness, mass fraction of slurry, cement-to-sand ratio, and filling interval time. …”
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Vibration Analysis of Rotating Tapered Timoshenko Beams by a New Finite Element Model by Bulent Yardimoglu

“…A new finite element model is developed and subsequently used for transverse vibrations of tapered Timoshenko beams with rectangular cross-section. The displacement functions of the finite element are derived from the coupled displacement field (the polynomial coefficients of transverse displacement and cross-sectional rotation are coupled through consideration of the differential equations of equilibrium) approach by considering the tapering functions of breadth and depth of the beam. …”
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Parametric Study of Fuel Distribution Effects on a Kerosene-Based Scramjet Combustor by Jun Yang, Xian-yu Wu, Zhen-guo Wang

“…The fuel equivalence ratio for each injection port was taken as the design variables. And the combustion efficiency, the total pressure recovery coefficient, and the drag coefficient were chosen as the objective functions. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Numerical solutions for fractional optimal control problems using Mü‎‎‎‎‎‎‎ntz-Legendre polynomials by Mohammad Sahabi, Allahbakhsh Yazdani Cherati

“…To achieve this, stable and efficient methods for calculating the fractional integral and derivative operators of Müntz-Legendre functions based on three-term recurrence formulas and Jacobi-Gauss quadrature rules are presented. …”
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Classification of petroleum origin and integrity by FTIR by FJ. Guzmán-Osorio, VI. Domínguez-Rodríguez, RH. Adams, CE. Lobato-García, A. Guerrero-Peña, JR. Barajas-Hernández

“…The canonic functions derived from the discriminate analysis had correlation coefficients of 0.994, 0.900, and 0.867, among the variables studied and the classification factor. …”
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THE USE OF CORRELATION ANALYSIS OF TWO-DIMENSION STOCHASTIC PROCESS FOR HELICOPTER MAINTENANCE WORKABILITY ESTIMATION by Y. M. Chinyuchin, A. S. Solov’ev

“…The linear correlated dependence is considered as linear or anyconnection close to it between two variables for which the correlated analysis theorem is true.The algorithm of calculated program complex for helicopter maintenance workability estimation consists of five steps: choice of equipment that needs to be installed on the helicopter; correlation coefficient calculation for helicopters having this equipment and revealing of optimal variants of location; zone partition of the developed helicopter and analysis of possi- ble disposal of clusters in optimal order; disposal of clusters on the designed helicopter; correlation coefficient calculation, direct regression construction for the designed helicopter and comparison of these readings with helicopters-analogues. …”
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Bankruptcy rules and sustainable water management: A MODSIM-NSGAII simulation multi-objective optimization framework for equitable transboundary water allocation by Bentolhoda Asl-Rousta, S. Jamshid Mousavi

“…This study addresses these challenges by introducing a new optimal bankruptcy rule (OpPro rule) through a simulation-optimization model (MODSIM-NSGAII), where MODSIM simulates the spatial and temporal variability of water resources, and the NSGA-II optimization algorithm includes two objective functions of maximizing basin-wide ecological sustainability and maximizing economic efficiency reflecting ''equitable and reasonable utilization'' of water. …”
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