Filtration of histogram evaluation of probability density based on fuzzy data accessibility to a grouping interval by A. V. Ausiannikau, V. M. Kozel

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Challenges and Ethical Considerations in Implementing Assistive Technologies in Healthcare by Eleni Gkiolnta, Debopriyo Roy, George F. Fragulis

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Fractional Stochastic Van der Pol Oscillator with Piecewise Derivatives by Atul Kumar, Khursheed Alam, Mati ur Rahman, Homan Emadifar, Geeta Arora, Ahmed A. Hamoud

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Optimization of Parameters of Two-Beam Laser Twelding of Quartz Raw Materials by V. A. Emelyanov, E. B. Shershnev, Y. V. Nikitjuk, S. I. Sokolov, I. Y. Aushev

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Potential Herb-Drug Interactions Among Elderly Nursing Home Residents in Romania by Hanna Sebesi, László István Bába, Melinda Kolcsár, Zsolt Gáll, Soma Dávid

“…AIM: Our study investigates the algorithm-predicted HDIs during herb-drug coadministration among elderly patients in nursing homes in a Romanian sample. …”
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In vivo and in silico dynamics of the development of Metabolic Syndrome. by Yvonne J W Rozendaal, Yanan Wang, Yared Paalvast, Lauren L Tambyrajah, Zhuang Li, Ko Willems van Dijk, Patrick C N Rensen, Jan A Kuivenhoven, Albert K Groen, Peter A J Hilbers, Natal A W van Riel

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METHODS OF FORMING THE STRUCTURE OF KNOWLEDGE by Tatyana A. Snegiryova, Irina A. Grishanova

“…Cherepanov; taxonomy and thesaurus approach when creating a model of taxonomic structure of knowledge, as well as models of the formation of the knowledge structure.Results. The algorithm, stages and procedures of knowledge structure formation of trainees are considered in detail; the model of the given process is created; the technology of content selection of a teaching material due to the fixed time that has been released on studying of concrete discipline is shown.Scientific novelty and practical significance. …”
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A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…Moreover, the GRA-TOPSIS-RFR method significantly outperforms existing optimization and prediction models, with the integration of the RFR model enhancing prediction accuracy by 42.6% compared to traditional linear regression approaches. …”
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Novel insights of disulfidptosis-mediated immune microenvironment regulation in atherosclerosis based on bioinformatics analyses by Huanyi Zhao, Zheng Jin, Junlong Li, Junfeng Fang, Wei Wu, J. F. Fang

“…Furthermore, a nomogram including hub genes was established that accurately predicted the occurrence of AS. The consensus clustering algorithm was used to separate patients with early atherosclerotic plaques and patients with advanced atherosclerotic plaques into two disulfidptosis subtypes. …”
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The RF–Absolute Gradient Method for Localizing Wheat Moisture Content’s Abnormal Regions with 2D Microwave Scanning Detection by Dong Dai, Zhenyu Wang, Hao Huang, Xu Mao, Yehong Liu, Hao Li, Du Chen

“…For quantifying the wheat’s MC, a dual-parameter wheat MC prediction model with the random forest (RF) algorithm was constructed, achieving a high accuracy (R² = 0.9846, MSE = 0.2768, MAE = 0.3986). …”
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Disrupted fetal carbohydrate metabolism in children with autism spectrum disorder by Serena B. Gumusoglu, Brandon M. Schickling, Donna A. Santillan, Lynn M. Teesch, Mark K. Santillan

“…Untargeted principle components analysis of all metabolites did not reveal group differences, while targeted biomarker assessment (using only Fructose 6-phosphate, D-Mannose, and D-Fructose) by a Random Forest algorithm generated an area under the curve (AUC) = 0.766 (95% CI: 0.612–0.896) for ASD prediction. …”
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Development and Analysis of Patient-Based Complete Conducting Airways Models. by Rafel Bordas, Christophe Lefevre, Bart Veeckmans, Joe Pitt-Francis, Catalin Fetita, Christopher E Brightling, David Kay, Salman Siddiqui, Kelly S Burrowes

“…Other studies have incorporated an algorithmic approach to extrapolate CT segmented airways in order to obtain a complete conducting airway tree down to the level of the acinus. …”
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A deep learning software tool for automated sleep staging in rats via single channel EEG by Andrew Smith, Snezana Milosavljevic, Courtney J. Wright, Charlie A. Grant, Ana Pocivavsek, Homayoun Valafar

“…The algorithm was able to predict key parameters of sleep architecture, including total bout duration, average bout duration, and number of bouts, with significant accuracy. …”
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Single-cell and spatial transcriptomic analysis reveals tumor cell heterogeneity and underlying molecular program in colorectal cancer by Teng Wang, Zhaoming Chen, Wang Wang, Wang Wang, Heng Wang, Shenglong Li

“…However, this heterogeneity offers opportunities for personalized therapy.MethodsThe consensus non-negative matrix factorization algorithm was employed to analyze single-cell transcriptomic data from CRC, which helped identify malignant cell expression programs (MCEPs). …”
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Investigation of the influence of the heterogeneous structure of concrete on its strength by V.M. Volchuk, M.A. Kotov, Ye G. Plakhtii, O.A. Tymoshenko, O.H. Zinkevych

“…The relevance of the work lies in the possibility to carry out express-assessment of the quality of concrete products and structures using the developed algorithm with the use of portable equipment: photographing the structure of concrete; estimation of the range of colour range of the structure elements; calculation of the fractal dimensionality of the structure elements using the developed program; automatic strength prediction. …”
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Block Markov superposition transmission of LDPC codes by Qianfan Wang, Kongjing Guo, Xiao Ma

“…For decoding, the sliding window decoding algorithm with sum-product or min-sum implementations can be employed, inheriting a relatively low-latency decoding. …”
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Exothermic thermosolutal convection in a nanofluid-filled square cavity with a rotating Z-Fin: ISPH and AI integration by Kuiyu Cheng, Abdelraheem M. Aly, Nghia Nguyen Ho, Sang-Wook Lee, Andaç Batur Çolak, Weaam Alhejaili

“…The ANN model, employing the Levenberg–Marquardt algorithm, achieved a coefficient of determination $ R = 0.99994 $ and a mean squared error $ \text{MSE} = 4.21\times {10}^{-6} $, demonstrating its reliability in predicting thermal performance. …”
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VAS value set still has its own application value compare with TTO value set of EQ-5D-3L in Chinese population by Lin Zhuo, Siyuan Gao, Rui Jin, Lang Zhuo, Xiuying Wang

“…Conclusions We recommend VAS value set, Model 2, as the reference of scoring algorithm when using EQ-5D-3L in large scale survey of Chinese population.…”
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Unveiling global flood hotspots: Optimized machine learning techniques for enhanced flood susceptibility modeling by Mahdi Panahi, Khabat Khosravi, Fatemeh Rezaie, Zahra Kalantari, Jeong-A. Lee

“…New hydrological insights for the region: This study reveals that the SVR-GWO model has the best performance in predicting flood-prone areas worldwide based on AUC, RMSE and MSE. …”
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Evaluating soil erosion zones in the Kangsabati River basin using a stacking framework and SHAP model: a comparative study of machine learning approaches by Javed Mallick, Saeed Alqadhi, Swapan Talukdar, Md Nawaj Sarif, Tania Nasrin, Hazem Ghassan Abdo

“…The study considered 17 factors in four primary categories: topographic, climatic, soil, and land use/land cover (LULC). The Boruta algorithm assessed the importance of these variables. …”
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