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  1. 17821

    Pilot Allocation in Multi-Cell MIMO Systems Based on Missing Data Imputation by Bushra Shaikh, Pere Garau Burguera, Hanan Al-Tous, Markku Juntti, Bilal Muhammad Khan, Olav Tirkkonen

    Published 2025-01-01
    “…We consider a pilot allocation algorithm to alleviate pilot contamination in a multi-cell massive MIMO network with missing channel information. …”
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    Article
  2. 17822

    Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

    Published 2024-07-01
    “…The creation of software based on the selected algorithm will make it possible to clarify the real effectiveness of machine learning on a larger population of patients with pancreatic neoplasms.…”
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    Article
  3. 17823

    A comparative approach of analyzing data uncertainty in parameter estimation for a Lumpy Skin Disease model by Edwiga Renald, Miracle Amadi, Heikki Haario, Joram Buza, Jean M. Tchuenche, Verdiana G. Masanja

    Published 2025-01-01
    “…The assessment of the uncertainties is determined with the help of Adaptive Metropolis Hastings algorithm, a Markov Chain Monte Carlo (MCMC) standard statistical method. …”
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  4. 17824
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  7. 17827
  8. 17828
  9. 17829
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  11. 17831

    Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

    Published 2025-05-01
    “…The dataset was divided into training and test set with a ratio of 7:3 with 6 machine learning algorithms implemented to diagnosis pleural effusion. …”
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    Article
  12. 17832

    Estimation of soil organic carbon content and dynamics in Mediterranean climate regions considering long-term monthly climatic conditions by Lei Shen, Wei Zhang, Duanqiang Zhai, Shuo Han, Shuang Tian

    Published 2024-11-01
    “…Results showed that the introduction of long-term average monthly climate data significantly improved the prediction accuracy of the models. The R2 value of the RF model was enhanced by 0.22, whilst the R2 of the LightGBM model improved by 0.20–0.21. …”
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    Article
  13. 17833

    Machine Learning-Based Detection of Archeological Sites Using Satellite and Meteorological Data: A Case Study of Funnel Beaker Culture Tombs in Poland by Krystian Kozioł, Natalia Borowiec, Urszula Marmol, Mateusz Rzeszutek, Celso Augusto Guimarães Santos, Jerzy Czerniec

    Published 2025-06-01
    “…The machine learning models, including logistic regression and decision tree-based algorithms, demonstrated strong potential for predicting site visibility. …”
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    Article
  14. 17834

    Identification and validation of the nicotine metabolism-related signature of bladder cancer by bioinformatics and machine learning by Yating Zhan, Min Weng, Yangyang Guo, Dingfeng Lv, Feng Zhao, Zejun Yan, Junhui Jiang, Yanyi Xiao, Lili Yao

    Published 2024-12-01
    “…Integrative machine learning combination based on 10 machine learning algorithms was used for the construction of robust signature. …”
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    Article
  15. 17835

    Analysis of human brain RNA-seq data reveals combined effects of 4 types of RNA modifications and 18 types of programmed cell death on Alzheimer’s disease by Ke Ye, Xinyu Han, Mengjie Tian, Lulu Liu, Xu Gao, Qing Xia, Dayong Wang

    Published 2025-04-01
    “…Finally, by combining unsupervised consensus clustering, gene co-expression networks, and machine learning algorithms, an RNA modification-related programmed cell death network was constructed, and the pivotal roles of programmed cell death genes in key modules were identified. …”
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    Article
  16. 17836

    Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety by Olly Kravchenko, Julia Bäckman, David Mataix-Cols, James J. Crowley, Matthew Halvorsen, Patrick F. Sullivan, John Wallert, Christian Rück

    Published 2025-05-01
    “…Employing machine learning algorithms capable of capturing complex non-linear associations and interactions is a viable next step to improve prediction of post-ICBT symptom severity. …”
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    Article
  17. 17837

    Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

    Published 2025-03-01
    “…The response surface methodology (RSM) model also proved to be a reliable forecasting tool, indicating its potential as a practical alternative to complex algorithmic computations in scenarios with limited raw data.…”
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    Article
  18. 17838

    Machine learning and SHAP values explain the association between social determinants of health and post-stroke depression by Zhiwei Song, Jilin Weng, Yupeng Han, Wangyu Li, Yiya Xu, Yingchao He, Yinzhou Wang

    Published 2025-08-01
    “…Logistic regression was employed to analyse the association between SDoH and PSD, whereas Cox regression was utilized to assess the correlation between SDoH and all-cause mortality in PSD. The Boruta algorithm was employed for feature selection, and four machine learning models were constructed (CatBoost, Logistic, Multilayer Perceptron, and Random Forest) to evaluate the predictive effectiveness, calibration, and clinical applicability of these ML models. …”
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    Article
  19. 17839

    Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes by Liu Yang, Li Du, Yuanyuan Ge, Muhui Ou, Wanyan Huang, Xianmei Wang

    Published 2025-01-01
    “…Abstract Objective This study aimed to evaluate the predictive performance of inflammatory and nutritional indices for adverse cardiovascular events (ACE) in patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI) using a machine learning (ML) algorithm. …”
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    Article
  20. 17840

    Hygienic substantiation of calculating models for prognosis of toxicity of different classes insecticides (second part) by O.P. Vavrinevych, B.I. Shpak, A.M. Antonenko, S.T. Omelchuk, T.I. Zinchenko

    Published 2020-12-01
    “…The purpose of the research is the scientific substantiation and statistical analysis of the calculation models for predicting the toxicity of insecticides of different classes. …”
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    Article