Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, B. O. Shcheglov, E. A. Kokarev

“…These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. …”
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Wireless Sensor Networks Focusing on Predicting Average Localization Error through Machine Learning Applications by Ioanna Gounari, Mattheos Kanzilieris

“…This research offers valuable insights into the effectiveness of different ML algorithms for predicting ALE in WSNs. By demonstrating the superior performance of DTRT, the study guides practitioners and researchers in selecting models that enhance localization accuracy, ultimately improving the overall functionality of WSNs.…”
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Development of machine learning models to predict the risk of fungal infection following flexible ureteroscopy lithotripsy by Haofang Zhang, Changbao Xu, Chenge Hu, Yunlai Xue, Daoke Yao, Yifan Hu, Ankang Wu, Miao Dai, Hang Ye

“…Our study aimed to construct a machine learning algorithm predictive model to predict the risk of fungal infection following F-URL. …”
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Study on an interpretable prediction model for pile bearing capacity based on SHAP and BP neural networks by Shunbo Li, Mingwei Hai, Qi Zhang, Bin Zhou, Miao Wang, Zhuo Zhao

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Predicting autoimmune thyroiditis in primary Sjogren’s syndrome patients using a random forest classifier: a retrospective study by Jia-yun Wu, Jing-yu Zhang, Wen-qi Xia, Yue-ning Kang, Ru-yi Liao, Yu-ling Chen, Xiao-min Li, Ya Wen, Fan-xuan Meng, Li-ling Xu, Sheng-hui Wen, Hui-fen Liu, Yuan-qing Li, Jie-ruo Gu, Qing Lv, Yong Ren

“…It is feasible to predict AIT in pSS using machine learning algorithms. …”
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A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF by Zenzen, Roumaissa, Ayadi, Ayoub, Benaissa, Brahim, Belaidi, Idir, Sukic, Enes, Khatir, Tawfiq

“…Additionally, the YUKI algorithm, leveraging population clustering for optimisation, is introduced. …”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

“…In this study, we conducted a comprehensive meta-analysis to analyze the relationship between the machine learning model performance and variables such crop type, the type of aerial phenotyping platform, the phenological stage, etc A trait-based comparison of the efficiency and popularity of machine learning algorithms was conducted. Our findings showed that the multiple linear regression is the most effective model in predicting biomass while artificial neural networks showed up as the top performing algorithm in determining nitrogen content. …”
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Improving Moth-Flame Optimization Algorithm by using Slime-Mould Algorithm by Sami N. Hussein, Nazar K. Hussein

“…The two predicted new algorithms were tested with standard test functions and the results were encouraging compared to the standard algorithms. …”
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Finite Element and Machine Learning-Based Prediction of Buckling Strength in Additively Manufactured Lattice Stiffened Panels by Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Szabolcs Szávai, Gyula Varga

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Integrating Bioengineering and Machine Learning: A Multi-Algorithm Approach to Enhance Agricultural Sustainability and Resource Efficiency by Senthil G.A., Prabha R., Asha R.M., Suganthi S.U., Sridevi S.

“…Findings have indicated that the multi-algorithm approach not only promotes increased predictive capabilities and resource optimization but also raises food safety with the increased threats in agriculture.…”
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Machine learning-based prediction of in-hospital mortality for critically ill patients with sepsis-associated acute kidney injury by Tianyun Gao, Zhiqiang Nong, Yuzhen Luo, Manqiu Mo, Zhaoyan Chen, Zhenhua Yang, Ling Pan

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Model Predictive Control of Electric Water Heaters in Individual Dwellings Equipped with Grid-Connected Photovoltaic Systems by Oumaima Laguili, Julien Eynard, Marion Podesta, Stéphane Grieu

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Machine Learning for Predicting Required Cross-Sectional Dimensions of Circular Concrete-Filled Steel Tubular Columns by Anton Chepurnenko, Samir Al-Zgul, Vasilina Tyurina

“…The first and second models are based on the CatBoost algorithm. They predict the column diameter at minimum and maximum wall thicknesses, respectively. …”
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Wavelet Decomposition-Based AVOA-DELM Model for Prediction of Monthly Runoff Time Series and Its Applications by ZHANG Yajie

Subjects: “…monthly runoff prediction…”
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Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM by Weigang Fu, Haitao Wang, Kuankuan Zhang, Xia Wang, Kunlun Chen, Chunmei Sun, Zhengwei Wang, Liuyang Song, Niannian Wang

“…Corrosion represents a major cause of damage and leakage in oil and gas pipelines, making accurate corrosion rate prediction critical for operational safety. This study establishes an average corrosion rate prediction model using the Sparrow Search Algorithm-optimized Light Gradient Boosting Machine (SSA-LightGBM). …”
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Learning path planning methods based on learning path variability and ant colony optimization by Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao

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All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning by Min A, Liu Y, Fu M, Hou Z, Wang Z

Subjects: “…Mortality、Intertrochanteric fractures、Femoral neck fractures、Boruta algorithm、Machine learning、Prediction model…”
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Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study by Prasanta Kumar Samal, R. Srinidhi, Pramod Kumar Malik, H. J. Manjunatha, Imran M. Jamadar

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Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products by Ehsan Mohsennia, Alireza Javid, Vahab Toufigh

“…Among the models tested, the CatBoost (CB) algorithm, optimized with the Whale Optimization Algorithm (WOA), exhibited outstanding predictive performance. …”
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Establishment and Solution Test of Wear Prediction Model Based on Particle Swarm Optimization Least Squares Support Vector Machine by Xiao Huang, Yongguo Wang, Yuhui Mao

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